.. _debugging_c_extensions: {{ header }} ====================== Debugging C extensions ====================== Pandas uses Cython and C/C++ `extension modules `_ to optimize performance. Unfortunately, the standard Python debugger does not allow you to step into these extensions. Cython extensions can be debugged with the `Cython debugger `_ and C/C++ extensions can be debugged using the tools shipped with your platform's compiler. For Python developers with limited or no C/C++ experience this can seem a daunting task. Core developer Will Ayd has written a 3 part blog series to help guide you from the standard Python debugger into these other tools: 1. `Fundamental Python Debugging Part 1 - Python `_ 2. `Fundamental Python Debugging Part 2 - Python Extensions `_ 3. `Fundamental Python Debugging Part 3 - Cython Extensions `_ Generating debug builds ----------------------- By default building pandas from source will generate a release build. To generate a development build you can type:: pip install -ve . --no-build-isolation --config-settings=builddir="debug" --config-settings=setup-args="-Dbuildtype=debug" By specifying ``builddir="debug"`` all of the targets will be built and placed in the debug directory relative to the project root. This helps to keep your debug and release artifacts separate; you are of course able to choose a different directory name or omit altogether if you do not care to separate build types. Editor support -------------- The meson build system generates a `compilation database `_ automatically and places it in the build directory. Many language servers and IDEs can use this information to provide code-completion, go-to-defintion and error checking support as you type. How each language server / IDE chooses to look for the compilation database may vary. When in doubt you may want to create a symlink at the root of the project that points to the compilation database in your build directory. Assuming you used *debug* as your directory name, you can run:: ln -s debug/compile_commands.json .