Owner
numpy
11 indexed repositories · View on GitHub
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numpy
The fundamental package for scientific computing with Python.
Python · 32784 stars
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x86-simd-sort
C++ template library for high performance SIMD based sorting algorithms
C++ · 1027 stars
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numpy-tutorials
NumPy tutorials & educational content in notebook format
673 stars
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numpy-financial
Standalone package of the NumPy financial functions
Python · 409 stars
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numpydoc
Numpy's Sphinx extensions
Python · 355 stars
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numpy.org
The NumPy home page
Shell · 128 stars
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numtype
Experimental Typing Stubs for NumPy
Python · 79 stars
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numpy-quaddtype
A cross-platform Quad (128-bit) float Data-Type for NumPy.
Python · 24 stars
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archive
Archive of documents related to the project governance and management
Jupyter Notebook · 15 stars
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numpy-simd-routines
SIMD math routines used in NumPy
C++ · 10 stars
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numpy-release
Repository for building numpy release artifacts and making releases to PyPI
Shell · 4 stars
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Difficulty 4/5 3-5 days Newbie friendliness 48/100
numpy/x86-simd-sort#240 ·
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00 - Bug
Difficulty 3/5 1-2 days Newbie friendliness 76/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 55/100
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01 - Enhancement triage review
Difficulty 5/5 Over a week Newbie friendliness 30/100
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01 - Enhancement triage review
Difficulty 5/5 Over a week Newbie friendliness 35/100
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01 - Enhancement triage review
Difficulty 5/5 Over a week Newbie friendliness 35/100
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sustain-2026
Difficulty 5/5 Over a week Newbie friendliness 35/100
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00 - Bug 07 - Deprecation sustain-2026
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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Difficulty 5/5 Over a week Newbie friendliness 35/100
numpy/numpy-release#65 · 2 comments ·
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00 - Bug
Difficulty 3/5 1-2 days Newbie friendliness 58/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 45/100
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00 - Bug
Difficulty 3/5 1-2 days Newbie friendliness 72/100
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01 - Enhancement triage review
Difficulty 4/5 3-5 days Newbie friendliness 52/100
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Difficulty 4/5 3-5 days Newbie friendliness 42/100
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00 - Bug triage review
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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Difficulty 5/5 Over a week Newbie friendliness 25/100
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Difficulty 5/5 Over a week Newbie friendliness 25/100
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00 - Bug component: numpy.strings
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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check_cpu_feature_support makes repeated/unnecessary calls to std::getenv("XSS_DISABLE_AVX512") Open
Difficulty 1/5 Under an hour Newbie friendliness 84/100
numpy/x86-simd-sort#239 · 1 comment ·
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00 - Bug
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
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BUG: Failing `test_unary_spurious_fpexception` and `test_floor_division_errors` tests on RISC-V Open00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 35/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 65/100
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00 - Bug
Difficulty 3/5 1-2 days Newbie friendliness 68/100
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01 - Enhancement
Difficulty 4/5 3-5 days Newbie friendliness 45/100
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ENH: use existing non-contiguous SIMD path for integer np.minimum/np.maximum (currently float-only) Open
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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04 - Documentation
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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sustain-2026
Difficulty 5/5 Over a week Newbie friendliness 35/100
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04 - Documentation sustain-2026
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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BUG: Integer overflow in stride × step/index multiplication causes segfault during array indexing Open00 - Bug sustain-2026
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 55/100
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Difficulty 3/5 1-2 days Newbie friendliness 52/100
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01 - Enhancement component: numpy.strings
Difficulty 3/5 1-2 days Newbie friendliness 52/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 45/100
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01 - Enhancement
Difficulty 4/5 3-5 days Newbie friendliness 58/100
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41 - Static typing
Difficulty 3/5 1-2 days Newbie friendliness 52/100
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bug
numpy/numpy-quaddtype#113 · 1 comment · 1 assignee ·
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bug
numpy/numpy-quaddtype#112 · 1 assignee ·
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00 - Bug
Difficulty 4/5 3-5 days Newbie friendliness 42/100
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00 - Bug 39 - free-threading component: numpy.random
Difficulty 5/5 Over a week Newbie friendliness 35/100
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00 - Bug component: numpy.random
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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00 - Bug
Difficulty 3/5 1-2 days Newbie friendliness 72/100
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PERF: `np.unique` has massive performance regression for large numeric arrays due to `_unique_hash` Open
Difficulty 4/5 3-5 days Newbie friendliness 48/100
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Difficulty 2/5 1-3 hours Newbie friendliness 76/100
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Difficulty 4/5 3-5 days Newbie friendliness 42/100
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BUG: Signed integer overflow in datetime.c - comprehensive fix needed for all arithmetic operations Open00 - Bug sustain-2026
Difficulty 5/5 Over a week Newbie friendliness 42/100
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63 - C API component: distribution
Difficulty 5/5 Over a week Newbie friendliness 30/100
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