📚 Dictionary Serialization in Python 🥣

🍪🥠 Optimizing Data Structures 🐀🐍

Notebooks using jsoncons and other libraries to manipulate data structures in Python

Getting Started with Interactive Jupyter Notebooks 📖

Welcome! This repository provides a comprehensive guide and practical examples for understanding and using serializable dictionaries in Python. Dictionaries are fundamental, and knowing how to effectively serialize (save/transmit) and deserialize (load/receive) them is a key skill for any Python developer.

This guide covers everything from basic concepts to advanced techniques, performance considerations, security implications, and real-world applications.

✨ Features

• Clear Explanations: Understand what serialization is and why it's essential.
• Multiple Formats: Explore and compare popular formats:
  • JSON: The web standard – lightweight and human-readable.
  • Pickle: Python's native format – powerful but with security caveats.
  • YAML: Highly readable, great for configuration.
  • MessagePack: Fast and compact binary format.
  • HDF5: High-performance format for large numerical datasets (often used with NumPy arrays within dictionaries).
• Advanced Techniques: Learn how to handle custom objects, circular references, optimize performance, and manage large data streams.
• Practical Examples: See serialization in action for:
  • Configuration Management (yaml)
  • API Data Exchange (json, requests)
  • Caching (pickle)
  • Data Persistence (Simple Inventory System using json)
• Security Focus: Understand the critical security risks of deserialization (especially pickle) and the importance of input validation (jsonschema).
• Best Practices: Actionable advice on choosing formats, versioning data, handling errors, and testing your code.
• Jupyter Notebooks: Interactive learning experience through three detailed notebooks:
  1. 1_Introduction_to_Serialization.ipynb: Basics and common formats.
  2. 2_Advanced_Serialization_Performance.ipynb: Custom objects, performance, HDF5 comparison.
  3. 3_Practical_Applications_Best_Practices.ipynb: Real-world use, security, best practices.
• The jsoncons Package: PyPi Package JSON Console utility | Simple CLI for JSON handling (see details below).

🚀 Getting Started

1. Clone the repository:

   git clone https://github.com/fapulito/jsoncons-nb.git
   cd jsoncons-nb

2. Set up a virtual environment (Recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:
   • For core notebooks (JSON, Pickle): No external dependencies needed beyond Python 3.
   • For advanced examples:

     pip install -r requirements.txt

     (You'll need to create a requirements.txt file listing pyyaml, msgpack-python, requests, jsonschema, h5py, numpy)
4. Launch Jupyter:

   jupyter notebook
   # or
   jupyter lab

5. Open and run the notebooks (.ipynb files) in order. Happy Serializing! 🎉