Measuring subprocesses

If your system under test spawns subprocesses, you’ll have to take extra steps to measure coverage in those processes. There are a few ways to ensure they get measured. The approach you use depends on how you create the processes.

No matter how your subprocesses are created, you will need the parallel option to collect separate data for each process, and the coverage combine command to combine them together before reporting.

To successfully write a coverage data file, the Python subprocess under measurement must shut down cleanly and have a chance for coverage.py to run its termination code. It will do that when the process ends naturally, or when a SIGTERM signal is received.

If your processes are ending with SIGTERM, you must enable the [run] sigterm setting to configure coverage to catch SIGTERM signals and write its data.

Other ways of ending a process, like SIGKILL or os._exit, will prevent coverage.py from writing its data file, leaving you with incomplete or non-existent coverage data.

Note

Subprocesses will only see coverage options in the configuration file. Options set on the command line will not be visible to subprocesses.

Using multiprocessing

The multiprocessing module in the Python standard library provides high-level tools for managing subprocesses. If you use it, the concurrency=multiprocessing and sigterm settings will configure coverage to measure the subprocesses.

Even with multiprocessing, you have to be careful that all subprocesses terminate cleanly or they won’t record their coverage measurements. For example, the correct way to use a Pool requires closing and joining the pool before terminating:

with multiprocessing.Pool() as pool:
    # ... use any of the pool methods ...
    pool.close()
    pool.join()

Implicit coverage

If you are starting subprocesses another way, you can configure Python to start coverage when it runs. Coverage.py includes a function designed to be invoked when Python starts: coverage.process_startup(). 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.

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:

Create or append to sitecustomize.py to add these lines:
```
import coverage
coverage.process_startup()
```
Create a .pth file in your Python installation containing:
```
import coverage; coverage.process_startup()
```

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.

Note that if you use one of these techniques, you must undo them if you uninstall coverage.py, since you will be trying to import it during Python start-up. Be sure to remove the change when you uninstall coverage.py, or use a more defensive approach to importing it.

Explicit coverage

Another option for running coverage on your subprocesses it to run coverage explicitly as the command for your subprocess instead of using “python” as the command. This isn’t recommended, since it requires running different code when running coverage than when not, which can complicate your test environment.