semvec/pypi-packages huggingface dataset:
accelerated-numpy 0.1.0
Faster loops for NumPy using multithreading and other tricks
License: MIT
Requires Python: >=3.6

# numpy-threading-extensions
Faster loops for NumPy using multithreading and other tricks. The first release
will target NumPy binary and unary ufuncs. Eventually we will enable overriding
other NumPy functions, and provide an C-based (non-Python) API for extending
via third-party functions.

[![Travis CI Build Status](https://api.travis-ci.org/Quansight/numpy-threading-extensions.svg)](https://travis-ci.org/Quansight/numpy-threading-extensions)

[![Coverage Status](https://codecov.io/gh/Quansight/numpy-threading-extensions/branch/main/graphs/badge.svg)](https://codecov.io/github/Quansight/numpy-threading-extensions)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

## Installation
```
pip install accelerated_numpy
```

You can also install the in-development version 0.0.1 with:
```
pip install https://github.com/Quansight/numpy-threading-extensions/archive/v0.0.1.zip
```
or latest with
```
pip install https://github.com/Quansight/numpy-threading-extensions/archive/main.zip
```

## Documentation

To use the project:

```python
    import accelerated_numpy
    accelerated_numpy.initialize()
```

## Development

To run all the tests run::

```
    tox
```

Note, to combine the coverage data from all the tox environments run:

 OS | Command
----|----
Windows | `set PYTEST_ADDOPTS=--cov-append`
|        | `tox`
Other   | `PYTEST_ADDOPTS=--cov-append tox`