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alkymi-0.0.7
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alkymi - Pythonic task automation
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | alkymi-0.0.7 |
| نام | alkymi |
| نسخه کتابخانه | 0.0.7 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Mathias Bøgh Stokholm |
| ایمیل نویسنده | mathias.stokholm@gmail.com |
| آدرس صفحه اصلی | https://github.com/MathiasStokholm/alkymi |
| آدرس اینترنتی | https://pypi.org/project/alkymi/ |
| مجوز | MIT |
# alkymi ⚗️
[](https://github.com/MathiasStokholm/alkymi/actions?query=workflow%3Abuild)
[](https://alkymi.readthedocs.io/en/latest/?badge=latest)
[](https://codecov.io/gh/MathiasStokholm/alkymi)
[](https://pypi.org/project/alkymi)
[](https://pypi.org/project/alkymi)
Alkymi is a pure Python (3.6+) library for describing and executing tasks and pipelines with built-in caching and
conditional evaluation based on checksums.
Alkymi is easy to install, simple to use, and has no dependencies outside of Python's standard library. The code is
cross-platform, and allows you to write your pipelines once and deploy to multiple operating systems (tested on Linux,
Windows and Mac).
Documentation, including a quickstart guide, is provided [here](https://alkymi.readthedocs.io/en/latest/).
## Features
* Easily define complex data pipelines as decorated Python functions
* This allows you to run linting, type checking, etc. on your data pipelines
* Return values are automatically cached to disk, regardless of type
* Efficiently checks if pipeline is up-to-date
* Checks if external files have changed, bound functions have changed or if pipeline dependencies have changed
* No domain specific language (DSL) or CLI tool, just regular Python
* Supports caching and conditional evaluation in Jupyter Notebooks
* Cross-platform - works on Linux, Windows and Mac
* Expose recipes as a command-line interface (CLI) using alkymi's
[Lab](https://alkymi.readthedocs.io/en/latest/examples/command_line.html) type
## Sample Usage
For examples of how to use alkymi, see the
[quickstart guide](https://alkymi.readthedocs.io/en/latest/getting_started/quick_start.html).
Example code:
```python
import numpy as np
import alkymi as alk
@alk.recipe()
def long_running_task() -> np.ndarray:
# Perform expensive computation here ...
hard_to_compute_result = np.array([42])
# Return value will be automatically cached to disk
return hard_to_compute_result
result = long_running_task.brew() # == np.ndarray([42])
```
Or one of the examples, e.g. [MNIST](https://alkymi.readthedocs.io/en/latest/examples/mnist.html).
## Upcoming Features
The following features are being considered for future implementation:
* Type annotations propagated from bound functions to recipes
* Support for call/type checking all recipes (e.g. by adding a `check` command to `Lab`)
* Cache maintenance functionality
* Parallel execution of pipeline
## Known Issues
* alkymi currently doesn't check custom objects for altered external files when computing cleanliness (e.g. `MyClass`
has a `self._some_path` that points to a file somewhere outside alkymi's internal cache)
* `alk.foreach()` currently only supports enumerable inputs of type `List` or `Dict`
* Recipes marked `transient` will always be dirty, and thus always require reevaluation. This functionality should be
replaced by a proper means of creating recipes that don't cache outputs, but only run when needed to provide inputs for
downstream recipes
## Installation
Install via pip:
```shell script
pip install --user alkymi
```
Or see the [Installation page](https://alkymi.readthedocs.io/en/latest/getting_started/installation.html).
### Testing
After installing, you can run the test suite (use the `lint`, `coverage` and `type_check` recipes to perform those
actions):
```shell script
python3 labfile.py brew test
```
## License
alkymi is licensed under The MIT License as found in the LICENSE.md file
نیازمندی
| مقدار | نام |
|---|---|
| >=2.0.0 | xxhash |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl alkymi-0.0.7:
pip install alkymi-0.0.7.whl
نصب پکیج tar.gz alkymi-0.0.7:
pip install alkymi-0.0.7.tar.gz