semvec/pypi-packages huggingface dataset:
qfetch 0.1.2
股票个人量化交易数据获取模块
Requires Python: >=3.7
Keywords: quantitative trading, stock, rust, automatic trading

# 数据获取

直接通过pip安装即可:

```shell
pip install -U qfetch
```

数据获取模块[qfetch](https://pypi.org/project/qfetch/)是相对独立的模块，主要功能是从公开的数据源获取数据。[qfetch](https://pypi.org/project/qfetch/)提供两种api，一种是异步版本，以`fetch_`开头，另外一种是阻塞版本，以`block_fetch_` 开头。

Rust编写的模块和函数是通过`qfetch.qfetch`导出，该模块原样导出Rust 封装的函数(.pyi\\ 文件)。一般情况下，是不需要使用该包下面的函数，在`qfetch.fetch`下面有此包的包装函数，包装函数除了可返回原始的Rust输出外，也提供可选装换为pd.Dataframe格式的参数。如：

```shell

In [1]: import qfetch as fetch

In [2]: await fetch.fetch_trade_date()
Out[2]: 
      trade_date
0       20120104
1       20120105
2       20120106
3       20120109
4       20120110
...          ...
8306    20021225
8307    20021226
8308    20021227
8309    20021230
8310    20021231

[8311 rows x 1 columns]
```
qdatac 0.1.2
股票个人量化交易数据中心模块
Requires Python: >=3.7
Keywords: quantitative trading, stock, rust, automatic trading

# 本地数据

直接通过pip安装即可:

```shell
pip install -U qdatac
```

[qfetch](https://pypi.org/project/qfetch/) 是获取远程数据的，而[qdatac](https://pypi.org/project/qdatac/)是如何将远程数据保存至本地以及如何获取本地数据的，也是一个相对独立的模块。[qdatac](https://pypi.org/project/qdatac/) 计划是支持四种形式的数据存储方式，文件，mongodb，mysql以及clickhouse，不过目前只实现mongodb 这种方式。将远程数据保存至本地，rust版本已经做的挺好的了，正常来说，是不太需要使用的，为了完整性保留下来。通常我们使用的是如何获取本地的数据。和[qfetch](https://pypi.org/project/qfetch/)类似，[qdatac](https://pypi.org/project/qdatac/)也是提供阻塞和非阻塞两个版本，不同的是[qdatac](https://pypi.org/project/qdatac/) 要保存一些状态，所以以类的形式提供。
robot-chat 0.51.3.dev0
RobotChat is AI robotics programming in your terminal
Requires Python: <3.13,>=3.9


<!-- Edit README.md, not index.md -->

# RobotChat is AI pair programming in your terminal for robots running Intel RealSense cameras and ROS2.

RobotChat (based on Aider) lets you pair program with LLMs,
to write and edit code in your local git repository.
Start a new project or work with an existing git repo.
RobotChat works best with GPT-4o & Claude 3.5 Sonnet and can
[connect to almost any LLM](https://aider.chat/docs/llms.html).

## Getting started

You can get started quickly like this:

```
$ pip install robot-chat

# Change directory into a git repo
cd /to/your/git/repo

# Work with Claude 3.5 Sonnet on your repo
$ export ANTHROPIC_API_KEY=your-key-goes-here
$ robotchat my-robot.py

# Work with GPT-4o on your repo
$ export OPENAI_API_KEY=your-key-goes-here
$ robotchat my-robot.py
```

See the
[installation instructions](https://aider.chat/docs/install.html)
and other
[documentation](https://aider.chat/docs/usage.html)
for more details.

## Features

- Run robotchat with the files you want to edit: `robotchat <file1> <file2> ...`
- `robotchat my-robot.py`
- Ask for changes:
  - Detect a person and their distance. Move the robot to the person. Stop when it reaches their feet.
  - `/run python3 my-robot.py`
  - If the resulting code, outputs a bug, simply add it to the chat by pressing "y" and RobotChat will attempt to fix the bug so you can re /run your app.
  - Add new features or test cases.
- RobotChat will edit your files to complete your request.
- RobotChat [automatically git commits](https://aider.chat/docs/git.html) changes with a sensible commit message.
- RobotChat works with [most popular languages](https://aider.chat/docs/languages.html): python, javascript, typescript, php, html, css, and more...
- RobotChat works best with GPT-4o & Claude 3.5 Sonnet and can [connect to almost any LLM](https://aider.chat/docs/llms.html).
- RobotChat can edit multiple files at once for complex requests.
- RobotChat uses a [map of your entire git repo](https://aider.chat/docs/repomap.html), which helps it work well in larger codebases.
- Edit files in your editor while chatting with aider, and it will always use the latest version.
mkdocsi 1.4.5
convert docs folder to mkdocs site , dynamic nested docs and folders

# mkdocsi : 

## Why  : 
consider you have nested folders that have makrdown documentation and want tool that convert them to website dynamiccly build the sute map urls according to path to url .



## Installation : 
```bash
pip install mkdocsi
```

## Quick start : 
all agumenst passed are optionnals  : 
```bash
python -m mkdocsi --docs=./docs --index=./README.md --site_name=documentation --mkdocs=./mkdocs.yml
```
when it come to doc repo git its handy to consider README.md as home page and have `docs` folder have all makdown files 

```bash
mkdocsi --docs=./docs --index=./README.md 
```