semvec/pypi-packages huggingface dataset:
pyinmem 1
Python in-memory database
Requires Python: >=3.11,<4.0

# PyInMemStore

PyInMemStore is a lightweight, in-memory data store written in Python. It provides a simple way to store and manipulate data structures such as strings, lists, sets, and sorted sets. The store offers thread-safe operations and supports key expiry, similar to Redis.

## Features

- Basic data types: Strings, Lists, Sets, and Sorted Sets.
- Thread-safe operations.
- Key expiry functionality.
- Dynamic method dispatching based on data type.
- Easy extensibility for additional data types and operations.

## Data Types and Operations

### String

- `set(key, value, ttl=None)`: Set a string value under a key. Optionally, specify a Time-To-Live (TTL) in seconds.
- `get(key)`: Retrieve the string value for a given key.

### List

- `lpush(key, value)`: Push a value to the beginning of a list at a given key.
- `rpop(key)`: Pop a value from the end of a list at a given key.
- `llen(key)`: Get the length of the list at a given key.

### Set

- `sadd(key, *values)`: Add one or more values to a set at a given key.
- `srem(key, *values)`: Remove one or more values from a set at a given key.
- `smembers(key)`: Get all the members of the set at a given key.
- `sis_member(key, value)`: Check if a value is a member of the set at a given key.

### Sorted Set

- `zadd(key, scores)`: Add one or more member-score pairs to a sorted set at a given key.
- `zrange(key, start, stop)`: Get a range of members from a sorted set at a given key, sorted by score.
- `zscore(key, member)`: Get the score of a member in a sorted set at a given key.

## Usage

```python
from pyinmemstore import PyInMemStore

store = PyInMemStore(save_data=True)


store.set('hello', 'world')
print(store.get('hello'))


store.lpush('mylist', 'hello')
store.lpush('mylist', 'world')
print(store.rpop('mylist'))


store.sadd('myset', 'hello', 'world')
print(store.smembers('myset'))


store.zadd('my_sorted_set', {'Alice': 100, 'Bob': 90})
print(store.zrange('my_sorted_set', 0, -1))
print(store.zscore('my_sorted_set', 'Alice'))
jcopml 1.2.7
J.COp ML is a machine Learning package to complement scikit-learn workflow
Requires Python: >=3.6.6
Keywords: machine learning ml jcop indonesia

# J.COp ML
J.COp ML is a machine Learning package to complement scikit-learn workflow. It includes helper functions for visualization, tuning, pipeline, and feature importance.

The project started in July 2018 as a tool to teach machine learning for beginner, but the serious development began in March 2019 together with the initiation of the LuWiji project. Both LuWiji and J.COp ML is developed by Wira D. K. Putra as complementary for his machine learning curriculum for young machine learning enthusiast.

# User Installation Guide
```
pip install jcopml
```