https://github.com/datalib/proclib

pythonic processes
https://github.com/datalib/proclib

Last synced: 2 months ago
JSON representation

pythonic processes

• Host: GitHub
• URL: https://github.com/datalib/proclib
• Owner: datalib
• License: mit
• Created: 2015-04-14T08:34:32.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2015-06-12T01:40:02.000Z (over 9 years ago)
• Last Synced: 2024-09-20T11:35:54.732Z (4 months ago)
• Language: Python
• Size: 672 KB
• Stars: 12
• Watchers: 6
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

• starred-awesome - proclib - pythonic processes (Python)

README

        
.. image:: https://raw.githubusercontent.com/datalib/proclib/master/media/logo-small.png

Proclib is a high level wrapper/abstraction around the standard

library subprocess module, written in Python, with proper piping

support which aims to simplify the usage of Unix utilities right

from Python and help the developer focus on the commands and not

the code which calls the commands.

.. image:: https://travis-ci.org/datalib/proclib.svg?branch=master

    :target: https://travis-ci.org/datalib/proclib

Overview

--------

`proclib.api.spawn(cmd)`

    Given a string or list making up commands *cmd*, return

    a Response object which is the result of piping the commands,

    i.e. they are run in *parallel*. The ``data`` parameter can be

    used to configure the data passed in to the initial process.

    Usage example::

        >>> from proclib.api import spawn

        >>> r = spawn('yes | head')

        >>> r.stdout.read()

        'y\ny\ny\ny\ny\ny\ny\ny\ny\ny\n'

        >>> r.close()

        >>> r.history[0].explain_signal()

        {'action': 'kill',

         'description': 'write on a pipe with no readers',

         'id': 13,

         'signal': 'SIGPIPE'}

    Streaming support is built-in- that is that the stdout of

    any process can be streamed lazily instead of read and stored

    in memory all in one go. Also, any kind of iterable can be

    piped to the process::

        def gen():

            yield 'hi\n'

            yield 'ho\n'

        r = spawn('cat', data=gen())

        assert r.out.split() == ['hi', 'ho']