semvec/pypi-packages huggingface dataset:
cache-alchemy 0.4.5
The Python Cache Toolkit.
Keywords: cache-alchemy

===============
Cache Alchemy
===============

.. image:: https://img.shields.io/pypi/v/cache-alchemy.svg
        :target: https://pypi.python.org/pypi/cache-alchemy

.. image:: https://github.com/GuangTianLi/cache-alchemy/workflows/test/badge.svg
        :target: https://github.com/GuangTianLi/cache-alchemy/actions
        :alt: CI Test Status

.. image:: https://readthedocs.org/projects/cache-alchemy/badge/?version=latest
        :target: https://cache-alchemy.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status

.. image:: https://img.shields.io/pypi/pyversions/cache-alchemy.svg
        :target: https://pypi.org/project/cache-alchemy/

.. image:: https://codecov.io/gh/GuangTianLi/cache-alchemy/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/GuangTianLi/cache-alchemy

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
  :target: https://github.com/psf/black



The Python Cache Toolkit.


* Free software: MIT license
* Documentation: https://cache-alchemy.readthedocs.io/en/latest/

Installation
----------------

.. code-block:: shell

    $ pipenv install cache-alchemy
    ✨🍰✨

Only **Python 3.6+** is supported.

Example
--------

.. code-block:: python

    import dataclasses

    from redis import Redis

    from cache_alchemy import memory_cache, json_cache, pickle_cache
    from cache_alchemy.config import DefaultConfig

    config = DefaultConfig()
    config.cache_redis_client = Redis.from_url(config.CACHE_ALCHEMY_REDIS_URL)


    @dataclasses.dataclass
    class User:
        name: str


    @pickle_cache()
    def get(name: str) -> User:
        return User(name=name)


    @memory_cache()
    def add(i: complex, j: complex) -> complex:
        return i + j


    @json_cache()
    def add(i: int, j: int) -> int:
        return i + j


Features
----------

- Distributed cache
- Cache clear and partial clear with specific function parameter
- Cache clear cascade by dependency
- Cache ``Json Serializable`` function return value with **json_cache**
- Cache Python Object function return value with **pickle_cache**
- Cache any function return value with **memory_cache**
- LRU Dict support

TODO
-------


=======
History
=======

0.4.* (2020)
------------------

* Refactory redis cache to json cache
* Support pickle Cache
* Add backend class in function hash
* Add cache key prefix to avoid key conflict

0.2.* (2019)
------------------

* Support Partially Clear Cache with Arguments
* Support Flush Backend Cache
* Cache Redis Client Must Decode Responses

0.1.* (2019)
------------------

* Support Method and Property Cache
* Support cache as a decorator with no arguments.
* Init Project.
isddc-kube 1.0.4
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────────────────────────────────────────────────────────────────────────
Home-page: http://www.gqylpy.com
Author: 竹永康
Author-email: zhuyk4@lenovo.com
License: Lenovo OI
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Topic :: Text Processing :: Indexing
Classifier: Topic :: Utilities
Classifier: Topic :: Internet
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
q26-quanTester 0.1
A python package for trading simulation
Requires Python: >=3.6

[1]: https://www.q26.io
[2]: https://www.q26.io/data/q26_backtest_system/doc/html/
[3]: https://github.com/LoannData/Q26_BacktestSystem/wiki/Hands-on-:-A-simple-backtest 

## Q26_BacktestSystem

Q26 Backtest System is a financial investment simulation tool dedicated for algorithmic traders developped in Python 3. 

### Main features : 
- Python based : very simple configuration file & strategies design model 
- High personnalisation and very wide way of use of the tool 
- Environment free of any development bias : 
  - No access to future data during the simulation   
- Pre-Backtest data preparation : 
  - Missing data filling models 
  - Possibility to resample data to any timeframe 
  - Multiple asset synchronization 
- High realism portfolio : 
  - Leverage, margin constraints, other security constraints 
  - High precision symbols characteristics : lot size, minimum lot size, open/close/off trading hours, fees ... 
- Fully personnalisable strategies & outputs 
- Parallelisable backtest, performance optimisation & MC approach 

And a lot more features ... 

And a lot of new features soon ! 

To get more informations about the Backtest System and the other products of Q26, you can visit our web site by clicking [here][1]. Get access to the detailled documentation [here][2] 

### Getting the Q26 Backtest System 

Download the code by cloning the git repository using 
```
$ git clone https://github.com/LoannData/Q26_BacktestSystem.git
```

### Hands-on 

[Here][3] you can find a tutorial which shows how to hands-on the Q26 Backtest system
adctools 0.0.1
tools package for adc group
Requires Python: >=3.6

### adctools

提供ADC组常用的可复用工具包

#### features

1. 提供VirtualDevice类，随机获取某手机设备参数；
2. 提供CYFMonitor类，随机生成可用的`x-acf-sensor-data`;
poetry-workspaces 0.1.0
Poetry workspace plugin for Python monorepos.
Requires Python: >=3.9,<4.0

# poetry-workspace-plugin

[Poetry](https://python-poetry.org/) workspace plugin for Python monorepos.  Inspired by [Yarn Workspaces](https://classic.yarnpkg.com/en/docs/workspaces/).

Adds a new subcommand group, `poetry workspace`, which is used to create, manage and inspect nested Python projects.

```shell
# Create a new python project at the specified path, tracked in the current project
poetry workspace new libs/my-library

# Add an existing python project to the current project's workspaces
poetry workspace add libs/my-existing-library

# List the current workspaces
poetry workspace list

# Run a command in every workspace:
poetry workspace run command

# Run a command in specified workspaces:
poetry workspace run --targets=my-library,my-existing-library -- command

# List dependees of a particular workspace (from among the list of workspaces).
poetry workspace dependees my-library

# Unlink a workspace from the current project
poetry remove workspace my-library

# Unlink and delete a workspace from the current project
poetry remove workspace my-library --delete
```

### Common patterns

#### Testing affected workspaces

After making a change to a workspace, you can run tests for all _affected_ workspaces like so:
```shell
poetry workspace run --targets=$(poetry workspace dependees --csv my-library) -- pytest tests/
```

### Planned commands

The following are currently possible e.g via `poetry workspace run poetry build`, but this would be more succint:

```shell
# Build or publish all workspaces:
poetry workspace build
poetry workspace publish

# Build specified workspaces:
poetry workspace --targets=my-library build

# Publish specified workspaces:
poetry workspace --targets=my-library publish
```


Metadata regarding workspaces is stored under `tool.poetry.workspaces`:

```toml
[tool.poetry.workspace]
workspaces = {
    my-library = "libs/my-library"
}
```

## Installation

This project is not currently packaged and so must be installed manually.

Clone the project with the following command:
```
git clone https://github.com/jacksmith15/poetry-workspace-plugin.git
```

## Development

Install dependencies:

```shell
pyenv shell 3.9.4  # Or other 3.9.x
pre-commit install  # Configure commit hooks
poetry install  # Install Python dependencies
```

Run tests:

```shell
poetry run inv verify
```

# License
This project is distributed under the MIT license.