semvec/pypi-packages huggingface dataset:
rapid-redis 0.1.1
A lightweight in-memory cache inspired by Redis (educational)
License: MIT
Requires Python: >=3.7

# Rapid Redis

**Rapid Redis** is a lightweight, educational in-memory cache library inspired by Redis.
It is built entirely in Python for learning purposes and designed to be simple, minimal, and easy to extend.

---

## Overview

Rapid Redis provides a basic Redis-like interface for storing and managing cached data using Python dictionaries under the hood.
It currently supports five common data structures and exposes simple, intuitive methods for cache operations.

---

## Features

* In-memory key-value cache using Python dictionaries
* Basic operations: `set`, `get`, `delete`, `exists`, and `flush`
* Supports multiple data structures:

  * Strings
  * Lists
  * Sets
  * Hashes
  * Sorted Sets
* Easy to use and lightweight â€” ideal for understanding Redis fundamentals

---

## Installation

You can install Rapid Redis locally using:

```bash
pip install -e .
```

(Ensure you run this from the project root directory where `setup.py` is located.)

---

## Usage

```python
from rapid_redis import RapidCache
from rapid_redis.datastructures import strings, lists, sets, hashes, sortedsets

cache = RapidCache()

# String operations
cache.set("name", "Atharsh")
print(cache.get("name"))  # Output: Atharsh

# List operations
lists.lpush(cache, "mylist", 1, 2, 3)
print(cache.get("mylist"))  # Output: [3, 2, 1]

# Set operations
sets.sadd(cache, "myset", "a", "b", "c")
print(sets.smembers(cache, "myset"))  # Output: {'a', 'b', 'c'}

# Hash operations
hashes.hset(cache, "user:1", "name", "Atharsh")
print(hashes.hget(cache, "user:1", "name"))  # Output: Atharsh

# Sorted set operations
sortedsets.zadd(cache, "scores", 10, "Alice")
sortedsets.zadd(cache, "scores", 5, "Bob")
print(sortedsets.zrange(cache, "scores", 0, -1))  # Output: ['Bob', 'Alice']
```

---

## Roadmap

Planned features for upcoming releases include:

* TTL (Time-to-Live) support for expiring keys
* Persistent cache storage (saving data to disk)
* Thread-safe operations
* Command-line interface for quick cache access
* Optional lightweight server mode for experimentation
* Concurrency for multiple user handling

---

## Contributing

Rapid Redis is an open project â€” contributions are welcome.
If youâ€™d like to improve functionality, add features, or clean up code, feel free to fork the repository and open a pull request.

---

## License

This project is released under the MIT License.
hello-uv-tkerby 0.1.0
A tiny demo package
License: MIT
Requires Python: >=3.13

# hello-uv-tkerby2

A tiny demo package for teaching Python packaging concepts.

## Description

This package demonstrates the basics of creating a Python package with:
- Basic functions (`add_one`)
- Functions with dependencies (`calculate_mean` using numpy)
- Proper project structure with tests
- Modern packaging with `uv`

## Installation

```bash
pip install hello-uv-tkerby2
```

## Usage

```python
from hello_uv_tkerby2 import add_one, calculate_mean

# Add one to a number
result = add_one(5)
print(result)  # Output: 6

# Calculate mean of a list
mean = calculate_mean([1, 2, 3, 4, 5])
print(mean)  # Output: 3.0
```

## Features

- Simple arithmetic operations
- Statistical calculations using numpy
- Well-tested with pytest
- Type hints and documentation

## Dependencies

- Python >= 3.13
- numpy >= 1.26.0
- pandas >= 2.3.3

## License

MIT
spotipy-anon 1.5.7
An extension to Spotipy for anonymous access to the Spotify Web API
License: MIT

# SpotipyAnon

##### Anonymous access to the Spotify API


## Installation

```bash
pip install spotipy-anon
```

alternatively, for Windows users 

```bash
py -m pip install spotipy-anon
```

or upgrade

```bash
pip install spotipy-anon --upgrade
```


## Quick Start

To get started, install spotipy with spotipy-anon to create a script like this:

```python
import spotipy
from spotipy_anon import SpotifyAnon

sp = spotipy.Spotify(auth_manager=SpotifyAnon())

results = sp.search(q='weezer', limit=20)
for idx, track in enumerate(results['tracks']['items']):
    print(idx, track['name'])
```


## Reporting Issues

If you have suggestions, bugs or other issues specific to this library,
file them [here](https://github.com/dieser-niko/spotipy-anon/issues).
Or just send a pull request.



## Disclaimer

Yes, this README is heavily inspired by the [spotipy](https://github.com/spotipy-dev/spotipy) library, as I want to create a similar experience when working with this extension module.