7.2. A Map of the Numba Repository
The Numba repository is quite large, and due to age has functionality spread
around many locations. To help orient developers, this document will try to
summarize where different categories of functionality can be found.
Note
It is likely that the organization of the code base will change in the
future to improve organization. Follow issue #3807
for more details.
7.2.1. Support Files
7.2.1.1. Build and Packaging
7.2.1.2. Continuous Integration
7.2.1.3. Documentation / Examples
- LICENSE - License for Numba
- LICENSES.third-party - License for third party code vendored
into Numba
- README.rst - README for repo, also uploaded to PyPI
- CONTRIBUTING.md - Documentation on how to contribute to project
(out of date, should be updated to point to Sphinx docs)
- AUTHORS - List of Github users who have contributed PRs (out of
date)
- CHANGE_LOG - History of Numba releases, also directly embedded
into Sphinx documentation
- docs/ - Documentation source
- docs/_templates/ - Directory for templates (to override defaults
with Sphinx theme)
- docs/Makefile - Used to build Sphinx docs with
make
- docs/source - ReST source for Numba documentation
- docs/_static/ - Static CSS and image assets for Numba docs
- docs/gh-pages.py - Utility script to update Numba docs (stored
as gh-pages)
- docs/make.bat - Not used (remove?)
- examples/ - Example scripts demonstrating numba (re/move to
numba-examples repo?)
- examples/notebooks/ - Example notebooks (re/move to
numba-examples repo?)
- benchmarks/ - Benchmark scripts (re/move to numba-examples
repo?)
- tutorials/ - Tutorial notebooks (definitely out of date, should
remove and direct to external tutorials)
- numba/scripts/generate_lower_listing.py - Dump all registered
implementations decorated with
@lower* for reference
documentation. Currently misses implementations from the higher
level extension API.
7.2.2. Numba Source Code
Numba ships with both the source code and tests in one package.
- numba/ - all of the source code and tests
7.2.2.1. Public API
These define aspects of the public Numba interface.
7.2.2.3. Compiler Pipeline
7.2.2.5. Compiled Extensions
Numba uses a small amount of compiled C/C++ code for core
functionality, like dispatching and type matching where performance
matters, and it is more convenient to encapsulate direct interaction
with CPython APIs.
7.2.2.7. Core Python Data Types
7.2.2.8. Math
- numba/_random.c - Reimplementation of NumPy / CPython random
number generator
- numba/_lapack.c - Wrappers for calling BLAS and LAPACK functions
(requires SciPy)
7.2.2.9. ParallelAccelerator
Code transformation passes that extract parallelizable code from
a function and convert it into multithreaded gufunc calls.
7.2.2.10. Debugging Support
7.2.2.11. Type Signatures (CPU)
Some (usually older) Numba supported functionality separates the
declaration of allowed type signatures from the definition of
implementations. This package contains registries of type signatures
that must be matched during type inference.
7.2.2.12. Target Implementations (CPU)
Implementations of Python / NumPy functions and some data models.
These modules are responsible for generating LLVM IR during lowering.
Note that some of these modules do not have counterparts in the typing
package because newer Numba extension APIs (like overload) allow
typing and implementation to be specified together.
7.2.2.13. Ufunc Compiler and Runtime
7.2.2.14. Unit Tests (CPU)
CPU unit tests (GPU target unit tests listed in later sections
7.2.2.15. Command Line Utilities
7.2.2.16. CUDA GPU Target
Note that the CUDA target does reuse some parts of the CPU target.
7.2.2.17. ROCm GPU Target
Note that the ROCm target does reuse some parts of the CPU target, and
duplicates some code from CUDA target. A future refactoring could
pull out the common subset of CUDA and ROCm. An older version of this
target was based on the HSA API, so “hsa” appears in many places.
Numba
0.46