libarchive-c-2.9/ 0000755 0002166 0000144 00000000000 13553052677 014655 5 ustar changaco users 0000000 0000000 libarchive-c-2.9/.gitattributes 0000644 0002166 0000144 00000000031 13017341356 017530 0 ustar changaco users 0000000 0000000 version.py export-subst
libarchive-c-2.9/.gitignore 0000644 0002166 0000144 00000000101 13017341361 016617 0 ustar changaco users 0000000 0000000 *.egg-info/
/build/
/dist/
/env/
/htmlcov/
.coverage
*.pyc
.tox/
libarchive-c-2.9/.travis.yml 0000644 0002166 0000144 00000001623 13553041177 016761 0 ustar changaco users 0000000 0000000 language: python
matrix:
include:
- python: 3.5
env: TOXENV=py27,py35
- python: 3.6
env: TOXENV=py36
- python: 3.7
env: TOXENV=py37
- python: 3.8-dev
env: TOXENV=py38
branches:
only:
- master
cache:
directories:
- /opt/python-libarchive-c
env:
global:
- LIBARCHIVE=/opt/python-libarchive-c/lib/libarchive.so
before_install:
- sudo apt-get install -y zlib1g-dev liblzma-dev libbz2-dev libxml2-dev nettle-dev libattr1-dev libacl1-dev
- "if [ ! -e $LIBARCHIVE ]; then
wget http://libarchive.org/downloads/libarchive-3.3.2.tar.gz &&
tar -xf libarchive-3.3.2.tar.gz && cd libarchive-3.3.2 &&
./configure --prefix=/opt/python-libarchive-c --disable-bsdcpio --disable-bsdtar &&
make && sudo make install && cd .. ;
fi"
install: pip install tox
script: tox
notifications:
email: false
sudo: required
dist: xenial
libarchive-c-2.9/LICENSE.md 0000644 0002166 0000144 00000000063 13307216353 016246 0 ustar changaco users 0000000 0000000 https://creativecommons.org/publicdomain/zero/1.0/
libarchive-c-2.9/MANIFEST.in 0000644 0002166 0000144 00000000023 13017341352 016370 0 ustar changaco users 0000000 0000000 include version.py
libarchive-c-2.9/Makefile 0000644 0002166 0000144 00000000377 13017341361 016306 0 ustar changaco users 0000000 0000000 clean:
rm -rf build dist *.egg-info
find . -name \*.pyc -delete
chmod:
git ls-files -z | xargs -0 chmod u=rwX,g=rX,o=rX
dist: chmod
python3 setup.py sdist bdist_wheel
python2 setup.py sdist
upload: chmod
python3 setup.py sdist bdist_wheel upload
libarchive-c-2.9/PKG-INFO 0000644 0002166 0000144 00000005532 13553052677 015757 0 ustar changaco users 0000000 0000000 Metadata-Version: 2.1
Name: libarchive-c
Version: 2.9
Summary: Python interface to libarchive
Home-page: https://github.com/Changaco/python-libarchive-c
Author: Changaco
Author-email: changaco@changaco.oy.lc
License: CC0
Description: .. image:: https://travis-ci.org/Changaco/python-libarchive-c.svg
:target: https://travis-ci.org/Changaco/python-libarchive-c
A Python interface to libarchive. It uses the standard ctypes_ module to
dynamically load and access the C library.
.. _ctypes: https://docs.python.org/3/library/ctypes.html
Installation
============
pip install libarchive-c
Compatibility
=============
python
------
python-libarchive-c is currently tested with python 2.7, 3.4, 3.5, and 3.6.
If you find an incompatibility with older versions you can send us a small patch,
but we won't accept big changes.
libarchive
----------
python-libarchive-c may not work properly with obsolete versions of libarchive such as the ones included in MacOS. In that case you can install a recent version of libarchive (e.g. with ``brew install libarchive`` on MacOS) and use the ``LIBARCHIVE`` environment variable to point python-libarchive-c to it::
export LIBARCHIVE=/usr/local/Cellar/libarchive/3.3.3/lib/libarchive.13.dylib
Usage
=====
Import::
import libarchive
To extract an archive to the current directory::
libarchive.extract_file('test.zip')
``extract_memory`` extracts from a buffer instead, and ``extract_fd`` extracts
from a file descriptor.
To read an archive::
with libarchive.file_reader('test.7z') as archive:
for entry in archive:
for block in entry.get_blocks():
...
``memory_reader`` reads from a memory buffer instead, and ``fd_reader`` reads
from a file descriptor.
To create an archive::
with libarchive.file_writer('test.tar.gz', 'ustar', 'gzip') as archive:
archive.add_files('libarchive/', 'README.rst')
``memory_writer`` writes to a memory buffer instead, ``fd_writer`` writes to a
file descriptor, and ``custom_writer`` sends the data to a callback function.
You can also find more thorough examples in the ``tests/`` directory.
License
=======
`CC0 Public Domain Dedication `_
Keywords: archive libarchive 7z tar bz2 zip gz
Platform: UNKNOWN
Description-Content-Type: text/x-rst
libarchive-c-2.9/README.rst 0000644 0002166 0000144 00000003741 13402200204 016317 0 ustar changaco users 0000000 0000000 .. image:: https://travis-ci.org/Changaco/python-libarchive-c.svg
:target: https://travis-ci.org/Changaco/python-libarchive-c
A Python interface to libarchive. It uses the standard ctypes_ module to
dynamically load and access the C library.
.. _ctypes: https://docs.python.org/3/library/ctypes.html
Installation
============
pip install libarchive-c
Compatibility
=============
python
------
python-libarchive-c is currently tested with python 2.7, 3.4, 3.5, and 3.6.
If you find an incompatibility with older versions you can send us a small patch,
but we won't accept big changes.
libarchive
----------
python-libarchive-c may not work properly with obsolete versions of libarchive such as the ones included in MacOS. In that case you can install a recent version of libarchive (e.g. with ``brew install libarchive`` on MacOS) and use the ``LIBARCHIVE`` environment variable to point python-libarchive-c to it::
export LIBARCHIVE=/usr/local/Cellar/libarchive/3.3.3/lib/libarchive.13.dylib
Usage
=====
Import::
import libarchive
To extract an archive to the current directory::
libarchive.extract_file('test.zip')
``extract_memory`` extracts from a buffer instead, and ``extract_fd`` extracts
from a file descriptor.
To read an archive::
with libarchive.file_reader('test.7z') as archive:
for entry in archive:
for block in entry.get_blocks():
...
``memory_reader`` reads from a memory buffer instead, and ``fd_reader`` reads
from a file descriptor.
To create an archive::
with libarchive.file_writer('test.tar.gz', 'ustar', 'gzip') as archive:
archive.add_files('libarchive/', 'README.rst')
``memory_writer`` writes to a memory buffer instead, ``fd_writer`` writes to a
file descriptor, and ``custom_writer`` sends the data to a callback function.
You can also find more thorough examples in the ``tests/`` directory.
License
=======
`CC0 Public Domain Dedication `_
libarchive-c-2.9/libarchive/ 0000755 0002166 0000144 00000000000 13553052677 016765 5 ustar changaco users 0000000 0000000 libarchive-c-2.9/libarchive/__init__.py 0000644 0002166 0000144 00000001041 13553041177 021063 0 ustar changaco users 0000000 0000000 from .entry import ArchiveEntry
from .exception import ArchiveError
from .extract import extract_fd, extract_file, extract_memory
from .read import (
custom_reader, fd_reader, file_reader, memory_reader, stream_reader
)
from .write import custom_writer, fd_writer, file_writer, memory_writer
__all__ = [x.__name__ for x in (
ArchiveEntry,
ArchiveError,
extract_fd, extract_file, extract_memory,
custom_reader, fd_reader, file_reader, memory_reader, stream_reader,
custom_writer, fd_writer, file_writer, memory_writer
)]
libarchive-c-2.9/libarchive/entry.py 0000644 0002166 0000144 00000012127 13553041177 020474 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from contextlib import contextmanager
from ctypes import c_char_p, create_string_buffer
from . import ffi
@contextmanager
def new_archive_entry():
entry_p = ffi.entry_new()
try:
yield entry_p
finally:
ffi.entry_free(entry_p)
def format_time(seconds, nanos):
""" return float of seconds.nanos when nanos set, or seconds when not """
if nanos:
return float(seconds) + float(nanos) / 1000000000.0
return int(seconds)
class ArchiveEntry(object):
__slots__ = ('_archive_p', '_entry_p')
def __init__(self, archive_p, entry_p):
self._archive_p = archive_p
self._entry_p = entry_p
def __str__(self):
return self.pathname
@property
def filetype(self):
return ffi.entry_filetype(self._entry_p)
@property
def uid(self):
return ffi.entry_uid(self._entry_p)
@property
def gid(self):
return ffi.entry_gid(self._entry_p)
def get_blocks(self, block_size=ffi.page_size):
archive_p = self._archive_p
buf = create_string_buffer(block_size)
read = ffi.read_data
while 1:
r = read(archive_p, buf, block_size)
if r == 0:
break
yield buf.raw[0:r]
@property
def isblk(self):
return self.filetype & 0o170000 == 0o060000
@property
def ischr(self):
return self.filetype & 0o170000 == 0o020000
@property
def isdir(self):
return self.filetype & 0o170000 == 0o040000
@property
def isfifo(self):
return self.filetype & 0o170000 == 0o010000
@property
def islnk(self):
return bool(ffi.entry_hardlink_w(self._entry_p) or
ffi.entry_hardlink(self._entry_p))
@property
def issym(self):
return self.filetype & 0o170000 == 0o120000
def _linkpath(self):
return (ffi.entry_symlink_w(self._entry_p) or
ffi.entry_hardlink_w(self._entry_p) or
ffi.entry_symlink(self._entry_p) or
ffi.entry_hardlink(self._entry_p))
# aliases to get the same api as tarfile
linkpath = property(_linkpath)
linkname = property(_linkpath)
@property
def isreg(self):
return self.filetype & 0o170000 == 0o100000
@property
def isfile(self):
return self.isreg
@property
def issock(self):
return self.filetype & 0o170000 == 0o140000
@property
def isdev(self):
return self.ischr or self.isblk or self.isfifo or self.issock
@property
def atime(self):
sec_val = ffi.entry_atime(self._entry_p)
nsec_val = ffi.entry_atime_nsec(self._entry_p)
return format_time(sec_val, nsec_val)
def set_atime(self, timestamp_sec, timestamp_nsec):
return ffi.entry_set_atime(self._entry_p,
timestamp_sec, timestamp_nsec)
@property
def mtime(self):
sec_val = ffi.entry_mtime(self._entry_p)
nsec_val = ffi.entry_mtime_nsec(self._entry_p)
return format_time(sec_val, nsec_val)
def set_mtime(self, timestamp_sec, timestamp_nsec):
return ffi.entry_set_mtime(self._entry_p,
timestamp_sec, timestamp_nsec)
@property
def ctime(self):
sec_val = ffi.entry_ctime(self._entry_p)
nsec_val = ffi.entry_ctime_nsec(self._entry_p)
return format_time(sec_val, nsec_val)
def set_ctime(self, timestamp_sec, timestamp_nsec):
return ffi.entry_set_ctime(self._entry_p,
timestamp_sec, timestamp_nsec)
@property
def birthtime(self):
sec_val = ffi.entry_birthtime(self._entry_p)
nsec_val = ffi.entry_birthtime_nsec(self._entry_p)
return format_time(sec_val, nsec_val)
def set_birthtime(self, timestamp_sec, timestamp_nsec):
return ffi.entry_set_birthtime(self._entry_p,
timestamp_sec, timestamp_nsec)
def _getpathname(self):
return (ffi.entry_pathname_w(self._entry_p) or
ffi.entry_pathname(self._entry_p))
def _setpathname(self, value):
if not isinstance(value, bytes):
value = value.encode('utf8')
ffi.entry_update_pathname_utf8(self._entry_p, c_char_p(value))
pathname = property(_getpathname, _setpathname)
# aliases to get the same api as tarfile
path = property(_getpathname, _setpathname)
name = property(_getpathname, _setpathname)
@property
def size(self):
if ffi.entry_size_is_set(self._entry_p):
return ffi.entry_size(self._entry_p)
@property
def mode(self):
return ffi.entry_mode(self._entry_p)
@property
def strmode(self):
# note we strip the mode because archive_entry_strmode
# returns a trailing space: strcpy(bp, "?rwxrwxrwx ");
return ffi.entry_strmode(self._entry_p).strip()
@property
def rdevmajor(self):
return ffi.entry_rdevmajor(self._entry_p)
@property
def rdevminor(self):
return ffi.entry_rdevminor(self._entry_p)
libarchive-c-2.9/libarchive/exception.py 0000644 0002166 0000144 00000000665 13017341357 021333 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
class ArchiveError(Exception):
def __init__(self, msg, errno=None, retcode=None, archive_p=None):
self.msg = msg
self.errno = errno
self.retcode = retcode
self.archive_p = archive_p
def __str__(self):
p = '%s (errno=%s, retcode=%s, archive_p=%s)'
return p % (self.msg, self.errno, self.retcode, self.archive_p)
libarchive-c-2.9/libarchive/extract.py 0000644 0002166 0000144 00000004507 13307207473 021010 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from contextlib import contextmanager
from ctypes import byref, c_longlong, c_size_t, c_void_p
from .ffi import (
write_disk_new, write_disk_set_options, write_free, write_header,
read_data_block, write_data_block, write_finish_entry, ARCHIVE_EOF
)
from .read import fd_reader, file_reader, memory_reader
EXTRACT_OWNER = 0x0001
EXTRACT_PERM = 0x0002
EXTRACT_TIME = 0x0004
EXTRACT_NO_OVERWRITE = 0x0008
EXTRACT_UNLINK = 0x0010
EXTRACT_ACL = 0x0020
EXTRACT_FFLAGS = 0x0040
EXTRACT_XATTR = 0x0080
EXTRACT_SECURE_SYMLINKS = 0x0100
EXTRACT_SECURE_NODOTDOT = 0x0200
EXTRACT_NO_AUTODIR = 0x0400
EXTRACT_NO_OVERWRITE_NEWER = 0x0800
EXTRACT_SPARSE = 0x1000
EXTRACT_MAC_METADATA = 0x2000
EXTRACT_NO_HFS_COMPRESSION = 0x4000
EXTRACT_HFS_COMPRESSION_FORCED = 0x8000
EXTRACT_SECURE_NOABSOLUTEPATHS = 0x10000
EXTRACT_CLEAR_NOCHANGE_FFLAGS = 0x20000
@contextmanager
def new_archive_write_disk(flags):
archive_p = write_disk_new()
write_disk_set_options(archive_p, flags)
try:
yield archive_p
finally:
write_free(archive_p)
def extract_entries(entries, flags=0):
"""Extracts the given archive entries into the current directory.
