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A package providing a process execution facility on top of the POSIX fork/exec model.

Project description


execute provides a process execution facility on top of the POSIX fork/exec model. It comprises functionality similar to the standard subprocess package but behind a more intuitive and user-friendly interface. The package is not designed to be compatible with subprocess. Some functionality, such as asynchronous process execution, is not provided at all. The execution model of a pipeline, on the other hand, passing the output of one program as input to another is expressable in a very natural and efficient way. Similarly, handling of environment variables is much more simple and safe.


The execute package provides the execute function. This primitive starts a process in a synchronous manner (i.e., waiting for it to finish).

>>> from deso.execute import execute
>>> execute("/bin/echo", "-n", "hello")

It is possible to control which streams to read from. By default, everything on standard error is reported (the empty byte object seen), whereas standard output is not read. The reason for this behavior is that whenever a program fails (that is, exits with a non-zero status), an exception is raised and this exception contains the data printed to standard error. Conversely, “most” programs do not write to standard out and so by default this data is not captured.

Of course, the user is able to change this default.

>>> execute("/bin/echo", "-n", "hello", stdout=b"", stderr=None)

Here, we read the standard output, appending it to an empty bytes buffer, while simply ignoring any data on standard error. It is also possible to stream into a file by supplying a file descriptor.

>>> execute("/bin/echo", "hi", stdout=sys.stderr.fileno(), stderr=None)

We redirect the output of the echo invocation directly to standard error (which will cause it to be displayed immediately). Note that execute, by virtue of the abstraction level it works at, does not support Python’s file-like objects: A file descriptor has to be a numeric value.

Not only is it possible to read from the output strings, supplying input is possible equally well.

>>> execute("/bin/tr", "e", "a", stdin=b"hello", stdout=b"", stderr=None)

The execute function also accepts an env parameter describing the environment in which to create the new process. By default, the entire environment of the parent process is inherited. However, it is possible to selectively provide a subset of variables or to specify new ones.

>>> env = {"VAR": "42"}
>>> execute("/bin/sh", "-c", "echo ${VAR}", env=env, stdout=b"", stderr=None)


execute provides native support for another execution primitive, a pipeline. The behavior is similar to the equally named Unix primitive with the output of one process from a list of processes being provided as input to the next one.

Pipelines are accessible by means of the pipeline function. A pipeline in the package’s sense is simply a list of commands and their parameters. With a command and parameter combination being a list of strings, a pipeline is a list of a list of strings.

>>> pipeline([
...     ["/bin/echo", "-n", "hello"],
...     ["/bin/tr", "e", "a"],
...   ], stdout=b"", stderr=None
... )


The last execution primitive supported natively by execute are so called springs. A spring is a series of data producing sources whose data is accumulated in a sequential fashion. A spring can be seen as a pipeline with the first element being special in that it can comprise multiple processes supplying data to the remaining ones.

>>> spring([
...     [["/bin/echo", "hallo"], ["/bin/echo", "axacuta"]],
...     ["/bin/tr", "a", "e"]
...   ], stdout=b"", stderr=None
... )

Because of their very nature of producing output in the first stage of the pipeline, springs do not support the stdin keyword parameter. The remaining accepted parameters, however, are similar to execute and pipeline functions.


In order to use the execute package the cleanup Python module (contained in the repository in compatible and tested versions) needs to be accessible by Python (typically by installing it in a directory listed in PYTHONPATH or adjusting the latter to point to it). The same procedure should then be followed for the execute package itself.

If you are using Gentoo Linux, there is an ebuild available that can be used directly.


The module is tested with Python 3. There is no work going on to ensure compatibility with Python 2.

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