tcorpus 0.1.8

A powerful CLI-based text corpus analyser for extracting palindromes, anagrams, word frequencies, pattern matches, emails, and phone numbers from text files or direct input.

tcorpus - Text Corpus Analyser

A powerful, lightweight command-line tool for analyzing text corpora. Extract palindromes, anagrams, word frequencies, pattern matches, emails, and phone numbers from text files or direct input.

✨ Features

• 🔍 Word Analysis: Find palindromes, anagrams, and word frequencies
• 🎯 Pattern Matching: Search words using wildcard patterns and masks
• 📧 Email Extraction: Extract email addresses from text
• 📱 Phone Number Detection: Find phone numbers in various formats
• 🚫 Stopword Filtering: Filter out common words using config files or CLI options
• 📊 Multiple Output Formats: Save results as JSON or CSV
• ⚡ Zero Dependencies: Pure Python standard library, no external packages required
• 🗜️ Compressed File Support: Automatically handles .gz compressed files

📦 Installation

From PyPI (Recommended)

pip install tcorpus

From Source

git clone https://github.com/Pegasus717/Text-Corpus-Analyser.git
cd text-corpus-analyser
pip install -e .

macOS Installation

Prerequisites

1. Install Python 3.8+ (if not already installed):

   # Using Homebrew (recommended)
   brew install python3
   
   # Or download from python.org
   # Visit https://www.python.org/downloads/
   

2. Verify Python installation:

   python3 --version
   # Should show Python 3.8 or higher
   

Installation Steps

Option 1: Using pip3 (Recommended for macOS)

# Install from PyPI
pip3 install tcorpus

# Or install from source
git clone https://github.com/Pegasus717/Text-Corpus-Analyser.git
cd text-corpus-analyser
pip3 install -e .

Option 2: Using Virtual Environment (Best Practice)

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
source venv/bin/activate

# Install tcorpus
pip install tcorpus

Note: If you encounter permission errors, use pip3 install --user tcorpus to install in user space.

Verify Installation

tcorpus --help
# Or if command not found:
python3 -m tcorpus --help

🚀 Quick Start

# Get help
tcorpus --help

# Analyze a text file with all features
tcorpus all demo.txt output.json

# Use direct text input
tcorpus palindrome --text "A man a plan a canal Panama" output.json

📖 Usage

Input Options

You can provide input in two ways:

1. From a file:

   tcorpus <command> <input_file> <output_file>
   

2. Direct text (using -t or --text):

   tcorpus <command> --text "Your text here" <output_file>
   

Common Options

All commands support these filtering options:

• --stopwords <word1> <word2> ... - Additional stopwords to ignore (combined with config.ini)
• --starts-with <letter> - Keep only words starting with this letter
• --config <path> - Path to config file for stopwords (default: config.ini)
• -pw, --print-words - Print filtered results to terminal

Config File

Create a config.ini file in your working directory to define default stopwords:

[stopwords]
words = the,or,but,a,an,is,are,was,were

📋 Commands

1. Palindrome Detection

Find all palindromes (words that read the same forwards and backwards).

# From file
tcorpus palindrome demo.txt palindromes.json

# Direct text
tcorpus palindrome --text "madam level cat radar" output.json

# With filters
tcorpus palindrome demo.txt output.json --starts-with m --print-words

Output:

{
  "palindromes": ["level", "madam", "radar"]
}

---

2. Anagram Detection

Find groups of words that are anagrams of each other.

# Basic usage
tcorpus anagram demo.txt anagrams.json

# With direct text
tcorpus anagram --text "cat act tac dog god" output.json

Output:

{
  "anagrams": [
    ["act", "cat", "tac"],
    ["dog", "god"]
  ]
}

---

3. Word Frequency Analysis

Count how often each word appears in the text.

# Count all words
tcorpus freq demo.txt frequencies.json

# Count specific words
tcorpus freq demo.txt output.json --words python code program

# Output as CSV
tcorpus freq demo.txt frequencies.csv

Output (JSON):

{
  "frequencies": {
    "python": 5,
    "code": 3,
    "program": 2
  }
}

Output (CSV):

word,count
code,3
program,2
python,5

---

4. Pattern Matching (Mask)

Find words matching a specific pattern using wildcards and special syntax.