"""
buff, size, offset = c_void_p(), c_size_t(), c_longlong()
buff_p, size_p, offset_p = byref(buff), byref(size), byref(offset)
with new_archive_write_disk(flags) as write_p:
for entry in entries:
write_header(write_p, entry._entry_p)
read_p = entry._archive_p
while 1:
r = read_data_block(read_p, buff_p, size_p, offset_p)
if r == ARCHIVE_EOF:
break
write_data_block(write_p, buff, size, offset)
write_finish_entry(write_p)
def extract_fd(fd, flags=0):
"""Extracts an archive from a file descriptor into the current directory.
"""
with fd_reader(fd) as archive:
extract_entries(archive, flags)
def extract_file(filepath, flags=0):
"""Extracts an archive from a file into the current directory."""
with file_reader(filepath) as archive:
extract_entries(archive, flags)
def extract_memory(buffer_, flags=0):
"""Extracts an archive from memory into the current directory."""
with memory_reader(buffer_) as archive:
extract_entries(archive, flags)
libarchive-c-2.9/libarchive/ffi.py 0000644 0002166 0000144 00000021451 13553041177 020077 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from ctypes import (
c_char_p, c_int, c_uint, c_long, c_longlong, c_size_t, c_void_p,
c_wchar_p, CFUNCTYPE, POINTER,
)
try:
from ctypes import c_ssize_t
except ImportError:
from ctypes import c_longlong as c_ssize_t
import ctypes
from ctypes.util import find_library
import logging
import mmap
import os
from .exception import ArchiveError
logger = logging.getLogger('libarchive')
page_size = mmap.PAGESIZE
libarchive_path = os.environ.get('LIBARCHIVE') or find_library('archive')
libarchive = ctypes.cdll.LoadLibrary(libarchive_path)
# Constants
ARCHIVE_EOF = 1 # Found end of archive.
ARCHIVE_OK = 0 # Operation was successful.
ARCHIVE_RETRY = -10 # Retry might succeed.
ARCHIVE_WARN = -20 # Partial success.
ARCHIVE_FAILED = -25 # Current operation cannot complete.
ARCHIVE_FATAL = -30 # No more operations are possible.
REGULAR_FILE = 0o100000
DEFAULT_UNIX_PERMISSION = 0o664
# Callback types
WRITE_CALLBACK = CFUNCTYPE(
c_ssize_t, c_void_p, c_void_p, POINTER(c_void_p), c_size_t
)
READ_CALLBACK = CFUNCTYPE(
c_ssize_t, c_void_p, c_void_p, POINTER(c_void_p)
)
OPEN_CALLBACK = CFUNCTYPE(c_int, c_void_p, c_void_p)
CLOSE_CALLBACK = CFUNCTYPE(c_int, c_void_p, c_void_p)
VOID_CB = lambda *_: ARCHIVE_OK
# Type aliases, for readability
c_archive_p = c_void_p
c_archive_entry_p = c_void_p
# Helper functions
def _error_string(archive_p):
msg = error_string(archive_p)
if msg is None:
return
try:
return msg.decode('ascii')
except UnicodeDecodeError:
return msg
def archive_error(archive_p, retcode):
msg = _error_string(archive_p)
raise ArchiveError(msg, errno(archive_p), retcode, archive_p)
def check_null(ret, func, args):
if ret is None:
raise ArchiveError(func.__name__+' returned NULL')
return ret
def check_int(retcode, func, args):
if retcode >= 0:
return retcode
elif retcode == ARCHIVE_WARN:
logger.warning(_error_string(args[0]))
return retcode
else:
raise archive_error(args[0], retcode)
def ffi(name, argtypes, restype, errcheck=None):
f = getattr(libarchive, 'archive_'+name)
f.argtypes = argtypes
f.restype = restype
if errcheck:
f.errcheck = errcheck
globals()[name] = f
return f
# FFI declarations
# archive_util
errno = ffi('errno', [c_archive_p], c_int)
error_string = ffi('error_string', [c_archive_p], c_char_p)
# archive_entry
ffi('entry_new', [], c_archive_entry_p, check_null)
ffi('entry_filetype', [c_archive_entry_p], c_int)
ffi('entry_atime', [c_archive_entry_p], c_int)
ffi('entry_birthtime', [c_archive_entry_p], c_int)
ffi('entry_mtime', [c_archive_entry_p], c_int)
ffi('entry_ctime', [c_archive_entry_p], c_int)
ffi('entry_atime_nsec', [c_archive_entry_p], c_long)
ffi('entry_birthtime_nsec', [c_archive_entry_p], c_long)
ffi('entry_mtime_nsec', [c_archive_entry_p], c_long)
ffi('entry_ctime_nsec', [c_archive_entry_p], c_long)
ffi('entry_pathname', [c_archive_entry_p], c_char_p)
ffi('entry_pathname_w', [c_archive_entry_p], c_wchar_p)
ffi('entry_sourcepath', [c_archive_entry_p], c_char_p)
ffi('entry_size', [c_archive_entry_p], c_longlong)
ffi('entry_size_is_set', [c_archive_entry_p], c_int)
ffi('entry_mode', [c_archive_entry_p], c_int)
ffi('entry_strmode', [c_archive_entry_p], c_char_p)
ffi('entry_hardlink', [c_archive_entry_p], c_char_p)
ffi('entry_hardlink_w', [c_archive_entry_p], c_wchar_p)
ffi('entry_symlink', [c_archive_entry_p], c_char_p)
ffi('entry_symlink_w', [c_archive_entry_p], c_wchar_p)
ffi('entry_rdevmajor', [c_archive_entry_p], c_uint)
ffi('entry_rdevminor', [c_archive_entry_p], c_uint)
ffi('entry_uid', [c_archive_entry_p], c_longlong)
ffi('entry_gid', [c_archive_entry_p], c_longlong)
ffi('entry_set_size', [c_archive_entry_p, c_longlong], None)
ffi('entry_set_filetype', [c_archive_entry_p, c_uint], None)
ffi('entry_set_perm', [c_archive_entry_p, c_int], None)
ffi('entry_set_atime', [c_archive_entry_p, c_int, c_long], None)
ffi('entry_set_mtime', [c_archive_entry_p, c_int, c_long], None)
ffi('entry_set_ctime', [c_archive_entry_p, c_int, c_long], None)
ffi('entry_set_birthtime', [c_archive_entry_p, c_int, c_long], None)
ffi('entry_update_pathname_utf8', [c_archive_entry_p, c_char_p], None)
ffi('entry_clear', [c_archive_entry_p], c_archive_entry_p)
ffi('entry_free', [c_archive_entry_p], None)
# archive_read
ffi('read_new', [], c_archive_p, check_null)
READ_FORMATS = set((
'7zip', 'all', 'ar', 'cab', 'cpio', 'empty', 'iso9660', 'lha', 'mtree',
'rar', 'raw', 'tar', 'xar', 'zip', 'warc'
))
for f_name in list(READ_FORMATS):
try:
ffi('read_support_format_'+f_name, [c_archive_p], c_int, check_int)
except AttributeError: # pragma: no cover
logger.info('read format "%s" is not supported' % f_name)
READ_FORMATS.remove(f_name)
READ_FILTERS = set((
'all', 'bzip2', 'compress', 'grzip', 'gzip', 'lrzip', 'lzip', 'lzma',
'lzop', 'none', 'rpm', 'uu', 'xz', 'lz4', 'zstd'
))
for f_name in list(READ_FILTERS):
try:
ffi('read_support_filter_'+f_name, [c_archive_p], c_int, check_int)
except AttributeError: # pragma: no cover
logger.info('read filter "%s" is not supported' % f_name)
READ_FILTERS.remove(f_name)
ffi('read_open',
[c_archive_p, c_void_p, OPEN_CALLBACK, READ_CALLBACK, CLOSE_CALLBACK],
c_int, check_int)
ffi('read_open_fd', [c_archive_p, c_int, c_size_t], c_int, check_int)
ffi('read_open_filename_w', [c_archive_p, c_wchar_p, c_size_t],
c_int, check_int)
ffi('read_open_memory', [c_archive_p, c_void_p, c_size_t], c_int, check_int)
ffi('read_next_header', [c_archive_p, POINTER(c_void_p)], c_int, check_int)
ffi('read_next_header2', [c_archive_p, c_void_p], c_int, check_int)
ffi('read_close', [c_archive_p], c_int, check_int)
ffi('read_free', [c_archive_p], c_int, check_int)
# archive_read_disk
ffi('read_disk_new', [], c_archive_p, check_null)
ffi('read_disk_set_behavior', [c_archive_p, c_int], c_int, check_int)
ffi('read_disk_set_standard_lookup', [c_archive_p], c_int, check_int)
ffi('read_disk_open', [c_archive_p, c_char_p], c_int, check_int)
ffi('read_disk_open_w', [c_archive_p, c_wchar_p], c_int, check_int)
ffi('read_disk_descend', [c_archive_p], c_int, check_int)
# archive_read_data
ffi('read_data_block',
[c_archive_p, POINTER(c_void_p), POINTER(c_size_t), POINTER(c_longlong)],
c_int, check_int)
ffi('read_data', [c_archive_p, c_void_p, c_size_t], c_ssize_t, check_int)
ffi('read_data_skip', [c_archive_p], c_int, check_int)
# archive_write
ffi('write_new', [], c_archive_p, check_null)
ffi('write_set_options', [c_archive_p, c_char_p], c_int, check_int)
ffi('write_disk_new', [], c_archive_p, check_null)
ffi('write_disk_set_options', [c_archive_p, c_int], c_int, check_int)
WRITE_FORMATS = set((
'7zip', 'ar_bsd', 'ar_svr4', 'cpio', 'cpio_newc', 'gnutar', 'iso9660',
'mtree', 'mtree_classic', 'pax', 'pax_restricted', 'shar', 'shar_dump',
'ustar', 'v7tar', 'xar', 'zip', 'warc'
))
for f_name in list(WRITE_FORMATS):
try:
ffi('write_set_format_'+f_name, [c_archive_p], c_int, check_int)
except AttributeError: # pragma: no cover
logger.info('write format "%s" is not supported' % f_name)
WRITE_FORMATS.remove(f_name)
WRITE_FILTERS = set((
'b64encode', 'bzip2', 'compress', 'grzip', 'gzip', 'lrzip', 'lzip', 'lzma',
'lzop', 'uuencode', 'xz', 'lz4', 'zstd'
))
for f_name in list(WRITE_FILTERS):
try:
ffi('write_add_filter_'+f_name, [c_archive_p], c_int, check_int)
except AttributeError: # pragma: no cover
logger.info('write filter "%s" is not supported' % f_name)
WRITE_FILTERS.remove(f_name)
ffi('write_open',
[c_archive_p, c_void_p, OPEN_CALLBACK, WRITE_CALLBACK, CLOSE_CALLBACK],
c_int, check_int)
ffi('write_open_fd', [c_archive_p, c_int], c_int, check_int)
ffi('write_open_filename', [c_archive_p, c_char_p], c_int, check_int)
ffi('write_open_filename_w', [c_archive_p, c_wchar_p], c_int, check_int)
ffi('write_open_memory',
[c_archive_p, c_void_p, c_size_t, POINTER(c_size_t)],
c_int, check_int)
ffi('write_get_bytes_in_last_block', [c_archive_p], c_int, check_int)
ffi('write_get_bytes_per_block', [c_archive_p], c_int, check_int)
ffi('write_set_bytes_in_last_block', [c_archive_p, c_int], c_int, check_int)
ffi('write_set_bytes_per_block', [c_archive_p, c_int], c_int, check_int)
ffi('write_header', [c_archive_p, c_void_p], c_int, check_int)
ffi('write_data', [c_archive_p, c_void_p, c_size_t], c_ssize_t, check_int)
ffi('write_data_block', [c_archive_p, c_void_p, c_size_t, c_longlong],
c_int, check_int)
ffi('write_finish_entry', [c_archive_p], c_int, check_int)
ffi('write_fail', [c_archive_p], c_int, check_int)
ffi('write_close', [c_archive_p], c_int, check_int)
ffi('write_free', [c_archive_p], c_int, check_int)
# library version
ffi('version_number', [], c_int, check_int)
libarchive-c-2.9/libarchive/flags.py 0000644 0002166 0000144 00000000323 13307223462 020416 0 ustar changaco users 0000000 0000000 READDISK_RESTORE_ATIME = 0x0001
READDISK_HONOR_NODUMP = 0x0002
READDISK_MAC_COPYFILE = 0x0004
READDISK_NO_TRAVERSE_MOUNTS = 0x0008
READDISK_NO_XATTR = 0x0010
READDISK_NO_ACL = 0x0020
READDISK_NO_FFLAGS = 0x0040
libarchive-c-2.9/libarchive/read.py 0000644 0002166 0000144 00000007776 13553032254 020260 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from contextlib import contextmanager
from ctypes import cast, c_void_p, POINTER, create_string_buffer
from os import fstat, stat
from . import ffi
from .ffi import (ARCHIVE_EOF, OPEN_CALLBACK, READ_CALLBACK, CLOSE_CALLBACK,
VOID_CB, page_size)
from .entry import ArchiveEntry, new_archive_entry
class ArchiveRead(object):
def __init__(self, archive_p):
self._pointer = archive_p
def __iter__(self):
"""Iterates through an archive's entries.
