Text Analysis Python

Overview

• A modular Python tool for character-level text analysis, capable of computing counts of letters, digits, spaces, and symbols.
• Generates a structured summary for each input string and outputs a detailed list of characters. Built to be easily integrated into text preprocessing, log analysis, and cybersecurity pipelines.

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Problem Statement

• Raw text data is often unstructured, making automated analysis challenging.
• Understanding the composition of text—letters, numbers, spaces, and symbols is a fundamental skill in cybersecurity, data validation, and text analytics.
• This project provides a reusable, precise solution for extracting this information efficiently.

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Approach

• Accepts input as sentences or text files.
• Iterates over each character, classifying it into letters, digits, spaces, or symbols.
• Compiles counts and produces a structured dictionary output, making it ready for further processing or visualization.
• Designed with modularity in mind, allowing integration with larger Python pipelines or analytical workflows.

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Installation & Usage.

# 1. Clone the repository:
   git clone https://github.com/SecEngineerX/text-analysis-python.git

# 2. Navigate to the project folder:
   cd text-analysis-python

# 3. Run the analyzer script:
   python3 text_analyzer.py

# 4. Replace sample_data.txt or provide your own text input to analyze.

Sample Output

• Sentence: I went to school today!
• Letters: 18
• Digits: 0
• Spaces: 4
• Symbols: 1
• Characters List:

['I', 'w', 'e', 'n', 't', 't', 'o', 's', 'c', 'h', 'o', 'o', 'l', 't', 'o', 'd', 'a', 'y']

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