File: PKG-INFO

package info (click to toggle)
cloudpickle 0.8.0-1
  • links: PTS, VCS
  • area: main
  • in suites: buster
  • size: 216 kB
  • sloc: python: 1,894; makefile: 9
file content (122 lines) | stat: -rw-r--r-- 4,722 bytes parent folder | download | duplicates (2)
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
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
Metadata-Version: 1.1
Name: cloudpickle
Version: 0.8.0
Summary: Extended pickling support for Python objects
Home-page: https://github.com/cloudpipe/cloudpickle
Author: Cloudpipe
Author-email: cloudpipe@googlegroups.com
License: BSD 3-Clause License
Description: # cloudpickle
        
        [![Build Status](https://travis-ci.org/cloudpipe/cloudpickle.svg?branch=master
            )](https://travis-ci.org/cloudpipe/cloudpickle)
        [![codecov.io](https://codecov.io/github/cloudpipe/cloudpickle/coverage.svg?branch=master)](https://codecov.io/github/cloudpipe/cloudpickle?branch=master)
        
        `cloudpickle` makes it possible to serialize Python constructs not supported
        by the default `pickle` module from the Python standard library.
        
        `cloudpickle` is especially useful for **cluster computing** where Python
        code is shipped over the network to execute on remote hosts, possibly close
        to the data.
        
        Among other things, `cloudpickle` supports pickling for **lambda functions**
        along with **functions and classes defined interactively** in the
        `__main__` module (for instance in a script, a shell or a Jupyter notebook).
        
        **`cloudpickle` uses `pickle.HIGHEST_PROTOCOL` by default**: it is meant to
        send objects between processes running the **same version of Python**.
        
        Using `cloudpickle` for **long-term object storage is not supported and
        discouraged.**
        
        
        Installation
        ------------
        
        The latest release of `cloudpickle` is available from
        [pypi](https://pypi.python.org/pypi/cloudpickle):
        
            pip install cloudpickle
        
        
        Examples
        --------
        
        Pickling a lambda expression:
        
        ```python
        >>> import cloudpickle
        >>> squared = lambda x: x ** 2
        >>> pickled_lambda = cloudpickle.dumps(squared)
        
        >>> import pickle
        >>> new_squared = pickle.loads(pickled_lambda)
        >>> new_squared(2)
        4
        ```
        
        Pickling a function interactively defined in a Python shell session
        (in the `__main__` module):
        
        ```python
        >>> CONSTANT = 42
        >>> def my_function(data):
        ...    return data + CONSTANT
        ...
        >>> pickled_function = cloudpickle.dumps(my_function)
        >>> pickle.loads(pickled_function)(43)
        85
        ```
        
        Running the tests
        -----------------
        
        - With `tox`, to test run the tests for all the supported versions of
          Python and PyPy:
        
              pip install tox
              tox
        
          or alternatively for a specific environment:
        
              tox -e py37
        
        
        - With `py.test` to only run the tests for your current version of
          Python:
        
              pip install -r dev-requirements.txt
              PYTHONPATH='.:tests' py.test
        
        
        History
        -------
        
        `cloudpickle` was initially developed by [picloud.com](http://web.archive.org/web/20140721022102/http://blog.picloud.com/2013/11/17/picloud-has-joined-dropbox/) and shipped as part of
        the client SDK.
        
        A copy of `cloudpickle.py` was included as part of PySpark, the Python
        interface to [Apache Spark](https://spark.apache.org/). Davies Liu, Josh
        Rosen, Thom Neale and other Apache Spark developers improved it significantly,
        most notably to add support for PyPy and Python 3.
        
        The aim of the `cloudpickle` project is to make that work available to a wider
        audience outside of the Spark ecosystem and to make it easier to improve it
        further notably with the help of a dedicated non-regression test suite.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: System :: Distributed Computing