"""
archive_p = self._pointer
read_next_header2 = ffi.read_next_header2
with new_archive_entry() as entry_p:
entry = ArchiveEntry(archive_p, entry_p)
while 1:
r = read_next_header2(archive_p, entry_p)
if r == ARCHIVE_EOF:
return
yield entry
@contextmanager
def new_archive_read(format_name='all', filter_name='all'):
"""Creates an archive struct suitable for reading from an archive.
Returns a pointer if successful. Raises ArchiveError on error.
"""
archive_p = ffi.read_new()
getattr(ffi, 'read_support_filter_'+filter_name)(archive_p)
getattr(ffi, 'read_support_format_'+format_name)(archive_p)
try:
yield archive_p
finally:
ffi.read_free(archive_p)
@contextmanager
def custom_reader(
read_func, format_name='all', filter_name='all',
open_func=VOID_CB, close_func=VOID_CB, block_size=page_size,
archive_read_class=ArchiveRead
):
"""Read an archive using a custom function.
"""
open_cb = OPEN_CALLBACK(open_func)
read_cb = READ_CALLBACK(read_func)
close_cb = CLOSE_CALLBACK(close_func)
with new_archive_read(format_name, filter_name) as archive_p:
ffi.read_open(archive_p, None, open_cb, read_cb, close_cb)
yield archive_read_class(archive_p)
@contextmanager
def fd_reader(fd, format_name='all', filter_name='all', block_size=4096):
"""Read an archive from a file descriptor.
"""
with new_archive_read(format_name, filter_name) as archive_p:
try:
block_size = fstat(fd).st_blksize
except (OSError, AttributeError): # pragma: no cover
pass
ffi.read_open_fd(archive_p, fd, block_size)
yield ArchiveRead(archive_p)
@contextmanager
def file_reader(path, format_name='all', filter_name='all', block_size=4096):
"""Read an archive from a file.
"""
with new_archive_read(format_name, filter_name) as archive_p:
try:
block_size = stat(path).st_blksize
except (OSError, AttributeError): # pragma: no cover
pass
ffi.read_open_filename_w(archive_p, path, block_size)
yield ArchiveRead(archive_p)
@contextmanager
def memory_reader(buf, format_name='all', filter_name='all'):
"""Read an archive from memory.
"""
with new_archive_read(format_name, filter_name) as archive_p:
ffi.read_open_memory(archive_p, cast(buf, c_void_p), len(buf))
yield ArchiveRead(archive_p)
@contextmanager
def stream_reader(stream, format_name='all', filter_name='all',
block_size=page_size):
"""Read an archive from a stream.
The `stream` object must support the standard `readinto` method.
"""
buf = create_string_buffer(block_size)
buf_p = cast(buf, c_void_p)
def read_func(archive_p, context, ptrptr):
# readinto the buffer, returns number of bytes read
length = stream.readinto(buf)
# write the address of the buffer into the pointer
ptrptr = cast(ptrptr, POINTER(c_void_p))
ptrptr[0] = buf_p
# tell libarchive how much data was written into the buffer
return length
open_cb = OPEN_CALLBACK(VOID_CB)
read_cb = READ_CALLBACK(read_func)
close_cb = CLOSE_CALLBACK(VOID_CB)
with new_archive_read(format_name, filter_name) as archive_p:
ffi.read_open(archive_p, None, open_cb, read_cb, close_cb)
yield ArchiveRead(archive_p)
libarchive-c-2.9/libarchive/write.py 0000644 0002166 0000144 00000020032 13553052124 020451 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from contextlib import contextmanager
from ctypes import byref, cast, c_char, c_size_t, c_void_p, POINTER
from . import ffi
from .entry import ArchiveEntry, new_archive_entry
from .ffi import (
OPEN_CALLBACK, WRITE_CALLBACK, CLOSE_CALLBACK, VOID_CB, REGULAR_FILE,
DEFAULT_UNIX_PERMISSION, ARCHIVE_EOF,
page_size, entry_sourcepath, entry_clear, read_disk_new, read_disk_open_w,
read_next_header2, read_disk_descend, read_free, write_header, write_data,
write_finish_entry, entry_set_size, entry_set_filetype, entry_set_perm,
read_disk_set_behavior
)
@contextmanager
def new_archive_read_disk(path, flags=0, lookup=False):
archive_p = read_disk_new()
read_disk_set_behavior(archive_p, flags)
if lookup:
ffi.read_disk_set_standard_lookup(archive_p)
read_disk_open_w(archive_p, path)
try:
yield archive_p
finally:
read_free(archive_p)
class ArchiveWrite(object):
def __init__(self, archive_p):
self._pointer = archive_p
def add_entries(self, entries):
"""Add the given entries to the archive.
"""
write_p = self._pointer
for entry in entries:
write_header(write_p, entry._entry_p)
for block in entry.get_blocks():
write_data(write_p, block, len(block))
write_finish_entry(write_p)
def add_files(self, *paths, **kw):
"""Read the given paths from disk and add them to the archive.
The keyword arguments (`**kw`) are passed to `new_archive_read_disk`.
"""
write_p = self._pointer
block_size = ffi.write_get_bytes_per_block(write_p)
if block_size <= 0:
block_size = 10240 # pragma: no cover
with new_archive_entry() as entry_p:
entry = ArchiveEntry(None, entry_p)
for path in paths:
with new_archive_read_disk(path, **kw) as read_p:
while 1:
r = read_next_header2(read_p, entry_p)
if r == ARCHIVE_EOF:
break
entry.pathname = entry.pathname.lstrip('/')
read_disk_descend(read_p)
write_header(write_p, entry_p)
if entry.isreg:
with open(entry_sourcepath(entry_p), 'rb') as f:
while 1:
data = f.read(block_size)
if not data:
break
write_data(write_p, data, len(data))
write_finish_entry(write_p)
entry_clear(entry_p)
def add_file_from_memory(
self, entry_path, entry_size, entry_data,
filetype=REGULAR_FILE, permission=DEFAULT_UNIX_PERMISSION,
atime=None, mtime=None, ctime=None, birthtime=None,
):
""""Add file from memory to archive.
:param entry_path: where entry should be places in archive
:type entry_path: str
:param entry_size: entire size of entry in bytes
:type entry_size: int
:param entry_data: content of entry
:type entry_data: bytes or Iterable[bytes]
:param filetype: which type of file: normal, symlink etc.
should entry be created as
:type filetype: octal number
:param permission: with which permission should entry be created
:type permission: octal number
:param atime: Last access time
:type atime: int seconds or tuple (int seconds, int nanoseconds)
:param mtime: Last modified time
:type mtime: int seconds or tuple (int seconds, int nanoseconds)
:param ctime: Creation time
:type ctime: int seconds or tuple (int seconds, int nanoseconds)
:param birthtime: Birth time (for archive formats that support it)
:type birthtime: int seconds or tuple (int seconds, int nanoseconds)
"""
archive_pointer = self._pointer
if isinstance(entry_data, bytes):
entry_data = (entry_data,)
elif isinstance(entry_data, str):
raise TypeError(
"entry_data: expected bytes, got %r" % type(entry_data)
)
with new_archive_entry() as archive_entry_pointer:
archive_entry = ArchiveEntry(None, archive_entry_pointer)
archive_entry.pathname = entry_path
entry_set_size(archive_entry_pointer, entry_size)
entry_set_filetype(archive_entry_pointer, filetype)
entry_set_perm(archive_entry_pointer, permission)
if atime is not None:
if not isinstance(atime, tuple):
atime = (atime, 0)
archive_entry.set_atime(*atime)
if mtime is not None:
if not isinstance(mtime, tuple):
mtime = (mtime, 0)
archive_entry.set_mtime(*mtime)
if ctime is not None:
if not isinstance(ctime, tuple):
ctime = (ctime, 0)
archive_entry.set_ctime(*ctime)
if birthtime is not None:
if not isinstance(birthtime, tuple):
birthtime = (birthtime, 0)
archive_entry.set_birthtime(*birthtime)
write_header(archive_pointer, archive_entry_pointer)
for chunk in entry_data:
if not chunk:
break
write_data(archive_pointer, chunk, len(chunk))
write_finish_entry(archive_pointer)
entry_clear(archive_entry_pointer)
@contextmanager
def new_archive_write(format_name, filter_name=None, options=''):
archive_p = ffi.write_new()
getattr(ffi, 'write_set_format_'+format_name)(archive_p)
if filter_name:
getattr(ffi, 'write_add_filter_'+filter_name)(archive_p)
if options:
if not isinstance(options, bytes):
options = options.encode('utf-8')
ffi.write_set_options(archive_p, options)
try:
yield archive_p
ffi.write_close(archive_p)
ffi.write_free(archive_p)
except Exception:
ffi.write_fail(archive_p)
ffi.write_free(archive_p)
raise
@contextmanager
def custom_writer(
write_func, format_name, filter_name=None,
open_func=VOID_CB, close_func=VOID_CB, block_size=page_size,
archive_write_class=ArchiveWrite, options=''
):
def write_cb_internal(archive_p, context, buffer_, length):
data = cast(buffer_, POINTER(c_char * length))[0]
return write_func(data)
open_cb = OPEN_CALLBACK(open_func)
write_cb = WRITE_CALLBACK(write_cb_internal)
close_cb = CLOSE_CALLBACK(close_func)
with new_archive_write(format_name, filter_name, options) as archive_p:
ffi.write_set_bytes_in_last_block(archive_p, 1)
ffi.write_set_bytes_per_block(archive_p, block_size)
ffi.write_open(archive_p, None, open_cb, write_cb, close_cb)
yield archive_write_class(archive_p)
@contextmanager
def fd_writer(
fd, format_name, filter_name=None,
archive_write_class=ArchiveWrite, options=''
):
with new_archive_write(format_name, filter_name, options) as archive_p:
ffi.write_open_fd(archive_p, fd)
yield archive_write_class(archive_p)
@contextmanager
def file_writer(
filepath, format_name, filter_name=None,
archive_write_class=ArchiveWrite, options=''
):
with new_archive_write(format_name, filter_name, options) as archive_p:
ffi.write_open_filename_w(archive_p, filepath)
yield archive_write_class(archive_p)
@contextmanager
def memory_writer(
buf, format_name, filter_name=None,
archive_write_class=ArchiveWrite, options=''
):
with new_archive_write(format_name, filter_name, options) as archive_p:
used = byref(c_size_t())
buf_p = cast(buf, c_void_p)
ffi.write_open_memory(archive_p, buf_p, len(buf), used)
yield archive_write_class(archive_p)
libarchive-c-2.9/libarchive_c.egg-info/ 0000755 0002166 0000144 00000000000 13553052677 020761 5 ustar changaco users 0000000 0000000 libarchive-c-2.9/libarchive_c.egg-info/PKG-INFO 0000644 0002166 0000144 00000005532 13553052677 022063 0 ustar changaco users 0000000 0000000 Metadata-Version: 2.1
Name: libarchive-c
Version: 2.9
Summary: Python interface to libarchive
Home-page: https://github.com/Changaco/python-libarchive-c
Author: Changaco
Author-email: changaco@changaco.oy.lc
License: CC0
Description: .. image:: https://travis-ci.org/Changaco/python-libarchive-c.svg
:target: https://travis-ci.org/Changaco/python-libarchive-c
A Python interface to libarchive. It uses the standard ctypes_ module to
dynamically load and access the C library.
