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Created 24 February 2010, last updated 25 July 2010
Complex test suites may spawn subprocesses to run tests, either to run them in parallel, or because subprocess behavior is an important part of the system under test. Measuring coverage in those subprocesses can be tricky because you have to modify the code spawning the process to invoke coverage.py.
There’s an easier way to do it: coverage.py includes a function, coverage.process_startup() designed to be invoked when Python starts. It examines the COVERAGE_PROCESS_START environment variable, and if it is set, begins coverage measurement. The environment variable’s value will be used as the name of the configuration file to use.
When using this technique, be sure to set the parallel option to true so that multiple coverage.py runs will each write their data to a distinct file.
Configuring Python for subprocess coverage
Measuring coverage in subprocesses is a little tricky. When you spawn a subprocess, you are invoking Python to run your program. Usually, to get coverage measurement, you have to use coverage.py to run your program. Your subprocess won’t be using coverage.py, so we have to convince Python to use coverage even when not explicitly invokved.
To do that, we’ll configure Python to run a little coverage.py code when it starts. That code will look for an environment variable that tells it to start coverage measurement at the start of the process.
To arrange all this, you have to do two things: set a value for the COVERAGE_PROCESS_START environment variable, and then configure Python to invoke coverage.process_startup() when Python processes start.
How you set COVERAGE_PROCESS_START depends on the details of how you create subprocesses. As long as the environment variable is visible in your subprocess, it will work.
You can configure your Python installation to invoke the process_startup function in two ways:
The sitecustomize.py technique is cleaner, but may involve modifying an existing sitecustomize.py, since there can be only one. If there is no sitecustomize.py already, you can create it in any directory on the Python path.
The .pth technique seems like a hack, but works, and is documented behavior. On the plus side, you can create the file with any name you like so you don’t have to coordinate with other .pth files. On the minus side, you have to create the file in a system-defined directory, so you may need privileges to write it.