semvec/pypi-packages huggingface dataset:
xdb-location 0.3.0
a geographic information database
License: MIT
Requires Python: >=3.10

# Xdb_Location
地理信息数据库

* PyPI package: https://pypi.org/project/xdb_location/
* Github: https://github.com/gunhe/xdb_location
* Free software: MIT License

## 使用
```bash
from xdb_location.xdb_location import searchWithContent
target_ip_location = searchWithContent(target_ip="1.15.241.228")
print(target_ip_location)
```



## 更新库
```bash
uv run xdb_location  main  ./src/xdb_location/data/ip.test.txt   ./ip2region.test.xdb
```
## Features

* ip2region xdb python 生成实现
* ip2region xdb python 生成实现

## Credits

[uv](https://docs.astral.sh/uv/)

[Cookiecutter](https://github.com/audreyfeldroy/cookiecutter)

[audreyfeldroy/cookiecutter-pypackage](https://github.com/audreyfeldroy/cookiecutter-pypackage)

[https://github.com/lionsoul2014/ip2region](https://github.com/lionsoul2014/ip2region)

# xdb_location
hangman-terminal 1.0.1
Hangman in terminal
License: MIT

# Hangman-Terminal

[![PyPI version](https://badge.fury.io/py/hangman-terminal.svg)](https://badge.fury.io/py/hangman-terminal)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A classic game of Hangman that you can play right in your terminal! Features fun ASCII art animations and a built-in word list for a simple, engaging experience.

## Gameplay Demo

![Gameplay GIF](https://raw.githubusercontent.com/menonkrishna57/Hangman-Game-in-Python/refs/heads/main/media/usage.gif)





## Features

* **Classic Hangman Gameplay:** Guess letters to solve the hidden word before you run out of attempts.
* **ASCII Art Animations:** Watch the hangman being drawn with each incorrect guess, all rendered in your terminal.
* **Built-in Word List:** Comes with a predefined set of words, so you can start playing immediately.
* **Lightweight & Simple:** No external dependencies needed. Just install and play!

## Installation
You can install it easily using `pip`:

```bash
pip install hangman-terminal
```

## Usage
There are two main ways to run the game:

### 1. From the Command Line:
After installation, you can start the game by simply typing this command in your terminal:

```Bash
hangman-terminal
```
### 2. As a Python Module:
You can also import and run the game from within your own Python script.

```Python

import hangman_terminal as
# This will start the game
ht.main()
```
## Contributing
Contributions, issues, and feature requests are welcome!  Feel free to check the [issues](https://github.com/menonkrishna57/Hangman-Game-in-Python/issues) page.
omnigrad 0.2.3
A scalar-valued autograd engine, consider this like an extension of micrograd with support of more complex functions
License: MIT
Requires Python: >=3.6

# omnidiff
This project is a lightweight Python library that implements reverse-mode automatic differentiation. It is designed as a learning-oriented extension of Andrej Karpathyâ€™s Micrograd, providing support for a broader range of mathematical operations and functions.

ref: https://github.com/karpathy/micrograd

Similar to Micrograd, this library operates exclusively on scalar values, enabling a clear and intuitive understanding of the underlying mechanics of automatic differentiation.

In addition to computing gradients, you can use this library alone to construct and train neural networks, with a particular focus on binary classification tasks.
qtrade-lib 0.1.3
A Python library for backtesting trading strategies and applying reinforcement learning to trading.
License: MIT
Requires Python: <4.0,>=3.10
Keywords: trading, backtesting, reinforcement learning

[![CI Status](https://github.com/gguan/qtrade/actions/workflows/ci.yml/badge.svg)](https://github.com/gguan/qtrade/actions)
[![Python](https://img.shields.io/pypi/pyversions/qtrade-lib.svg)](https://badge.fury.io/py/qtrade-lib)
[![PyPI version](https://badge.fury.io/py/qtrade-lib.svg)](https://badge.fury.io/py/qtrade-lib)
![Coverage](https://img.shields.io/badge/coverage-87%25-green)
[![codestyle](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

# QTrade

QTrade is a simple, modular, and highly customizable trading interface capable of handling backtesting, reinforcement learning tasks.

## Features

- Backtesting engine
- Gym Trading environment simulation

## Installation

QTrade can be installed with [pip](https://pip.pypa.io):

```bash
$ pip install qtrade-lib
```

Alternatively, you can obtain the latest source code from [GitHub](https://github.com/gguan/qtrade):

```bash
$ git clone https://github.com/gguan/qtrade.git
$ cd qtrade
$ pip install .
```

### Run Example

To run the example code from repository:

```bash
$ pip install -r examples/requirements.txt
$ python examples/simple_strategy.py
```

### Requirements

- Python >= 3.8
- Dependencies listed in requirements.txt


### Usage

The [User Guide](guide/getting_started.md) is the place to learn how to use the library and accomplish common tasks. For more advanced customization, refer to the [Customization Guide](customisation/index.md).

The [Reference Documentation](reference/index.md) provides API-level documentation.


## References

This project is inspired by following projects.

- https://github.com/tensortrade-org/tensortrade
- https://github.com/kernc/backtesting.py


## License

This project is licensed under the MIT License - see the LICENSE file for details.