.. _ctypes: https://docs.python.org/3/library/ctypes.html
Installation
============
pip install libarchive-c
Compatibility
=============
python
------
python-libarchive-c is currently tested with python 2.7, 3.4, 3.5, and 3.6.
If you find an incompatibility with older versions you can send us a small patch,
but we won't accept big changes.
libarchive
----------
python-libarchive-c may not work properly with obsolete versions of libarchive such as the ones included in MacOS. In that case you can install a recent version of libarchive (e.g. with ``brew install libarchive`` on MacOS) and use the ``LIBARCHIVE`` environment variable to point python-libarchive-c to it::
export LIBARCHIVE=/usr/local/Cellar/libarchive/3.3.3/lib/libarchive.13.dylib
Usage
=====
Import::
import libarchive
To extract an archive to the current directory::
libarchive.extract_file('test.zip')
``extract_memory`` extracts from a buffer instead, and ``extract_fd`` extracts
from a file descriptor.
To read an archive::
with libarchive.file_reader('test.7z') as archive:
for entry in archive:
for block in entry.get_blocks():
...
``memory_reader`` reads from a memory buffer instead, and ``fd_reader`` reads
from a file descriptor.
To create an archive::
with libarchive.file_writer('test.tar.gz', 'ustar', 'gzip') as archive:
archive.add_files('libarchive/', 'README.rst')
``memory_writer`` writes to a memory buffer instead, ``fd_writer`` writes to a
file descriptor, and ``custom_writer`` sends the data to a callback function.
You can also find more thorough examples in the ``tests/`` directory.
License
=======
`CC0 Public Domain Dedication `_
Keywords: archive libarchive 7z tar bz2 zip gz
Platform: UNKNOWN
Description-Content-Type: text/x-rst
libarchive-c-2.9/libarchive_c.egg-info/SOURCES.txt 0000644 0002166 0000144 00000001761 13553052677 022652 0 ustar changaco users 0000000 0000000 .gitattributes
.gitignore
.travis.yml
LICENSE.md
MANIFEST.in
Makefile
README.rst
setup.cfg
setup.py
tox.ini
version.py
libarchive/__init__.py
libarchive/entry.py
libarchive/exception.py
libarchive/extract.py
libarchive/ffi.py
libarchive/flags.py
libarchive/read.py
libarchive/write.py
libarchive_c.egg-info/PKG-INFO
libarchive_c.egg-info/SOURCES.txt
libarchive_c.egg-info/dependency_links.txt
libarchive_c.egg-info/top_level.txt
tests/__init__.py
tests/surrogateescape.py
tests/test_atime_mtime_ctime.py
tests/test_convert.py
tests/test_entry.py
tests/test_errors.py
tests/test_rwx.py
tests/test_security_flags.py
tests/data/flags.tar
tests/data/special.tar
tests/data/tar_relative.tar
tests/data/testtar.README
tests/data/testtar.tar
tests/data/testtar.tar.json
tests/data/unicode.tar
tests/data/unicode.tar.json
tests/data/unicode.zip
tests/data/unicode.zip.json
tests/data/unicode2.zip
tests/data/unicode2.zip.json
tests/data/프로그램.README
tests/data/프로그램.zip
tests/data/프로그램.zip.json libarchive-c-2.9/libarchive_c.egg-info/dependency_links.txt 0000644 0002166 0000144 00000000001 13553052677 025027 0 ustar changaco users 0000000 0000000
libarchive-c-2.9/libarchive_c.egg-info/top_level.txt 0000644 0002166 0000144 00000000013 13553052677 023505 0 ustar changaco users 0000000 0000000 libarchive
libarchive-c-2.9/setup.cfg 0000644 0002166 0000144 00000000210 13553052677 016467 0 ustar changaco users 0000000 0000000 [wheel]
universal = 1
[flake8]
exclude = .?*,env*/
ignore = E226,E731,W504
max-line-length = 80
[egg_info]
tag_build =
tag_date = 0
libarchive-c-2.9/setup.py 0000644 0002166 0000144 00000001151 13553052545 016357 0 ustar changaco users 0000000 0000000 import os
from os.path import join, dirname
from setuptools import setup, find_packages
from version import get_version
os.umask(0o022)
setup(
name='libarchive-c',
version=get_version(),
description='Python interface to libarchive',
author='Changaco',
author_email='changaco@changaco.oy.lc',
url='https://github.com/Changaco/python-libarchive-c',
license='CC0',
packages=find_packages(exclude=['tests']),
long_description=open(join(dirname(__file__), 'README.rst')).read(),
long_description_content_type='text/x-rst',
keywords='archive libarchive 7z tar bz2 zip gz',
)
libarchive-c-2.9/tests/ 0000755 0002166 0000144 00000000000 13553052677 016017 5 ustar changaco users 0000000 0000000 libarchive-c-2.9/tests/__init__.py 0000644 0002166 0000144 00000010506 13553041177 020123 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from contextlib import closing, contextmanager
from copy import copy
from os import chdir, getcwd, stat, walk
from os.path import abspath, dirname, join
from stat import S_ISREG
import tarfile
try:
from stat import filemode
except ImportError: # Python 2
filemode = tarfile.filemode
from libarchive import file_reader
from . import surrogateescape
data_dir = join(dirname(__file__), 'data')
surrogateescape.register()
def check_archive(archive, tree):
tree2 = copy(tree)
for e in archive:
epath = str(e).rstrip('/')
assert epath in tree2
estat = tree2.pop(epath)
assert e.mtime == int(estat['mtime'])
if not e.isdir:
size = e.size
if size is not None:
assert size == estat['size']
with open(epath, 'rb') as f:
for block in e.get_blocks():
assert f.read(len(block)) == block
leftover = f.read()
assert not leftover
# Check that there are no missing directories or files
assert len(tree2) == 0
def get_entries(location):
"""
Using the archive file at `location`, return an iterable of name->value
mappings for each libarchive.ArchiveEntry objects essential attributes.
Paths are base64-encoded because JSON is UTF-8 and cannot handle
arbitrary binary pathdata.
"""
with file_reader(location) as arch:
for entry in arch:
# libarchive introduces prefixes such as h prefix for
# hardlinks: tarfile does not, so we ignore the first char
mode = entry.strmode[1:].decode('ascii')
yield {
'path': surrogate_decode(entry.pathname),
'mtime': entry.mtime,
'size': entry.size,
'mode': mode,
'isreg': entry.isreg,
'isdir': entry.isdir,
'islnk': entry.islnk,
'issym': entry.issym,
'linkpath': surrogate_decode(entry.linkpath),
'isblk': entry.isblk,
'ischr': entry.ischr,
'isfifo': entry.isfifo,
'isdev': entry.isdev,
'uid': entry.uid,
'gid': entry.gid
}
def get_tarinfos(location):
"""
Using the tar archive file at `location`, return an iterable of
name->value mappings for each tarfile.TarInfo objects essential
attributes.
Paths are base64-encoded because JSON is UTF-8 and cannot handle
arbitrary binary pathdata.
"""
with closing(tarfile.open(location)) as tar:
for entry in tar:
path = surrogate_decode(entry.path or '')
if entry.isdir() and not path.endswith('/'):
path += '/'
# libarchive introduces prefixes such as h prefix for
# hardlinks: tarfile does not, so we ignore the first char
mode = filemode(entry.mode)[1:]
yield {
'path': path,
'mtime': entry.mtime,
'size': entry.size,
'mode': mode,
'isreg': entry.isreg(),
'isdir': entry.isdir(),
'islnk': entry.islnk(),
'issym': entry.issym(),
'linkpath': surrogate_decode(entry.linkpath or None),
'isblk': entry.isblk(),
'ischr': entry.ischr(),
'isfifo': entry.isfifo(),
'isdev': entry.isdev(),
'uid': entry.uid,
'gid': entry.gid
}
@contextmanager
def in_dir(dirpath):
prev = abspath(getcwd())
chdir(dirpath)
try:
yield
finally:
chdir(prev)
def stat_dict(path):
keys = set(('uid', 'gid', 'mtime'))
mode, _, _, _, uid, gid, size, _, mtime, _ = stat(path)
if S_ISREG(mode):
keys.add('size')
return {k: v for k, v in locals().items() if k in keys}
def treestat(d, stat_dict=stat_dict):
r = {}
for dirpath, dirnames, filenames in walk(d):
r[dirpath] = stat_dict(dirpath)
for fname in filenames:
fpath = join(dirpath, fname)
r[fpath] = stat_dict(fpath)
return r
def surrogate_decode(o):
if isinstance(o, bytes):
return o.decode('utf8', errors='surrogateescape')
return o
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Title: Index of Python Enhancement Proposals (PEPs)
Version: Revision: 1.212
Last-Modified: Date: 2002/09/03 15:58:42
Author: Barry A. Warsaw
Status: Active
Type: Informational
Created: 13-Jul-2000
Post-History:
Introduction
The PEP contains the index of all Python Enhancement Proposals,
known as PEPs. PEP numbers are assigned by the PEP Editor, and
once assigned are never changed. The CVS history[1] of the PEP
texts represent their historical record.
The BDFL maintains his own Pronouncements page[2] at
http://www.python.org/doc/essays/pepparade.html which contains his
musings on the various outstanding PEPs.
