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coola-0.0.6
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مشاهده بیشترتوضیحات
A light library to check if two complex/nested objects are equal or not
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | coola-0.0.6 |
| نام | coola |
| نسخه کتابخانه | 0.0.6 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Thibaut Durand |
| ایمیل نویسنده | durand.tibo+gh@gmail.com |
| آدرس صفحه اصلی | https://github.com/durandtibo/coola |
| آدرس اینترنتی | https://pypi.org/project/coola/ |
| مجوز | BSD-3-Clause |
# coola
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## Overview
`coola` is a light Python library that provides simple functions to check in a single line if two
complex/nested objects are equal or not.
`coola` was initially designed to work
with [PyTorch `Tensor`s](https://pytorch.org/docs/stable/tensors.html)
and [NumPy `ndarray`](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html), but it
is possible to extend it
to [support other data structures](https://durandtibo.github.io/coola/customization).
- [Motivation](#motivation)
- [Documentation](https://durandtibo.github.io/coola/)
- [Installation](#installation)
- [Contributing](#contributing)
- [API stability](#api-stability)
- [License](#license)
## Motivation
Let's imagine you have the following dictionaries that contain both a PyTorch `Tensor` and a
NumPy `ndarray`.
You want to check if the two dictionaries are equal or not.
By default, Python does not provide an easy way to check if the two dictionaries are equal or not.
It is not possible to use the default equality operator `==` because it will raise an error.
The `coola` library was developed to fill this gap. `coola` provides a function `objects_are_equal`
that can indicate if two complex/nested objects are equal or not.
```python
import numpy
import torch
from coola import objects_are_equal
data1 = {'torch': torch.ones(2, 3), 'numpy': numpy.zeros((2, 3))}
data2 = {'torch': torch.zeros(2, 3), 'numpy': numpy.ones((2, 3))}
objects_are_equal(data1, data2)
```
`coola` also provides a function `objects_are_allclose` that can indicate if two complex/nested
objects are equal within a tolerance or not.
```python
from coola import objects_are_allclose
objects_are_allclose(data1, data2, atol=1e-6)
```
Please check the [quickstart page](https://durandtibo.github.io/coola/quickstart) to learn more on
how to use `coola`.
## Installation
We highly recommend installing
a [virtual environment](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
`coola` can be installed from pip using the following command:
```shell
pip install coola
```
To make the package as slim as possible, only the minimal packages required to use `coola` are
installed.
To include all the packages, you can use the following command:
```shell
pip install coola[all]
```
Please check the [get started page](https://durandtibo.github.io/coola/get_started) to see how to
install only some specific packages or other alternatives to install the library.
## Contributing
Please check the instructions in [CONTRIBUTING.md](.github/CONTRIBUTING.md).
## API stability
:warning: While `coola` is in development stage, no API is guaranteed to be stable from one
release to the next.
In fact, it is very likely that the API will change multiple times before a stable 1.0.0 release.
In practice, this means that upgrading `coola` to a new version will possibly break any code that
was using the old version of `coola`.
## License
`coola` is licensed under BSD 3-Clause "New" or "Revised" license available in [LICENSE](LICENSE)
file.
نیازمندی
| مقدار | نام |
|---|---|
| >=1.20,<2.0 | numpy |
| >=1.10,<3.0 | torch |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.9,<4.0 | Python |
نحوه نصب
نصب پکیج whl coola-0.0.6:
pip install coola-0.0.6.whl
نصب پکیج tar.gz coola-0.0.6:
pip install coola-0.0.6.tar.gz