semvec/pypi-packages huggingface dataset:
custom-pipeline-stages-manager 0.1.0
A package for managing custom pipeline stages
Requires Python: >=3.6

Pipeline Staging in a Sales Management System

A Web Application intended for customers or clients from contrasting domains seeking to upskill business outcomes with the supplementary contribution of 'Pipeline Stages'. This is a demonstration intended to prioritize the the Customer - Key Priority relationship in a cloud-ready environment.

Custom Libraries for PipelineStagingLibrary:
- setuptools 69.5.1
- wheel 0.43.0
- twine 5.0.0

**setup.py:** pkg-newfinalcustom-pipeline-staging-final 0.1.0

Custom Packages for AWS S3 Facilitation:
- boto3 1.34.88
- s3transfer 0.10.1
- botocore 1.34.88

**Library**:

Hierarchy and Structure:

```bash
PipelineStagingLibrary
              -------> .git
              -------> _dist
              -------> dist
              -------> env
              -------> pipeline_staging_properties_pkg
		              ----> __init__.py
		              ----> pipeline_staging_properties.py
              -------> pkg_newfinalcustom_pipeline_staging_final.egg-info
              -------> tests
              -------> CHANGELOG.txt
              -------> LICENSE
              -------> README.md
              -------> setup.py
```

Build the library i.e. generate the distribution package:

```bash
  python3 -m pip install --upgrade setuptools wheel
```

Upload/publish the distribution package files with twine:

```bash
  python3 -m pip install --upgrade twine
```

Publish the library to PyPI:

```bash
  python3 -m twine upload --repository pypi dist/*
  twine upload dist/*
```
Install (i.e. via pip) the distribution package/library:

```bash
  python3 -m pip install --index-url https://pypi.org/simple --no-deps pkg-newfinalcustom-pipeline-staging-final==0.1.0
```
Information about the installed library:

```bash
  pip list
  pip show pkg-newfinalcustom-pipeline-staging-final
```

## Configuration Files

- setup.py
Metadata of Custom Library :
```bash
 pkg-newfinalcustom-pipeline-staging-final 
 version=0.1.0
```
graphlight 0.0.2
A lightweight graph database library
Requires Python: >=3.6

# GraphLight: A Lightweight, Distributed Graph Database

GraphLight is an innovative graph database designed for high performance and scalability, leveraging the power of Python for ease of use and flexibility. Built with a focus on in-memory data storage akin to Redis and incorporating the robust querying capabilities of OpenCypher, GraphLight aims to provide developers with a fast, efficient, and intuitive tool for managing graph-based data.

## Key Features

* In-Memory Data Storage: Optimized for speed, GraphLight stores your graph data entirely in RAM, ensuring rapid access and manipulation of data points.

* OpenCypher Query Support: Utilize the power of the OpenCypher query language to interact with your graphs. From simple lookups to complex traversals, GraphLight brings you the flexibility of graph querying right at your fingertips.

* Distributed Computing: GraphLight is designed from the ground up to support distributed operations. With its secure peer-to-peer (P2P) networking capabilities, it allows for clustering of data across multiple compute nodes, enhancing both the scalability and resilience of your database.

* Multi-threaded Query Processing: To ensure maximum efficiency, GraphLight employs multi-threaded processing for handling queries, allowing for concurrent execution and reduced response times.

* Easy Integration: As a Python-based solution, GraphLight integrates seamlessly into your existing Python ecosystem, enabling straightforward implementation and interaction within your projects.

## Getting Started
To get started with GraphLight, simply install the package via pip:

```bash
pip install graphlight
```

For detailed documentation on installation, configuration, and usage, please refer to our official documentation (Link to Documentation - ToDo).

## Example Usage
Here's a quick snippet to give you a taste of what working with GraphLight looks like:

```python
from graphlight import Graph

# Initialize your graph
my_graph = Graph()

# Add nodes and edges
my_graph.add_node("Alice")
my_graph.add_node("Bob")
my_graph.add_edge("Alice", "Bob", "knows")

# Query your graph
results = my_graph.query("MATCH (person)-[relation]->(friend) RETURN person, relation, friend")
print(results)
```

## Contributing
We welcome contributions from the community! Whether it's adding new features, improving documentation, or reporting bugs, your help makes GraphLight better for everyone. Check out our contributing guidelines for more information on how to get involved.