Index by Category
num title owner
--- ----- -----
Meta-PEPs (PEPs about PEPs or Process)
I 0 Index of Python Enhancement Proposals Warsaw
I 1 PEP Guidelines Warsaw, Hylton
I 2 Procedure for Adding New Modules Faassen
I 3 Guidelines for Handling Bug Reports Hylton
I 4 Deprecation of Standard Modules von Loewis
I 5 Guidelines for Language Evolution Prescod
I 6 Bug Fix Releases Aahz
I 7 Style Guide for C Code van Rossum
I 8 Style Guide for Python Code van Rossum, Warsaw
I 9 Sample Plaintext PEP Template Warsaw
I 10 Voting Guidelines Warsaw
I 11 Removing support for little used platforms von Loewis
I 12 Sample reStructuredText PEP Template Goodger, Warsaw
Other Informational PEPs
I 101 Doing Python Releases 101 Warsaw, van Rossum
I 102 Doing Python Micro Releases Baxter, Warsaw, van Rossum
IF 247 API for Cryptographic Hash Functions Kuchling
IF 248 Python Database API Specification v1.0 Lemburg
IF 249 Python Database API Specification v2.0 Lemburg
I 257 Docstring Conventions Goodger, van Rossum
IF 272 API for Block Encryption Algorithms v1.0 Kuchling
I 290 Code Migration and Modernization Hettinger
Accepted PEPs (accepted; may not be implemented yet)
S 252 Making Types Look More Like Classes van Rossum
S 253 Subtyping Built-in Types van Rossum
Open PEPs (under consideration)
I 42 Small Feature Requests Hylton
I 206 2.0 Batteries Included Zadka
S 209 Adding Multidimensional Arrays Barrett, Oliphant
S 215 String Interpolation Yee
S 218 Adding a Built-In Set Object Type Wilson
S 228 Reworking Python's Numeric Model Zadka, van Rossum
S 237 Unifying Long Integers and Integers Zadka, van Rossum
S 239 Adding a Rational Type to Python Zadka
S 240 Adding a Rational Literal to Python Zadka
S 242 Numeric Kinds Dubois
S 243 Module Repository Upload Mechanism Reifschneider
S 245 Python Interface Syntax Pelletier
S 246 Object Adaptation Evans
S 254 Making Classes Look More Like Types van Rossum
S 256 Docstring Processing System Framework Goodger
S 258 Docutils Design Specification Goodger
S 262 Database of Installed Python Packages Kuchling
S 265 Sorting Dictionaries by Value Griffin
S 266 Optimizing Global Variable/Attribute Access Montanaro
S 267 Optimized Access to Module Namespaces Hylton
S 268 Extended HTTP functionality and WebDAV Stein
S 269 Pgen Module for Python Riehl
S 270 uniq method for list objects Petrone
S 273 Import Modules from Zip Archives Ahlstrom
S 274 Dict Comprehensions Warsaw
S 275 Switching on Multiple Values Lemburg
S 276 Simple Iterator for ints Althoff
S 277 Unicode file name support for Windows NT Hodgson
S 278 Universal Newline Support Jansen
S 280 Optimizing access to globals van Rossum
S 281 Loop Counter Iteration with range and xrange Hetland
S 282 A Logging System Sajip, Mick
I 283 Python 2.3 Release Schedule van Rossum
S 284 Integer for-loops Eppstein, Ewing
S 286 Enhanced Argument Tuples von Loewis
I 287 reStructuredText Docstring Format Goodger
I 291 Backward Compatibility for Standard Library Norwitz
S 292 Simpler String Substitutions Warsaw
S 294 Type Names in the types Module Tirosh
S 296 Adding a bytes Object Type Gilbert
S 297 Support for System Upgrades Lemburg
S 298 The Locked Buffer Interface Heller
S 299 Special __main__() function in modules Epler
Finished PEPs (done, implemented in CVS)
SF 100 Python Unicode Integration Lemburg
IF 160 Python 1.6 Release Schedule Drake
IF 200 Python 2.0 Release Schedule Hylton
SF 201 Lockstep Iteration Warsaw
SF 202 List Comprehensions Warsaw
SF 203 Augmented Assignments Wouters
S 205 Weak References Drake
SF 207 Rich Comparisons van Rossum, Ascher
SF 208 Reworking the Coercion Model Schemenauer, Lemburg
SF 214 Extended Print Statement Warsaw
SF 217 Display Hook for Interactive Use Zadka
SF 221 Import As Wouters
SF 223 Change the Meaning of \x Escapes Peters
I 226 Python 2.1 Release Schedule Hylton
S 227 Statically Nested Scopes Hylton
SF 229 Using Distutils to Build Python Kuchling
SF 230 Warning Framework van Rossum
SF 232 Function Attributes Warsaw
SF 234 Iterators Yee, van Rossum
SF 235 Import on Case-Insensitive Platforms Peters
SF 236 Back to the __future__ Peters
SF 238 Changing the Division Operator Zadka, van Rossum
SF 241 Metadata for Python Software Packages Kuchling
SF 250 Using site-packages on Windows Moore
IF 251 Python 2.2 Release Schedule Warsaw, van Rossum
SF 255 Simple Generators Schemenauer, et al
SF 260 Simplify xrange() van Rossum
S 261 Support for "wide" Unicode characters Prescod
SF 263 Defining Python Source Code Encodings Lemburg
SF 264 Future statements in simulated shells Hudson
SF 279 The enumerate() built-in function Hettinger
SF 285 Adding a bool type van Rossum
SF 293 Codec Error Handling Callbacks Drwald
Empty PEPs (or containing only an abstract)
SD 210 Decoupling the Interpreter Loop Ascher
ID 220 Coroutines, Generators, Continuations McMillan
Deferred, Abandoned, Withdrawn, and Rejected PEPs
SR 204 Range Literals Wouters
SD 211 Adding A New Outer Product Operator Wilson
SD 212 Loop Counter Iteration Schneider-Kamp
SD 213 Attribute Access Handlers Prescod
IR 216 Docstring Format Zadka
SD 219 Stackless Python McMillan
SD 222 Web Library Enhancements Kuchling
SR 224 Attribute Docstrings Lemburg
SD 225 Elementwise/Objectwise Operators Zhu, Lielens
SR 231 __findattr__() Warsaw
SD 233 Python Online Help Prescod
SR 244 The `directive' Statement von Loewis
SR 259 Omit printing newline after newline van Rossum
SR 271 Prefixing sys.path by command line option Giacometti
SD 288 Generators Attributes and Exceptions Hettinger
SR 289 Generator Comprehensions Hettinger
SR 295 Interpretation of multiline string constants Koltsov
SR 666 Reject Foolish Indentation Creighton
Numerical Index
num title owner
--- ----- -----
I 0 Index of Python Enhancement Proposals Warsaw
I 1 PEP Guidelines Warsaw, Hylton
I 2 Procedure for Adding New Modules Faassen
I 3 Guidelines for Handling Bug Reports Hylton
I 4 Deprecation of Standard Modules von Loewis
I 5 Guidelines for Language Evolution Prescod
I 6 Bug Fix Releases Aahz
I 7 Style Guide for C Code van Rossum
I 8 Style Guide for Python Code van Rossum, Warsaw
I 9 Sample Plaintext PEP Template Warsaw
I 10 Voting Guidelines Warsaw
I 11 Removing support for little used platforms von Loewis
I 12 Sample reStructuredText PEP Template Goodger, Warsaw
I 42 Small Feature Requests Hylton
SF 100 Python Unicode Integration Lemburg
I 101 Doing Python Releases 101 Warsaw, van Rossum
I 102 Doing Python Micro Releases Baxter, Warsaw, van Rossum
IF 160 Python 1.6 Release Schedule Drake
IF 200 Python 2.0 Release Schedule Hylton
SF 201 Lockstep Iteration Warsaw
SF 202 List Comprehensions Warsaw
SF 203 Augmented Assignments Wouters
SR 204 Range Literals Wouters
S 205 Weak References Drake
I 206 2.0 Batteries Included Zadka
SF 207 Rich Comparisons van Rossum, Ascher
SF 208 Reworking the Coercion Model Schemenauer, Lemburg
S 209 Adding Multidimensional Arrays Barrett, Oliphant
SD 210 Decoupling the Interpreter Loop Ascher
SD 211 Adding A New Outer Product Operator Wilson
SD 212 Loop Counter Iteration Schneider-Kamp
SD 213 Attribute Access Handlers Prescod
SF 214 Extended Print Statement Warsaw
SD 215 String Interpolation Yee
IR 216 Docstring Format Zadka
SF 217 Display Hook for Interactive Use Zadka
S 218 Adding a Built-In Set Object Type Wilson
SD 219 Stackless Python McMillan
ID 220 Coroutines, Generators, Continuations McMillan
SF 221 Import As Wouters
SD 222 Web Library Enhancements Kuchling
SF 223 Change the Meaning of \x Escapes Peters
SR 224 Attribute Docstrings Lemburg
SD 225 Elementwise/Objectwise Operators Zhu, Lielens
I 226 Python 2.1 Release Schedule Hylton
S 227 Statically Nested Scopes Hylton
S 228 Reworking Python's Numeric Model Zadka, van Rossum
SF 229 Using Distutils to Build Python Kuchling
SF 230 Warning Framework van Rossum
SR 231 __findattr__() Warsaw
SF 232 Function Attributes Warsaw
SD 233 Python Online Help Prescod
SF 234 Iterators Yee, van Rossum
SF 235 Import on Case-Insensitive Platforms Peters
SF 236 Back to the __future__ Peters
S 237 Unifying Long Integers and Integers Zadka, van Rossum
SF 238 Changing the Division Operator Zadka, van Rossum
S 239 Adding a Rational Type to Python Zadka
S 240 Adding a Rational Literal to Python Zadka
SF 241 Metadata for Python Software Packages Kuchling
S 242 Numeric Kinds Dubois
S 243 Module Repository Upload Mechanism Reifschneider
SR 244 The `directive' Statement von Loewis
S 245 Python Interface Syntax Pelletier
S 246 Object Adaptation Evans
IF 247 API for Cryptographic Hash Functions Kuchling
IF 248 Python Database API Specification v1.0 Lemburg
IF 249 Python Database API Specification v2.0 Lemburg
SF 250 Using site-packages on Windows Moore
IF 251 Python 2.2 Release Schedule Warsaw, van Rossum
S 252 Making Types Look More Like Classes van Rossum
S 253 Subtyping Built-in Types van Rossum
S 254 Making Classes Look More Like Types van Rossum
SF 255 Simple Generators Schemenauer, et al
S 256 Docstring Processing System Framework Goodger
I 257 Docstring Conventions Goodger, van Rossum
S 258 Docutils Design Specification Goodger
SR 259 Omit printing newline after newline van Rossum
SF 260 Simplify xrange() van Rossum
S 261 Support for "wide" Unicode characters Prescod
S 262 Database of Installed Python Packages Kuchling
SF 263 Defining Python Source Code Encodings Lemburg
SF 264 Future statements in simulated shells Hudson
S 265 Sorting Dictionaries by Value Griffin
S 266 Optimizing Global Variable/Attribute Access Montanaro
S 267 Optimized Access to Module Namespaces Hylton
S 268 Extended HTTP functionality and WebDAV Stein
S 269 Pgen Module for Python Riehl
S 270 uniq method for list objects Petrone
SR 271 Prefixing sys.path by command line option Giacometti
IF 272 API for Block Encryption Algorithms v1.0 Kuchling
S 273 Import Modules from Zip Archives Ahlstrom
S 274 Dict Comprehensions Warsaw
S 275 Switching on Multiple Values Lemburg
S 276 Simple Iterator for ints Althoff
S 277 Unicode file name support for Windows NT Hodgson
S 278 Universal Newline Support Jansen
SF 279 The enumerate() built-in function Hettinger
S 280 Optimizing access to globals van Rossum
S 281 Loop Counter Iteration with range and xrange Hetland
S 282 A Logging System Sajip, Mick
I 283 Python 2.3 Release Schedule van Rossum
S 284 Integer for-loops Eppstein, Ewing
SF 285 Adding a bool type van Rossum
S 286 Enhanced Argument Tuples von Loewis
I 287 reStructuredText Docstring Format Goodger
SD 288 Generators Attributes and Exceptions Hettinger
SR 289 Generator Comprehensions Hettinger
I 290 Code Migration and Modernization Hettinger
I 291 Backward Compatibility for Standard Library Norwitz
S 292 Simpler String Substitutions Warsaw
SF 293 Codec Error Handling Callbacks Drwald
S 294 Type Names in the types Module Tirosh
SR 295 Interpretation of multiline string constants Koltsov
S 296 Adding a bytes Object Type Gilbert
S 297 Support for System Upgrades Lemburg
S 298 The Locked Buffer Interface Heller
S 299 Special __main__() function in modules Epler
SR 666 Reject Foolish Indentation Creighton
Key
I - Informational PEP
S - Standards Track PEP
A - Accepted proposal
R - Rejected proposal
D - Deferred proposal
F - Final proposal
Owners
name email address
---------------- -------------
Aahz aahz@pobox.com
Ahlstrom, James C. jim@interet.com
Althoff, Jim james_althoff@i2.com
Ascher, David davida@activestate.com
Barrett, Paul barrett@stsci.edu
Baxter, Anthony anthony@interlink.com.au
Creighton, Laura lac@strakt.com
Drwald, Walter
Drake, Fred fdrake@acm.org
Dubois, Paul F. paul@pfdubois.com
Epler, Jeff jepler@unpythonic.net
Eppstein, David eppstein@ics.uci.edu
Evans, Clark C. cce@clarkevans.com
Ewing, Greg greg@cosc.canterbury.ac.nz
Faassen, Martijn faassen@infrae.com
Giacometti, Frdric B. fred@arakne.com
Gilbert, Scott xscottg at yahoo.com
Goodger, David goodger@users.sourceforge.net
Griffin, Grant g2@iowegian.com
Heller, Thomas theller@python.net
Hetland, Magnus Lie magnus@hetland.org
Hettinger, Raymond D. python@rcn.com
Hodgson, Neil neilh@scintilla.org
Hudson, Michael mwh@python.net
Hylton, Jeremy jeremy@zope.com
Jansen, Jack jack@cwi.nl
Koltsov, Stepan yozh@mx1.ru
Kuchling, Andrew akuchlin@mems-exchange.org
Lemburg, Marc-Andre mal@lemburg.com
Lielens, Gregory gregory.lielens@fft.be
von Loewis, Martin loewis@informatik.hu-berlin.de
Martelli, Alex aleax@aleax.it
McMillan, Gordon gmcm@hypernet.com
Mick, Trent trentm@activestate.com
Montanaro, Skip skip@pobox.com
Moore, Paul gustav@morpheus.demon.co.uk
Norwitz, Neal neal@metaslash.com
Oliphant, Travis oliphant@ee.byu.edu
Pelletier, Michel michel@digicool.com
Peters, Tim tim@digicool.com
Petrone, Jason jp@demonseed.net
Prescod, Paul paul@prescod.net
Reifschneider, Sean jafo-pep@tummy.com
Riehl, Jonathan jriehl@spaceship.com
van Rossum, Guido guido@python.org
Sajip, Vinay vinay_sajip@red-dove.com
Schemenauer, Neil nas@arctrix.com
Schneider-Kamp, Peter nowonder@nowonder.de
Stein, Greg gstein@lyra.org
Tirosh, Oren oren at hishome.net
Warsaw, Barry barry@zope.com
Wilson, Greg gvwilson@ddj.com
Wouters, Thomas thomas@xs4all.net
Yee, Ka-Ping ping@lfw.org
Zadka, Moshe moshez@zadka.site.co.il
Zhu, Huaiyu hzhu@users.sourceforge.net
References
[1] View PEP history online
http://cvs.sf.net/cgi-bin/viewcvs.cgi/python/python/nondist/peps/
[2] The Benevolent Dictator For Life's Parade of PEPs
http://www.python.org/doc/essays/pepparade.html
Local Variables:
mode: indented-text
indent-tabs-mode: nil
sentence-end-double-space: t
fill-column: 70
End:
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libarchive-c-2.9/tests/data/tar_relative.tar 0000644 0002166 0000144 00000024000 13017341356 022103 0 ustar changaco users 0000000 0000000 ../a_parent_folder.txt 0000666 0000000 0000000 00000000006 11242711436 015321 0 ustar 00user group 0000000 0000000 test a ../../another_folder/b_two_root.txt 0000666 0000000 0000000 00000000006 11242711442 017555 0 ustar 00user group 0000000 0000000 test b ../folder/subfolder/b_subfolder.txt 0000666 0000000 0000000 00000000006 11242711442 017720 0 ustar 00user group 0000000 0000000 test b libarchive-c-2.9/tests/data/testtar.README 0000644 0002166 0000144 00000000303 13017341356 021257 0 ustar changaco users 0000000 0000000 This test file is borrowed from Python codebase and test suite.
