It provides:
a powerful N-dimensional array object
sophisticated (broadcasting) functions
tools for integrating C/C++ and Fortran code
useful linear algebra, Fourier transform, and random number capabilities
and much more
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
All NumPy wheels distributed on PyPI are BSD licensed.
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Release files for numpy-mips64 1.17.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| numpy_mips64-1.17.4.tar.gz | 5.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| numpy_mips64-1.17.4-cp37-cp37m-manylinux2010_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.12+ x86-64 | Details |
Total release size: 15.7 MB
Release files / numpy_mips64-1.17.4.tar.gz
| Download URL | numpy_mips64-1.17.4.tar.gz |
|---|---|
| Size | 5.8 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.4
|
Release files / numpy_mips64-1.17.4-cp37-cp37m-manylinux2010_x86_64.whl
| Download URL | numpy_mips64-1.17.4-cp37-cp37m-manylinux2010_x86_64.whl |
|---|---|
| Size | 9.9 MB |
| Tags | CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.4
|