Pattern Syntax:

• * - Matches zero or more characters (wildcard)
• ? - Matches exactly one character
• word+ - Words starting with "word" (e.g., ram+ matches "ram", "ramesh", "ramadan")
• +word - Words ending with "word" (e.g., +ing matches "running", "coding")
• +word+ - Words containing "word" (e.g., +ram+ matches "program", "ramesh")

Options:

• --min-length <n> - Minimum word length
• --max-length <n> - Maximum word length
• --length <n> - Exact word length
• --contains <substring> - Word must contain this substring

Examples:

# Wildcard pattern: words starting with 's' and ending with 'e'
tcorpus mask "s*e" demo.txt output.json

# Starts with pattern
tcorpus mask "ram+" demo.txt output.json

# Ends with pattern
tcorpus mask "+ing" demo.txt output.json

# With length filters
tcorpus mask "s*e" demo.txt output.json --min-length 4 --max-length 6

Output:

{
  "mask_matches": ["sale", "safe", "same", "sane", "site", "size"]
}

---

5. Email Extraction

Extract email addresses from text.

# From file
tcorpus email demo.txt emails.json

# Direct text
tcorpus email --text "Contact us at [e-mail] or [e-mail]" output.json

Output:

{
  "emails": ["[e-mail]", "[e-mail]"]
}

---

6. Phone Number Extraction

Extract phone numbers from text in various formats.

# Basic usage (default: 10 digits minimum)
tcorpus phone demo.txt phones.json

# Custom minimum digits
tcorpus phone demo.txt output.json --digits 7

# Direct text
tcorpus phone --text "Call [phone] or 07123 456789" output.json

Output:

{
  "phone_numbers": ["[phone]", "07123 456789"]
}

---

7. All Analyses

Run all analyses at once: palindromes, anagrams, frequencies, emails, and phone numbers.

# Run all analyses
tcorpus all demo.txt complete_analysis.json

# With word frequency filter
tcorpus all demo.txt output.json --words python code

# Custom phone digit requirement
tcorpus all demo.txt output.json --digits 7

Output:

{
  "palindromes": ["level", "madam"],
  "anagrams": [["act", "cat", "tac"]],
  "frequencies": {
    "python": 5,
    "code": 3
  },
  "emails": ["[e-mail]"],
  "phone_numbers": ["[phone]"]
}

---

8. Multi Analyses (Choose Specific Combination)

Run any combination of analyses in a single command (e.g., just palindromes and anagrams, or palindromes + frequencies + emails).

tcorpus multi -o palindrome -o anagram demo.txt output.json

tcorpus multi -o palindrome -o freq demo.txt output.json --words python code

tcorpus multi -o palindrome -o mask -o phone --mask "s*e" demo.txt output.json --digits 8

Notes:

• Use -o/--ops once per analysis you want to run (e.g., -o palindrome -o anagram).
• If you include mask, provide --mask (pattern) and optional length filters (--min-length, --max-length, --length, --contains).
• If you include freq, --words lets you target specific words; omit to count all.
• If you include phone, use --digits to set the minimum digit count (default 10).
• --print-words works here too and prints only the analyses you ran.

🔧 Advanced Examples

Combining Filters

# Find palindromes starting with 'm', excluding stopwords
tcorpus palindrome demo.txt output.json \
  --starts-with m \
  --stopwords the a an \
  --print-words

Processing Compressed Files

The tool automatically handles .gz compressed files:

tcorpus all large_text.txt.gz output.json

Batch Processing

# Process multiple files (Unix/Linux/Mac)
for file in *.txt; do
  tcorpus all "$file" "${file%.txt}_analysis.json"
done

# Windows PowerShell
Get-ChildItem *.txt | ForEach-Object {
  tcorpus all $_.Name ($_.BaseName + "_analysis.json")
}

📤 Output Formats

JSON (Default)

All commands output JSON by default. The structure varies by command:

• Single analysis: {"palindromes": [...]}
• All analyses: {"palindromes": [...], "anagrams": [...], ...}

CSV (Frequency Only)

When using freq command with .csv extension, outputs CSV format suitable for spreadsheet applications.

🛠️ Requirements

• Python 3.8 or higher
• No external dependencies (uses only Python standard library)

🧪 Testing

Run the test suite:

python -m unittest discover -s tests -v

❓ Troubleshooting

Command Not Found

If tcorpus is not recognized after installation:

1. Check installation:

   pip show tcorpus
   

2. Verify PATH includes Python Scripts directory:

   python -m site --user-base
   

3. Use module execution:

   python -m tcorpus --help
   

Config File Not Found

If config.ini is missing, the tool will still work but won't use default stopwords. Create a config.ini file in your working directory:

[stopwords]
words = the,or,but,a,an,is,are

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

👥 Authors

• Raghu - [e-mail]

👨‍💼 Maintainers

• Santosh
• Raghuram

📄 License

This project is open source and available under the MIT License.

📌 Version

Current version: 0.1.8

💬 Support

For issues, questions, or contributions, please open an issue on the project repository.

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Made with ❤️ for text analysis enthusiasts