semvec/pypi-packages huggingface dataset:
feigua-data-collection 1.0.1
Feigua Zhitou data collection
License: MIT
Requires Python: >=3.9

# feigua-data-collection
飞瓜智投数据采集工具

## 安装
```bash
pip install feigua-data-collection
```

## 使用方法
### 连接浏览器
```python
from FeiguaDataCollection import Collector

collector = Collector()
collector.connect_browser(port=9527)

```

### 获取团队管理数据

在获取数据之前可以现在浏览器中打开目标页面, 这样子就可以直接使用已打开的页面

```python
# 获取 团队管理-主播排行-主播排行 数据
result = collector.team_manage.anchor.get__anchor_rank__detail(
    begin_date='2025-01-20', end_date='2025-01-20'
)

# ... 其他数据获取方法与上面类似
```
ACSpy 0.0.9
Package for working with ACS motion controllers.
License: MIT

ACSpy
=====

A Python package for working with [ACS motion controllers](https://www.acsmotioncontrol.com/). Note that this project is not 
affiliated with or endorsed by ACS Motion Control. 


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

Note that the ACS motion control SPiiPlus User-Mode Driver must be installed and running. Contact ACS to obtain this software.

This Python package can be installed from PyPI via `pip` with

    pip install acspy
    
To install from the source, clone locally and execute

    python setup.py install


Usage
-----

### Using the `acsc` module

The `acsc` module is designed to mimic the syntax of the ACS C library that it
wraps.

```python
>>> from acspy import acsc
>>> hcomm = acsc.openCommDirect()
>>> acsc.enable(hcomm, 0)
>>> acsc.getMotorState(hcomm, 0)
{'moving': False, 'enabled': True, 'in position': True, 'accelerating': False}
>>> acsc.closeComm(hcomm)
```


### Using the `Controller` object

The `control` module provides an object-oriented interface to the controller,
making code development more intuitive. An example of its use:

```python
>>> from acspy.control import Controller
>>> controller = Controller(contype="simulator", n_axes=4)
>>> controller.connect()
>>> axis0 = controller.axes[0]
>>> axis0.enable()
>>> axis0.enabled
True
>>> axis0.ptp(500.5)
>>> axis0.rpos
500.5
>>> axis0.disable()
>>> controller.disconnect()
```
zenduty-api 1.0.0
Python SDK wrapper for the Zenduty API
License: MIT
Requires Python: >=3.9


        # Zenduty Python SDK

        The **Zenduty Python SDK** provides a seamless way to integrate with Zenduty's powerful incident management platform. Whether you're building automated workflows, custom dashboards, or advanced monitoring solutions, this SDK offers the tools you need to connect with Zenduty's API endpoints efficiently.

        ## About Zenduty

        Zenduty is a cutting-edge incident management platform designed to help teams resolve incidents faster, smarter, and with greater ease. By leveraging advanced automation, Zenduty ensures that developers and engineers stay in control during high-pressure scenarios. Zenduty empowers teams to:

        - Proactively identify and resolve issues before they escalate.
        - Collaborate effectively to minimize downtime and service disruptions.
        - Improve reliability and customer satisfaction with actionable insights.

        ## Why Use the Zenduty Python SDK?

        The Zenduty Python SDK is crafted for developers looking to integrate their applications or services with Zenduty. It simplifies the process of interacting with Zenduty's API and supports robust and scalable integrations for a variety of use cases, including:

        - Triggering, acknowledging, and resolving incidents programmatically.
        - Accessing detailed analytics and reporting data.
        - Managing services, teams, schedules, and escalation policies.
        - Building automation pipelines for incident notifications and workflows.

        ## Key Features

        - **Ease of Use**: Intuitive methods and structures to reduce development time.
        - **Comprehensive API Support**: Full access to Zenduty's endpoints for managing incidents, teams, schedules, and more.
        - **Scalability**: Designed to handle complex workflows and high-volume environments.
        - **Compatibility**: Works seamlessly with modern Python environments and frameworks.

        ## Installation

        You can install the Zenduty Python SDK quickly via pip:

        ```sh
        $ pip install zenduty-api
        ```
        
        or you may grab the latest source code from GitHub:

        ```sh
        $ git clone https://github.com/Zenduty/zenduty-python-sdk
        ```

        ## Docs
        Please refer this link to understand the SDK better. https://github.com/Zenduty/zenduty-python-sdk
qftools 0.1.1
Python Toolkit for Quantitative Finance
License: MIT
Requires Python: >=3.12

# QFTools

QFTools is a Python library for quantitative finance calculations, currently focusing on date arithmetic and calendar operations. More features will be added in future releases.

## Requirements

- Python ≥ 3.13
- NumPy ≥ 2.2.1

## Installation

```bash
pip install qftools
```

## Current Features

- Calendar Operations
- Day Count Conventions
- Tenor Arithmetic
- Date Sequence Generation
- Roll Conventions

## Development

This project uses:
- [Poetry](https://python-poetry.org/) for dependency management
- [Ruff](https://github.com/astral-sh/ruff) for linting and formatting
- [pytest](https://docs.pytest.org/) for testing
- [pre-commit](https://pre-commit.com/) for git hooks

### Setting up development environment

```bash
# Clone the repository
git clone https://github.com/reecemiao/QFTools.git
cd qftools

# Install dependencies with Poetry
poetry install

# Install pre-commit hooks
poetry run pre-commit install
```

### Running tests
```bash
poetry run pytest
```

### Code Style

The project uses Ruff for both linting and formatting with the following configurations:
- Line length: 120 characters
- Python target version: 3.13
- NumPy docstring convention
- Selected rule sets: `F`, `E`, `W`, `C90`, `I`, `D`

## License

MIT License - see the [LICENSE](LICENSE) file for details.
lintian-codeclimate 0.2.4
Codeclimate parser for lintian
License: MIT
Requires Python: >=3.8

# lintian-codeclimate

This project provides a Python-based parser for Lintian to write
CodeClimate-format reports, mainly to assist using Lintian in
Gitlab CI/CD pipelines.

## Install

```shell
python -m pip install lintian-codeclimate
```

## Usage

Just pipe the output of `lintian --info` to the `lintian_codeclimate` module.

```shell
lintian --info | python -m lintian_codeclimate
```
file-process 1.4.6
A package that does file validation and file preview.
License: MIT

Superbio.ai

Package that can validate and return preview for different files.

Currenty supported extensions:

- .h5ad
- .csv
- .tsv
- .txt
- .pdb
- .fasta

Usage:

```
pip install file_process
```

```
from file_process import preview_file
try:
    processor = FileProcessFactory.get(file_data.filename, file_data.file)
except WrongExtension as exc:
    raise CustomException from exc
processor.validate(model_metadata_file)
var_target_names, obs_target_names, obs_preview, var_preview, text_preview  = processor.get_preview()
```

where:

- file: an object of io.BytesIo or FileStorage which will be validated and previewed
- filename: name of the validated file (only it's extention will be used)
- model_metadata_file (optional parameter): file with metadata of a model that will be used for validation. If this file is provided, the code will check that this file has the same set of columns as the validated file. If this file is not provided, no validation will be applied.

The code returns a list of var targets and obs targets (columns from the validated file), var preview and obs preview and text preview.
If some is not applicable for the file, None will be returned).

How to release:

1. Make your changes
2. Change the version in setup.py
3. Merge changes into the main branch; it will be automatically released to [pypi](https://pypi.org/project/file-process/#history)