A pure Python project that parses unstructured Instagram profile text and converts it into structured JSON data.
Social media data is often available in raw, unstructured text formats that are not directly suitable for analysis.
InstaParseX demonstrates how core Python only can be used to process such data without relying on external libraries.
The project focuses on:
- Reading raw Instagram profile text from files
- Parsing and cleaning profile information
- Converting unstructured text into structured JSON
- Validating logic using both initial and final datasets
- Raw, unprocessed Instagram profile data in text format
- Used to test the initial parsing logic
- Refined version of the raw text data
- Used for final parsing and accurate extraction
- Structured output generated after parsing
- Contains:
- Username
- Followers
- Following
- Posts
- Category
- Notebook for testing parsing logic on initial data
- Notebook containing finalized parsing logic and results
- 🧩 Parses unstructured Instagram profile text
- 🐍 Uses only core Python string operations
- 🔢 Converts follower counts (K / M) into numeric values
- 📦 Stores output in JSON format
- ✅ Tested on multiple datasets
- 🐍 Python (Core)
- ✂️ String Manipulation
- 📂 File Handling
- 📋 Lists and Dictionaries
- 🗂️ JSON (Built-in)
❌ No external libraries
❌ No regex
❌ No frameworks
- Beginner-friendly data processing project
- Portfolio project for Python fundamentals
- Practice for parsing unstructured data
- Foundation for future data analytics or NLP projects
- Strong understanding of text parsing fundamentals
- Experience handling unstructured data
- Improved Python logic and problem-solving skills
- Real-world data processing practice
- 📈 Add data visualizations
- 📊 Calculate engagement metrics
- 🌐 Extend parsing to other platforms
- 🤖 Automate data input
InstaParseX – Unstructured to Structured
-Anmol Patel