Metadata-Version: 1.1
Name: pytest-pipeline
Version: 0.1.0
Summary: Pytest plugin for functional testing of data analysis pipelines
Home-page: https://github.com/bow/pytest_pipeline
Author: Wibowo Arindrarto
Author-email: bow@bow.web.id
License: BSD
Description: ===============================
        pytest-pipeline
        ===============================
        
        
        .. image:: https://travis-ci.org/bow/pytest-pipeline.png?branch=master
                :target: https://travis-ci.org/bow/pytest-pipeline
        
        
        pytest-pipeline is a Python3-compatible pytest plugin for functional testing
        of data analysis pipelines. They are usually long-running scripts or executables
        with multiple input and/or output files + directories.
        
        It is meant for end-to-end testing where you test for conditions before the
        pipeline run and after the pipeline runs (output files, checksums, etc.).
        
        
        Installation
        ============
        
        ::
        
            pip install pytest-pipeline
        
        
        Walkthrough
        ===========
        
        For our example, we will use a super simple pipeline that writes a file and
        prints to stdout:
        
        .. code-block:: python
        
            #!/usr/bin/env python
        
            from __future__ import print_function
        
            if __name__ == "__main__":
        
                with open("result.txt", "w") as result:
                    result.write("42\n")
                print("Result computed")
        
        At this point it's just a simple script, but it should be enough to illustrate
        the plugin. Also, if you want to follow along, save the above file as
        ``run_pipeline``.
        
        With the pipeline above, here's how your test would look like with
        ``pytest_pipeline``:
        
        .. code-block:: python
        
            import os
            import shutil
            from pytest_pipeline import PipelineRun, PipelineTest, mark, utils
        
            # one pipeline run is represented by one class that subclasses PipelineTest
            class TestMyPipeline(PipelineTest):
        
                # define the pipeline execution via PipelineRun objects
                run = PipelineRun(
                    # the actual command to start your pipeline
                    cmd="./run_pipeline",
                    stdout="run.stdout",
                )
        
                # before_run-marked functions will be run before the pipeline is executed
                @mark.before_run
                def test_prep_executable(self):
                    # copy the executable to the run directory
                    shutil.copy2("/path/to/run_pipeline", "run_pipeline")
                    # testing if the file is executable
                    assert os.access("run_pipeline", os.X_OK)
        
                # after_run-marked tests will only be run after pipeline execution is finished
                @mark.after_run(order=1)
                def test_result_md5(self):
                    assert utils.file_md5sum("result.txt") == "50a2fabfdd276f573ff97ace8b11c5f4"
        
                # ordering for all tests annotated by after_run can be set manually
                # here we want to test the exit code first after the run is finished
                @mark.after_run(order=0)
                def test_exit_code(self):
                    assert self.run.exit_code == 0
        
                # we can also check the stdout that we capture as well
                @mark.after_run(order=2)
                def test_stdout(self):
                    assert open("run.stdout", "r").read().strip() == "Result computed"
        
        If the test above is saved as ``test_demo.py``, you can then run the test by
        executing ``py.test -v test_demo.py``. You should see that four tests were
        executed and all four passed.
        
        What just happened?
        -------------------
        
        You just executed your first pipeline test. The plugin itself gives you:
        
        - Test directory creation (one class gets one directory).
          By default, testdirectories are all created in the ``/tmp/pipeline_test``
          directory. You can tweak this location by supplying the
          ``--base-pipeline-dir`` command line flag.
        
        - Automatic execution of the pipeline.
          No need to ``import subprocess``, just define the command via the
          ``PipelineRun`` object. We optionally captured the standard output to a file
          called ``run.stdout`` as well. For long running pipelines, you can also supply
          a ``timeout`` argument which limits how long the pipeline process can run.
        
        - Test ordering.
          Pipelines by definition are simply series of commands executed subsequently.
          The plugin allows you to also order your tests accordingly via the
          ``before_run`` and ``after_run`` decorators. In the code above, we first test
          for the exit code before testing the output files. Using the command line flag
          ``--xfail-pipeline``, if the first test after the pipeline run fails then
          the rest will be marked as failed immediately.
        
        And since this is a py.test plugin, test discovery and execution is done via
        py.test.
        
        
        Getting + giving help
        =====================
        
        Please use the `issue tracker <https://github.com/bow/pytest-pipeline/issues>`_
        to report bugs or feature requests. You can always fork and submit a pull
        request as well.
        
        
        License
        =======
        
        See LICENSE.
        
        
        
        
        History
        -------
Keywords: pytest pipeline plugin testing
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Utilities
Classifier: Topic :: Software Development :: Testing
Classifier: Topic :: Software Development :: Libraries