This is a trick Tar with several weird and malformed entries:
https://hg.python.org/cpython/file/bff88c866886/Lib/test/testtar.tar
libarchive-c-2.9/tests/data/testtar.tar 0000644 0002166 0000144 00001522000 13017341356 021114 0 ustar changaco users 0000000 0000000 ustar/conttype 0000644 0001750 0000144 00000015543 07606136617 015171 7 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
ustar/regtype 0000644 0001750 0000144 00000015543 07606136617 014774 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
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ustar/umlauts- 0000644 0001750 0000144 00000015543 07606136617 020137 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/1234567/longname0000644 0001750 0000144 00000015543 07606136617 045233 0 ustar 00tarfile tarfile 0000000 0000000 ustar/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345/12345 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
./ustar/linktest2/symtype 0000777 0001750 0000144 00000000000 07606136617 021323 2../linktest1/regtype ustar tarfile tarfile ustar/linktest1/regtype 0000644 0001750 0000144 00000015543 07606136617 015412 0 ustar tarfile tarfile Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
./ustar/linktest2/lnktype 0000644 0001750 0000144 00000000000 07606136617 022347 1./ustar/linktest1/regtype ustar tarfile tarfile symtype2 0000777 0001750 0000144 00000000000 07606136617 016500 2ustar/regtype ustar 00tarfile tarfile 0000000 0000000 ././@LongLink 0000000 0000000 0000000 00000001001 00000000000 011555 L ustar root root gnu/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/longname gnu/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/0000644 0001750 0000144 00000015543 07606136617 022717 0 ustar tarfile tarfile Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
././@LongLink 0000000 0000000 0000000 00000001001 00000000000 011554 K ustar root root gnu/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/123/longname ././@LongLink 0000000 0000000 0000000 00000001001 00000000000 011555 L ustar root root 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20 atime=1169212652
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0000644 00000015543 07606136617 021077 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
misc/regtype-old-v7 644 1750 144 15543 7606136617 007662 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
misc/regtype-hpux-signed-chksum- 0000644 0001750 0000144 00000015543 07606136617 020042 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
misc/regtype-old-v7-signed-chksum- 644 1750 144 15543 7606136617 012151 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
misc/dirtype-old-v7/ 40755 1750 144 0 7606136617 007667 misc/regtype-suntar 0100644 0000145 0000012 00000000036 10550714670 0020273 X ustar 00lars staff 0000040 0000017 /tmp/PaxHeaders.378 30 mtime=1041808783.000000000
misc/regtype-suntar 0100644 0001750 0000144 00000015543 10550714670 0016111 0 ustar 00tarfile tarfile 0000040 0000017 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
misc/regtype-xstar 0000644 0001750 0000144 00000015543 07606136617 0020313 0 ustar 00lars users 0000000 0000000 07606136617 07606136617 tar Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
././@PaxHeader 0000600 0000000 0000000 00000001144 00000000000 0013633 x ustar 00root root 0000000 0000000 30 atime=1041808783.000000000
30 ctime=1041808783.000000000
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As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
././@PaxHeader 0000600 0000000 0000000 00000002162 00000000000 0013634 x ustar 00root root 0000000 0000000 30 atime=1041808783.000000000
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pax/umlauts- 0000644 0001750 0000144 00000015543 07606136617 017571 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
/tmp/GlobalHead.26030.1 0000644 0001750 0000144 00000000073 10552150730 012753 g ustar 00 0000000 0000000 13 gname=bar
13 uname=foo
33 VENDOR.umlauts=ÄÖÜäöüß
pax/regtype1 0000644 0001750 0000144 00000015543 07606136617 014507 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
/tmp/GlobalHead.23988.1 0000644 0001750 0000144 00000000011 10552143626 012774 g ustar 00 0000000 0000000 9 uname=
pax/regtype2 0000644 0001750 0000144 00000015543 07606136617 014510 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
/tmp/GlobalHead.23988.1 0000644 0001750 0000144 00000000042 10552143626 013000 g ustar 00 0000000 0000000 17 uname=tarfile
17 gname=tarfile
pax/regtype3 0000644 0001750 0000144 00000015543 07606136617 014511 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
././@PaxHeader 0000600 0000000 0000000 00000000175 00000000000 013636 x ustar 00root root 0000000 0000000 30 atime=1041808783.000000000
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pax/regtype4 0000644 0001750 0000144 00000000000 00000000000 014755 0 ustar 00tarfile tarfile 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
pax/PaxHeaders.16970/bad-pax- 0000644 0001750 0001750 00000000162 07606136617 015564 x ustar 00 0000000 0000000 24 path=pax/bad-pax-
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pax/bad-pax- 0000644 0001750 0001750 00000015543 07606136617 014520 0 ustar 00lars lars 0000000 0000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
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pax/hdrcharset- 000644 000000 000000 00000015543 07606136617 016433 0 ustar 00tarfile tarfile 000000 000000 Foreword for "Programming Python" (1st ed.)
As Python's creator, I'd like to say a few words about its origins, adding a
bit of personal philosophy.
Over six years ago, in December 1989, I was looking for a "hobby" programming
project that would keep me occupied during the week around Christmas. My office
(a government-run research lab in Amsterdam) would be closed, but I had a home
computer, and not much else on my hands. I decided to write an interpreter for
the new scripting language I had been thinking about lately: a descendant of
ABC that would appeal to Unix/C hackers. I chose Python as a working title for
the project, being in a slightly irreverent mood (and a big fan of Monty
Python's Flying Circus).
Today, I can safely say that Python has changed my life. I have moved to a
different continent. I spend my working days developing large systems in
Python, when I'm not hacking on Python or answering Python-related email. There
are Python T-shirts, workshops, mailing lists, a newsgroup, and now a book.
Frankly, my only unfulfilled wish is to have my picture on the front page of
the New York Times. But before I get carried away daydreaming, here are a few
tidbits from Python's past.
It all started with ABC, a wonderful teaching language that I had helped create
in the early eighties. It was an incredibly elegant and powerful language,
aimed at non-professional programmers. Despite all its elegance and power and
the availability of a free implementation, ABC never became popular in the
Unix/C world. I can only speculate about the reasons, but here's a likely one:
the difficulty of adding new "primitive" operations to ABC. It was a
monolithic, "closed system", with only the most basic I/O operations: read a
string from the console, write a string to the console. I decided not repeat
this mistake in Python.
Besides this intention, I had a number of other ideas for improvement over ABC,
and was eager to try them out. For instance, ABC's powerful data types turned
out to be less efficient than we hoped. There was too much emphasis on
theoretically optimal algorithms, and not enough tuning for common cases. I
also felt that some of ABC's features, aimed at novice programmers, were less
desirable for the (then!) intended audience of experienced Unix/C programmers.
For instance: ABC's ideosyncratic syntax (all uppercase keywords!); some
terminology (e.g. "how-to" instead of "procedure"); and the integrated
structured editor, which its users almost universally hated. Python would rely
more on the Unix infrastructure and conventions, without being Unix-bound. And
in fact, the first implementation was done on a Mac.
As it turned out, Python is remarkably free from many of the hang-ups of
conventional programming languages. This is perhaps due to my choice of
examples: besides ABC, my main influence was Modula-3. This is another language
with remarkable elegance and power, designed by a small, strong-willed team
(most of whom I had met during a summer internship at DEC's Systems Research
Center in Palo Alto). Imagine what Python would have looked like if I had
modelled it after the Unix shell and C instead! (Yes, I borrowed from C too,
but only its least controversial features, in my desire to please the Unix/C
audience.)
Any individual creation has its ideosyncracies, and occasionally its creator
has to justify these. Perhaps Python's most controversial feature is its use of
indentation for statement grouping, which derives directly from ABC. It is one
of the language's features that is dearest to my heart. It makes Python code
more readable in two ways. First, the use of indentation reduces visual clutter
and makes programs shorter, thus reducing the attention span needed to take in
a basic unit of code. Second, it allows the programmer less freedom in
formatting, thereby enabling a more uniform style, which makes it easier to
read someone else's code. (Compare, for instance, the three or four different
conventions for the placement of braces in C, each with strong proponents.)
This emphasis on readability is no accident. As an object-oriented language,
Python aims to encourage the creation of reusable code. Even if we all wrote
perfect documentation all of the time, code can hardly be considered reusable
if it's not readable. Many of Python's features, in addition to its use of
indentation, conspire to make Python code highly readable. This reflects the
philosophy of ABC, which was intended to teach programming in its purest form,
and therefore placed a high value on clarity.
Readability is often enhanced by reducing unnecessary variability. When
possible, there's a single, obvious way to code a particular construct. This
reduces the number of choices facing the programmer who is writing the code,
and increases the chance that will appear familiar to a second programmer
reading it. Yet another contribution to Python's readability is the choice to
use punctuation mostly in a conservative, conventional manner. Most operator
symbols are familiar to anyone with even a vague recollection of high school
math, and no new meanings have to be learned for comic strip curse characters
like @&$!.
I will gladly admit that Python is not the fastest running scripting language.
It is a good runner-up though. With ever-increasing hardware speed, the
accumulated running time of a program during its lifetime is often negligible
compared to the programmer time needed to write and debug it. This, of course,
is where the real savings can be made. While this is hard to assess
objectively, Python is considered a winner in coding time by most who have
tried it. In addition, many consider using Python a pleasure -- a better
recommendation is hard to imagine.
I am solely responsible for Python's strengths and shortcomings, even when some
of the code has been written by others. However, its success is the product of
a community, starting with the early adopters who picked it up when I first
published Python on the net, and who spread the word about it in their own
environment. They sent me their praise, criticism, feature requests, code
contributions, and personal revelations via email. They were willing to discuss
every aspect of Python in the mailing list that I soon set up, and educate me
or nudge me in the right direction where my initial intuition failed me. There
have been too many contributors to thank individually. I'll make one exception,
however: this book's author was one of Python's early adopters and evangelists.
