semvec/pypi-packages huggingface dataset:
gigagraph-sdk 0.1.29
SDK for interacting with LangGraph API
License: MIT
Requires Python: <4.0.0,>=3.9.0

# LangGraph Python SDK

This repository contains the Python SDK for interacting with the LangGraph Cloud REST API.

## Quick Start

To get started with the Python SDK, [install the package](https://pypi.org/project/langgraph-sdk/)

```bash
pip install -U langgraph-sdk
```

You will need a running LangGraph API server. If you're running a server locally using `langgraph-cli`, SDK will automatically point at `http://localhost:8123`, otherwise
you would need to specify the server URL when creating a client.

```python
from langgraph_sdk import get_client

# If you're using a remote server, initialize the client with `get_client(url=REMOTE_URL)`
client = get_client()

# List all assistants
assistants = await client.assistants.search()

# We auto-create an assistant for each graph you register in config.
agent = assistants[0]

# Start a new thread
thread = await client.threads.create()

# Start a streaming run
input = {"messages": [{"role": "human", "content": "what's the weather in la"}]}
async for chunk in client.runs.stream(thread['thread_id'], agent['assistant_id'], input=input):
    print(chunk)
```
algolearn 0.1.0
Custom implementation of standard library to help learn Data Structures, Algorithms and Leetcode
License: MIT

# algolearn - Custom Standard Library

Custom implementation of standard library to help learn Data Structures, Algorithms and Leetcode.

## Core Features

- Implement Array
- Implement LinkedList
- Implement HashMap
- Implement Heap
- Implement Stack
- Implement Tree

## Future Features

- Use a build tool instead of running setup.py directly because this method is deprecated

## Phases

## Milestones

## User stories

## System requirements

For manual publishing to PyPi: pip, wheel, twine, setuptools

## Installation

```bash
pip3 install algolearn
```

## Usage

```bash
python3 main.py
```

## Testing

```bash
python3 -m unittest -v tests/multiplication_tests.py
```

## Manually publishing to PyPi

```bash
pip install twine wheel setuptools
python setup.py sdist bdist_wheel
twine check dist/*
twine upload --repository-url https://test.pypi.org/legacy/ dist/*
twine upload dist/*
```

## Contributing

## License
sqlpickle 0.1.3
Simple KV Storage and memoization based on sqlite
License: MIT
Requires Python: <4.0,>=3.12

# SQL Pickle

SQL Pickle is a simple key-value store that uses SQLite to store pickled objects.

```python
from sqlpickle import KeyValueStore
store = KeyValueStore('test.db')

store['test'] = 1
print(store['test']) 
# 1

store['very_complex_object'] = {'a': 1, 'b': 2}
```

# Memoization

```python
from sqlpickle import memoize, KeyValueStore

@memoize(KeyValueStore('test.db'))
def expensive_function(x):
    return x**2

expensive_function(2) # 4
expensive_function(2) # 4
```

# Other features

```python
'key' in store # True
store.keys() # ['key1', 'key2']
store.items() # [('key1', 1), ('key2', 2)]
store.get('key1') # 1
store.get('key2') # 2
store.get('key3') # KeyError
len(store) # 2
store.random_keys(2) # ['key1', 'key2']
```