semvec/pypi-packages huggingface dataset:
tushare-interface 0.2.0
An interface encapsulated based on Tushare, which implements rate limiting and retry mechanisms.
Requires Python: >=3.10
Keywords: tushare, stock

# tushare-interface
将tushare接口封装在类中，并提供限流、重试功能

#### 安装教程
1.  pip install tushare-interface
2.  在.bashrc中添加环境变量：
-   export TUSHARE_TOKEN='xxxxxxxxxx'  该api从tushare.pro网站购买
-   export TUSHARE_POINTS='120', 设置你的实际积分，将据此设定每分钟可访问接口的次数，需要注意的是，与网站上说明的不同，120积分实际只支持10次查询/分钟

#### 使用说明

1.  from tushare_interface import interfaceTuShare as pro
2.  package内有实例化对象: interfaceTuShare, 
-   如果环境变量已经设置好，import后即可使用
-   如果环境变量未设置，可通过setToken函数设置从htp://tushare.pro获得的token; 以及
-   通过setPoints函数设置积分，最低120
3.  interfaceTuShare还可以使用setRetry设置重试次数（最少0次）和重试间隔（以秒为单位，最低1秒）
4.  如果发现请求后出现流控告警，可以通过setTimesPerMinutus直接设置每分钟发送请求的数量，最低1次/分钟。
5.  调用query接口从tushare下载数据，接口与tushare原始的query保持一致
6.  函数原型
-   setToken(self, token: str) -> None
-   setPoints(self, points: int) -> None:
-   setTimesPerMinutus(self, timesPerMinutus: int) -> None
-   setRetry(self, retrys: int, secondsWaitRetry: int) -> None
-   query(self, func_name: str, **kwds: object) -> pandas.DataFrame | None
felonfinder 1.0.3
Felon Finder facilitates face recognition through variational autoencoding and genetics-inspired algorithm.
Requires Python: ==3.12.2

# FELON FINDER

This application aims to facilitate the recognition of a potential assailant by producing composite sketches.

## Table of contents
* [General info](#general-info-)
* [Installation, Documentation, Q&A](#installation-documentation-qa-)

### General info :
***

When launching FELON FINDER, four randomly selected images from our database (celebA dataset) are presented to the user.

The user selects the most similar images. They can choose from one to four photos each time.

By clicking on the "Valider" button, the selected images are then processed to produce four new composite sketches that increasingly resemble the assailant.

Once the user has identified a suitable sketch, they can save the image.

The software is currently only available in French.

### Installation, Documentation, Q&A :
***

[Read the documentation](https://alexandrelayous.github.io/felon-finder/)
webdomains 1.0.0b3
Manage your Web domains served by NGINX
Requires Python: >=3.8

# webdomains

Manage your Web domains served by NGINX.

## Installation
### Requirements

On a Debian-based host, you will need an already configured and running
[NGINX server](https://nginx.net/). You may also install the following
packages to satisfy the Python dependencies:
- `python3-click`
- `python3-jinja2`

To generate the SSL/TLS certificates for the domains, you will also have to
install and configure [dehydrated](https://dehydrated.io/). It is recommended
to use a recent version - i.e. from `buster-backports`. To serve the ACME
challenge, the default NGINX configuration of a domain is looking for
`/etc/nginx/snippets/acme-challenge.conf` - which can just contain:

```nginx
location /.well-known/acme-challenge {
    default_type "text/plain";
    alias        /var/lib/dehydrated/acme-challenges;
}
```

### Configuration

You can provide your own `server.conf` template which is used to generate the
NGINX configuration of a new domain. *webdomains* will look for a file with this
name in `/etc/webdomains/templates` at first. If it does not exist, the
[default template](webdomains/templates/server.conf) is used.

## Development

To set up a development environment, all you need to have to install is a
Python 3 interpreter, Git and Make. Then, run the following:

```bash
git clone https://framagit.org/cliss21/webdomains.git
cd webdomains/

# create and active a virtual environment
python3 -m venv venv/
source venv/bin/activate

# install the package with test requirements
pip install --editable ".[dev]"
```

You can now run the following commands:
- `make lint`: check the code syntax
- `make test`: run the tests
- `make coverage`: report the code coverage

## License

*webdomains* is mainly developed by [Cliss XXI](https://www.cliss21.com) and
licensed under the [GPLv3+](LICENSE). Any contribution is welcome!