With its publication, his longstanding wish (and mine!) of having a more
accessible description of Python than the standard set of manuals, is
fulfilled.
But enough rambling. I highly recommend this book to anyone interested in
learning Python, whether for personal improvement or as a career enhancement.
Take it away, Eric, the orchestra leader! (If you don't understand this last
sentence, you haven't watched enough Monty Python reruns.)
Guido van Rossum
Reston, VA, May 1996
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"isfifo": false,
"islnk": false,
"isreg": false,
"issym": false,
"linkpath": null,
"mode": "rwx------",
"mtime": 1319027321,
"path": "2859/",
"size": 0,
"uid": 500
},
{
"gid": 513,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rwx------",
"mtime": 1319027194,
"path": "2859/Copy of h\u00e0nz\u00ec-somefile.txt",
"size": 0,
"uid": 500
},
{
"gid": 513,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rwx------",
"mtime": 1319027194,
"path": "2859/h\u00e0nz\u00ec?-somefile.txt ",
"size": 0,
"uid": 500
}
] libarchive-c-2.9/tests/data/unicode.zip 0000644 0002166 0000144 00000001234 13017341356 021070 0 ustar changaco users 0000000 0000000 PK
\o< a/UT ~K/=Tux PK
\o< j j a/grün.pngUT s~KKux PNG
IHDR
pHYs ~ tEXtComment * IDATxQ;
@}z.]vB,,L VXsfhvW ٝy 0?V/ת5F]hϜaD = .jYP!A a}Qh6x>bNIvv p| s ؊ZUXOP6O.`Sdj ޛLd`R2Rb`r 94Ki:lFLa- FDMuJǚ29 #"^ }? l[H IENDB`PK
\o< A a/UT ~Kux PK
\o< j j < a/grün.pngUT s~Kux PK libarchive-c-2.9/tests/data/unicode.zip.json 0000644 0002166 0000144 00000001224 13307207473 022042 0 ustar changaco users 0000000 0000000 [
{
"gid": 1000,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": true,
"isfifo": false,
"islnk": false,
"isreg": false,
"issym": false,
"linkpath": null,
"mode": "rwxr-xr-x",
"mtime": 1268678396,
"path": "a/",
"size": 0,
"uid": 1000
},
{
"gid": 1000,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rw-r--r--",
"mtime": 1268678259,
"path": "a/gr\u00fcn.png",
"size": 362,
"uid": 1000
}
] libarchive-c-2.9/tests/data/unicode2.zip 0000644 0002166 0000144 00000001174 13017341356 021155 0 ustar changaco users 0000000 0000000 PK faNC a/PK
o< j j a/grün.pngPNG
IHDR
pHYs ~ tEXtComment * IDATxQ;
@}z.]vB,,L VXsfhvW ٝy 0?V/ת5F]hϜaD = .jYP!A a}Qh6x>bNIvv p| s ؊ZUXOP6O.`Sdj ޛLd`R2Rb`r 94Ki:lFLa- FDMuJǚ29 #"^ }? l[H IENDB`PK? faNC $ a/
JJPK?
o< j j $ a/grün.png
J5f##PK libarchive-c-2.9/tests/data/unicode2.zip.json 0000644 0002166 0000144 00000001211 13307207473 022120 0 ustar changaco users 0000000 0000000 [
{
"gid": 0,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": true,
"isfifo": false,
"islnk": false,
"isreg": false,
"issym": false,
"linkpath": null,
"mode": "rwxrwxr-x",
"mtime": 1381752672,
"path": "a/",
"size": 0,
"uid": 0
},
{
"gid": 0,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rw-rw-r--",
"mtime": 1268681860,
"path": "a/gru\u0308n.png",
"size": 362,
"uid": 0
}
] libarchive-c-2.9/tests/data/프로그램.README 0000644 0002166 0000144 00000000267 13017341356 024150 0 ustar changaco users 0000000 0000000 Test file from borrowed from
https://github.com/libarchive/libarchive/issues/459
http://libarchive.github.io/google-code/issue-350/comment-0/%ED%94%84%EB%A1%9C%EA%B7%B8%EB%9E%A8.zip
libarchive-c-2.9/tests/data/프로그램.zip 0000644 0002166 0000144 00000000543 13017341356 024012 0 ustar changaco users 0000000 0000000 PK
/H7D hello.txtUT R Rux Hello, World!
PK
H7D!
프로그램.txtUT R Rux 프로그램
PK
/H7D hello.txtUT Rux PK
H7D!
Q 프로그램.txtUT Rux PK libarchive-c-2.9/tests/data/프로그램.zip.json 0000644 0002166 0000144 00000001244 13307207473 024764 0 ustar changaco users 0000000 0000000 [
{
"gid": 502,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rw-rw-r--",
"mtime": 1390485689,
"path": "hello.txt",
"size": 14,
"uid": 502
},
{
"gid": 502,
"isblk": false,
"ischr": false,
"isdev": false,
"isdir": false,
"isfifo": false,
"islnk": false,
"isreg": true,
"issym": false,
"linkpath": null,
"mode": "rw-rw-r--",
"mtime": 1390485651,
"path": "\ud504\ub85c\uadf8\ub7a8.txt",
"size": 13,
"uid": 502
}
] libarchive-c-2.9/tests/surrogateescape.py 0000644 0002166 0000144 00000002663 13017341356 021562 0 ustar changaco users 0000000 0000000 """
This is a modified version of Victor Stinner's pure-Python implementation of
PEP 383: the "surrogateescape" error handler of Python 3.
This code is released under the Python license and the BSD 2-clause license
Source: misc/python/surrogateescape.py in https://bitbucket.org/haypo/misc
"""
from __future__ import division, print_function, unicode_literals
import codecs
chr = __builtins__.get('unichr', chr)
def surrogateescape(exc):
if isinstance(exc, UnicodeDecodeError):
decoded = []
for code in exc.object[exc.start:exc.end]:
if not isinstance(code, int):
code = ord(code)
if 0x80 <= code <= 0xFF:
decoded.append(chr(0xDC00 + code))
elif code <= 0x7F:
decoded.append(chr(code))
else:
raise exc
return (''.join(decoded), exc.end)
elif isinstance(exc, UnicodeEncodeError):
encoded = []
for ch in exc.object[exc.start:exc.end]:
code = ord(ch)
if not 0xDC80 <= code <= 0xDCFF:
raise exc
encoded.append(chr(code - 0xDC00))
return (''.join(encoded), exc.end)
else:
raise exc
def register():
"""Register the surrogateescape error handler if it doesn't exist
"""
try:
codecs.lookup_error('surrogateescape')
except LookupError:
codecs.register_error('surrogateescape', surrogateescape)
libarchive-c-2.9/tests/test_atime_mtime_ctime.py 0000644 0002166 0000144 00000011254 13307220433 023066 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from copy import copy
from os import stat
from libarchive import (file_reader, file_writer, memory_reader, memory_writer)
import pytest
from . import treestat
# NOTE: zip does not support high resolution time data, but pax and others do
def check_atime_ctime(archive, tree, timefmt=int):
tree2 = copy(tree)
for entry in archive:
epath = str(entry).rstrip('/')
assert epath in tree2
estat = tree2.pop(epath)
assert entry.atime == timefmt(estat.st_atime)
assert entry.ctime == timefmt(estat.st_ctime)
def stat_dict(path):
# return the raw stat output, the tuple output only returns ints
return stat(path)
def time_check(time_tuple, timefmt):
seconds, nanos = time_tuple
maths = float(seconds) + float(nanos) / 1000000000.0
return timefmt(maths)
@pytest.mark.parametrize('archfmt,timefmt', [('zip', int), ('pax', float)])
def test_memory_atime_ctime(archfmt, timefmt):
# Collect information on what should be in the archive
tree = treestat('libarchive', stat_dict)
# Create an archive of our libarchive/ directory
buf = bytes(bytearray(1000000))
with memory_writer(buf, archfmt) as archive1:
archive1.add_files('libarchive/')
# Check the data
with memory_reader(buf) as archive2:
check_atime_ctime(archive2, tree, timefmt=timefmt)
@pytest.mark.parametrize('archfmt,timefmt', [('zip', int), ('pax', float)])
def test_file_atime_ctime(archfmt, timefmt, tmpdir):
archive_path = "{0}/test.{1}".format(tmpdir.strpath, archfmt)
# Collect information on what should be in the archive
tree = treestat('libarchive', stat_dict)
# Create an archive of our libarchive/ directory
with file_writer(archive_path, archfmt) as archive:
archive.add_files('libarchive/')
# Read the archive and check that the data is correct
with file_reader(archive_path) as archive:
check_atime_ctime(archive, tree, timefmt=timefmt)
@pytest.mark.parametrize('archfmt,timefmt', [('zip', int), ('pax', float)])
def test_memory_time_setters(archfmt, timefmt):
has_birthtime = archfmt != 'zip'
# Create an archive of our libarchive/ directory
buf = bytes(bytearray(1000000))
with memory_writer(buf, archfmt) as archive1:
archive1.add_files('libarchive/')
atimestamp = (1482144741, 495628118)
mtimestamp = (1482155417, 659017086)
ctimestamp = (1482145211, 536858081)
btimestamp = (1482144740, 495628118)
buf2 = bytes(bytearray(1000000))
with memory_reader(buf) as archive1:
with memory_writer(buf2, archfmt) as archive2:
for entry in archive1:
entry.set_atime(*atimestamp)
entry.set_mtime(*mtimestamp)
entry.set_ctime(*ctimestamp)
if has_birthtime:
entry.set_birthtime(*btimestamp)
archive2.add_entries([entry])
with memory_reader(buf2) as archive2:
for entry in archive2:
assert entry.atime == time_check(atimestamp, timefmt)
assert entry.mtime == time_check(mtimestamp, timefmt)
assert entry.ctime == time_check(ctimestamp, timefmt)
if has_birthtime:
assert entry.birthtime == time_check(btimestamp, timefmt)
@pytest.mark.parametrize('archfmt,timefmt', [('zip', int), ('pax', float)])
def test_file_time_setters(archfmt, timefmt, tmpdir):
has_birthtime = archfmt != 'zip'
# Create an archive of our libarchive/ directory
archive_path = tmpdir.join('/test.{0}'.format(archfmt)).strpath
archive2_path = tmpdir.join('/test2.{0}'.format(archfmt)).strpath
with file_writer(archive_path, archfmt) as archive1:
archive1.add_files('libarchive/')
atimestamp = (1482144741, 495628118)
mtimestamp = (1482155417, 659017086)
ctimestamp = (1482145211, 536858081)
btimestamp = (1482144740, 495628118)
with file_reader(archive_path) as archive1:
with file_writer(archive2_path, archfmt) as archive2:
for entry in archive1:
entry.set_atime(*atimestamp)
entry.set_mtime(*mtimestamp)
entry.set_ctime(*ctimestamp)
if has_birthtime:
entry.set_birthtime(*btimestamp)
archive2.add_entries([entry])
with file_reader(archive2_path) as archive2:
for entry in archive2:
assert entry.atime == time_check(atimestamp, timefmt)
assert entry.mtime == time_check(mtimestamp, timefmt)
assert entry.ctime == time_check(ctimestamp, timefmt)
if has_birthtime:
assert entry.birthtime == time_check(btimestamp, timefmt)
libarchive-c-2.9/tests/test_convert.py 0000644 0002166 0000144 00000001420 13024550543 021071 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from libarchive import memory_reader, memory_writer
from . import check_archive, treestat
def test_convert():
# Collect information on what should be in the archive
tree = treestat('libarchive')
# Create an archive of our libarchive/ directory
buf = bytes(bytearray(1000000))
with memory_writer(buf, 'gnutar', 'xz') as archive1:
archive1.add_files('libarchive/')
# Convert the archive to another format
buf2 = bytes(bytearray(1000000))
with memory_reader(buf) as archive1:
with memory_writer(buf2, 'zip') as archive2:
archive2.add_entries(archive1)
# Check the data
with memory_reader(buf2) as archive2:
check_archive(archive2, tree)
libarchive-c-2.9/tests/test_entry.py 0000644 0002166 0000144 00000006264 13553041177 020572 0 ustar changaco users 0000000 0000000 # -*- coding: utf-8 -*-
from __future__ import division, print_function, unicode_literals
from codecs import open
import json
import locale
from os import environ, stat
from os.path import join
import unicodedata
from libarchive import memory_reader, memory_writer
from . import data_dir, get_entries, get_tarinfos
text_type = unicode if str is bytes else str # noqa: F821
locale.setlocale(locale.LC_ALL, '')
# needed for sane time stamp comparison
environ['TZ'] = 'UTC'
def test_entry_properties():
buf = bytes(bytearray(1000000))
with memory_writer(buf, 'gnutar') as archive:
