1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
|
from setuptools import setup
# extract version from pickleshare.py
# can't import because pickleshare depends on path.py
with open('pickleshare.py') as f:
for line in f:
if line.startswith('__version__'):
version = eval(line.split('=', 1)[1])
break
setup(
name="pickleshare",
version=version,
py_modules=['pickleshare'],
author="Ville Vainio",
author_email="vivainio@gmail.com",
description="Tiny 'shelve'-like database with concurrency support",
license="MIT",
extras_require = {
# Ugly, but we can't do < comparison here
':python_version in "2.6 2.7 3.2 3.3"': ['pathlib2'],
},
url="https://github.com/pickleshare/pickleshare",
keywords="database persistence pickle ipc shelve",
long_description="""\
PickleShare - a small 'shelve' like datastore with concurrency support
Like shelve, a PickleShareDB object acts like a normal dictionary. Unlike shelve,
many processes can access the database simultaneously. Changing a value in
database is immediately visible to other processes accessing the same database.
Concurrency is possible because the values are stored in separate files. Hence
the "database" is a directory where *all* files are governed by PickleShare.
Example usage::
from pickleshare import *
db = PickleShareDB('~/testpickleshare')
db.clear()
print("Should be empty:",db.items())
db['hello'] = 15
db['aku ankka'] = [1,2,313]
db['paths/are/ok/key'] = [1,(5,46)]
print(db.keys())
This module is certainly not ZODB, but can be used for low-load
(non-mission-critical) situations where tiny code size trumps the
advanced features of a "real" object database.
Installation guide: pip install pickleshare
""",
classifiers=[
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
]
)
|