archive.add_files('README.rst')
readme_stat = stat('README.rst')
with memory_reader(buf) as archive:
for entry in archive:
assert entry.uid == readme_stat.st_uid
assert entry.gid == readme_stat.st_gid
assert entry.mode == readme_stat.st_mode
assert not entry.isblk
assert not entry.ischr
assert not entry.isdir
assert not entry.isfifo
assert not entry.islnk
assert not entry.issym
assert not entry.linkpath
assert entry.linkpath == entry.linkname
assert entry.isreg
assert entry.isfile
assert not entry.issock
assert not entry.isdev
assert b'rw' in entry.strmode
assert entry.pathname == entry.path
assert entry.pathname == entry.name
def test_check_ArchiveEntry_against_TarInfo():
for name in ('special.tar', 'tar_relative.tar'):
path = join(data_dir, name)
tarinfos = list(get_tarinfos(path))
entries = list(get_entries(path))
for tarinfo, entry in zip(tarinfos, entries):
assert tarinfo == entry
assert len(tarinfos) == len(entries)
def test_check_archiveentry_using_python_testtar():
check_entries(join(data_dir, 'testtar.tar'))
def test_check_archiveentry_with_unicode_and_binary_entries_tar():
check_entries(join(data_dir, 'unicode.tar'))
def test_check_archiveentry_with_unicode_and_binary_entries_zip():
check_entries(join(data_dir, 'unicode.zip'))
def test_check_archiveentry_with_unicode_and_binary_entries_zip2():
check_entries(join(data_dir, 'unicode2.zip'), ignore='mode')
def test_check_archiveentry_with_unicode_entries_and_name_zip():
check_entries(join(data_dir, '\ud504\ub85c\uadf8\ub7a8.zip'))
def check_entries(test_file, regen=False, ignore=''):
ignore = ignore.split()
fixture_file = test_file + '.json'
if regen:
entries = list(get_entries(test_file))
with open(fixture_file, 'w', encoding='UTF-8') as ex:
json.dump(entries, ex, indent=2, sort_keys=True)
with open(fixture_file, encoding='UTF-8') as ex:
expected = json.load(ex)
actual = list(get_entries(test_file))
for e1, e2 in zip(actual, expected):
for key in ignore:
e1.pop(key)
e2.pop(key)
# Normalize all unicode (can vary depending on the system)
for d in (e1, e2):
for key in d:
if isinstance(d[key], text_type):
d[key] = unicodedata.normalize('NFC', d[key])
assert e1 == e2
libarchive-c-2.9/tests/test_errors.py 0000644 0002166 0000144 00000002371 13017341357 020736 0 ustar changaco users 0000000 0000000 from __future__ import division, print_function, unicode_literals
from errno import ENOENT
import pytest
from libarchive import ArchiveError, ffi, memory_writer
def test_add_files_nonexistent():
with memory_writer(bytes(bytearray(4096)), 'zip') as archive:
with pytest.raises(ArchiveError) as e:
archive.add_files('nonexistent')
assert e.value.msg
assert e.value.errno == ENOENT
assert e.value.retcode == -25
def test_check_int_logs_warnings(monkeypatch):
calls = []
monkeypatch.setattr(ffi.logger, 'warning', lambda *_: calls.append(1))
archive_p = ffi.write_new()
ffi.check_int(ffi.ARCHIVE_WARN, print, [archive_p])
assert calls == [1]
def test_check_null():
with pytest.raises(ArchiveError) as e:
ffi.check_null(None, print, [])
assert str(e)
def test_error_string_decoding(monkeypatch):
monkeypatch.setattr(ffi, 'error_string', lambda *_: None)
r = ffi._error_string(None)
assert r is None
monkeypatch.setattr(ffi, 'error_string', lambda *_: b'a')
r = ffi._error_string(None)
assert isinstance(r, type(''))
monkeypatch.setattr(ffi, 'error_string', lambda *_: '\xe9'.encode('utf8'))
r = ffi._error_string(None)
assert isinstance(r, bytes)
libarchive-c-2.9/tests/test_rwx.py 0000644 0002166 0000144 00000012477 13553052124 020246 0 ustar changaco users 0000000 0000000 """Test reading, writing and extracting archives."""
from __future__ import division, print_function, unicode_literals
import io
import json
import libarchive
from libarchive.entry import format_time
from libarchive.extract import EXTRACT_OWNER, EXTRACT_PERM, EXTRACT_TIME
from libarchive.write import memory_writer
from mock import patch
import pytest
from . import check_archive, in_dir, treestat
def test_buffers(tmpdir):
# Collect information on what should be in the archive
tree = treestat('libarchive')
# Create an archive of our libarchive/ directory
buf = bytes(bytearray(1000000))
with libarchive.memory_writer(buf, 'gnutar', 'xz') as archive:
archive.add_files('libarchive/')
# Read the archive and check that the data is correct
with libarchive.memory_reader(buf) as archive:
check_archive(archive, tree)
# Extract the archive in tmpdir and check that the data is intact
with in_dir(tmpdir.strpath):
flags = EXTRACT_OWNER | EXTRACT_PERM | EXTRACT_TIME
libarchive.extract_memory(buf, flags)
tree2 = treestat('libarchive')
assert tree2 == tree
def test_fd(tmpdir):
archive_file = open(tmpdir.strpath+'/test.tar.bz2', 'w+b')
fd = archive_file.fileno()
# Collect information on what should be in the archive
tree = treestat('libarchive')
# Create an archive of our libarchive/ directory
with libarchive.fd_writer(fd, 'gnutar', 'bzip2') as archive:
archive.add_files('libarchive/')
# Read the archive and check that the data is correct
archive_file.seek(0)
with libarchive.fd_reader(fd) as archive:
check_archive(archive, tree)
# Extract the archive in tmpdir and check that the data is intact
archive_file.seek(0)
with in_dir(tmpdir.strpath):
flags = EXTRACT_OWNER | EXTRACT_PERM | EXTRACT_TIME
libarchive.extract_fd(fd, flags)
tree2 = treestat('libarchive')
assert tree2 == tree
def test_files(tmpdir):
archive_path = tmpdir.strpath+'/test.tar.gz'
# Collect information on what should be in the archive
tree = treestat('libarchive')
# Create an archive of our libarchive/ directory
with libarchive.file_writer(archive_path, 'ustar', 'gzip') as archive:
archive.add_files('libarchive/')
# Read the archive and check that the data is correct
with libarchive.file_reader(archive_path) as archive:
check_archive(archive, tree)
# Extract the archive in tmpdir and check that the data is intact
with in_dir(tmpdir.strpath):
flags = EXTRACT_OWNER | EXTRACT_PERM | EXTRACT_TIME
libarchive.extract_file(archive_path, flags)
tree2 = treestat('libarchive')
assert tree2 == tree
def test_custom_writer_and_stream_reader():
# Collect information on what should be in the archive
tree = treestat('libarchive')
# Create an archive of our libarchive/ directory
stream = io.BytesIO()
with libarchive.custom_writer(stream.write, 'zip') as archive:
archive.add_files('libarchive/')
stream.seek(0)
# Read the archive and check that the data is correct
with libarchive.stream_reader(stream, 'zip') as archive:
check_archive(archive, tree)
@patch('libarchive.ffi.write_fail')
def test_write_fail(write_fail_mock):
buf = bytes(bytearray(1000000))
try:
with memory_writer(buf, 'gnutar', 'xz') as archive:
archive.add_files('libarchive/')
raise TypeError
except TypeError:
pass
assert write_fail_mock.called
@patch('libarchive.ffi.write_fail')
def test_write_not_fail(write_fail_mock):
buf = bytes(bytearray(1000000))
with memory_writer(buf, 'gnutar', 'xz') as archive:
archive.add_files('libarchive/')
assert not write_fail_mock.called
@pytest.mark.parametrize(
'archfmt,data_bytes',
[('zip', b'content'),
('gnutar', b''),
('pax', json.dumps({'a': 1, 'b': 2, 'c': 3}).encode()),
('7zip', b'lorem\0ipsum')])
def test_adding_entry_from_memory(archfmt, data_bytes):
entry_path = 'testfile.data'
entry_data = data_bytes
entry_size = len(data_bytes)
blocks = []
archfmt = 'zip'
has_birthtime = archfmt != 'zip'
atime = (1482144741, 495628118)
mtime = (1482155417, 659017086)
ctime = (1482145211, 536858081)
btime = (1482144740, 495628118) if has_birthtime else None
def write_callback(data):
blocks.append(data[:])
return len(data)
with libarchive.custom_writer(write_callback, archfmt) as archive:
archive.add_file_from_memory(
entry_path, entry_size, entry_data,
atime=atime, mtime=mtime, ctime=ctime, birthtime=btime
)
buf = b''.join(blocks)
with libarchive.memory_reader(buf) as memory_archive:
for archive_entry in memory_archive:
expected = entry_data
actual = b''.join(archive_entry.get_blocks())
assert expected == actual
assert archive_entry.path == entry_path
assert archive_entry.atime in (atime[0], format_time(*atime))
assert archive_entry.mtime in (mtime[0], format_time(*mtime))
assert archive_entry.ctime in (ctime[0], format_time(*ctime))
if has_birthtime:
assert archive_entry.birthtime in (
btime[0], format_time(*btime)
)
libarchive-c-2.9/tests/test_security_flags.py 0000644 0002166 0000144 00000002042 13307207473 022442 0 ustar changaco users 0000000 0000000 """Test security-related extraction flags."""
from __future__ import division, print_function, unicode_literals
import pytest
import os
from libarchive import extract_file
from libarchive.ffi import version_number
from libarchive.extract import EXTRACT_SECURE_NOABSOLUTEPATHS, \
EXTRACT_SECURE_NODOTDOT
from libarchive.exception import ArchiveError
from . import data_dir
def run_test(flag, filename):
archive_path = os.path.join(data_dir, 'flags.tar')
try:
extract_file(archive_path)
with pytest.raises(ArchiveError):
extract_file(archive_path, flag)
finally:
if os.path.exists(filename):
os.remove(filename)
def test_no_dot_dot():
run_test(EXTRACT_SECURE_NODOTDOT,
'../python-libarchive-c-test-dot-dot-file')
def test_absolute():
# EXTRACT_SECURE_NOABSOLUTEPATHS was only added in 3.1.900
# 3.1.900 -> 3001009
if version_number() >= 3001009:
run_test(EXTRACT_SECURE_NOABSOLUTEPATHS,
'/tmp/python-libarchive-c-test-absolute-file')
libarchive-c-2.9/tox.ini 0000644 0002166 0000144 00000000460 13553041177 016161 0 ustar changaco users 0000000 0000000 [tox]
envlist=py27,py35,py36,py37,py38
skipsdist=True
[testenv]
passenv = LIBARCHIVE
commands=
python -m pytest -Wd -vv --boxed --cov libarchive --cov-report term-missing {toxinidir}/tests {posargs}
flake8 {toxinidir}
deps=
flake8
pytest
pytest-cov
pytest-xdist
six
mock
libarchive-c-2.9/version.py 0000644 0002166 0000144 00000002446 13017341356 016710 0 ustar changaco users 0000000 0000000 # Source: https://github.com/Changaco/version.py
from os.path import dirname, isdir, join
import re
from subprocess import CalledProcessError, check_output
PREFIX = ''
tag_re = re.compile(r'\btag: %s([0-9][^,]*)\b' % PREFIX)
version_re = re.compile('^Version: (.+)$', re.M)
def get_version():
# Return the version if it has been injected into the file by git-archive
version = tag_re.search('$Format:%D$')
if version:
return version.group(1)
d = dirname(__file__)
if isdir(join(d, '.git')):
# Get the version using "git describe".
cmd = 'git describe --tags --match %s[0-9]* --dirty' % PREFIX
try:
version = check_output(cmd.split()).decode().strip()[len(PREFIX):]
except CalledProcessError:
raise RuntimeError('Unable to get version number from git tags')
# PEP 440 compatibility
if '-' in version:
if version.endswith('-dirty'):
raise RuntimeError('The working tree is dirty')
version = '.post'.join(version.split('-')[:2])
else:
# Extract the version from the PKG-INFO file.
with open(join(d, 'PKG-INFO')) as f:
version = version_re.search(f.read()).group(1)
return version
if __name__ == '__main__':
print(get_version())