I have a rule: if a Python script needs more than requests, it better have a good reason.
Here are 3 tools I built that follow this philosophy. They solve real problems with zero or minimal dependencies.
1. CSV Cleaner — Fix Data Files
Dependencies: None (stdlib only)
python csv_cleaner.py messy_export.csv -o clean.csv
What it does:
- Auto-detects file encoding (UTF-8, Latin-1, Shift-JIS)
- Normalizes 10+ null variants (NULL, N/A, None, nan, -)
- Standardizes column names to snake_case
- Removes duplicate rows
- Normalizes dates to ISO 8601
- Detects outliers via IQR
Why zero dependencies? Because data cleaning is the first step of every project. You should not need to install pandas just to fix a CSV.
2. Polymarket Scanner — Find Market Mispricings
Dependencies: requests only
pip install requests
python polymarket_scanner.py
Scans 10,000+ prediction markets for logical contradictions. If "Team A wins" + "Team B wins" + "Team C wins" adds up to 130%, something is mispriced.
Uses the public Polymarket Gamma API. No authentication needed.
3. PromptLab — Test LLM Prompts
Dependencies: requests, pyyaml
pip install requests pyyaml
python promptlab.py "Summarize: {{text}}" --var text="Your content"
Compare prompt variations side-by-side with real metrics: response time, token count, estimated cost. Includes 15 ready-to-use templates.
Why Zero Dependencies Matters
-
No version conflicts — No
pip installfailures on production servers - No security surface — Fewer packages = fewer CVEs
- Portable — Copy the file, run it anywhere with Python 3.10+
- Fast startup — No import chain of 50 packages
The Python standard library is incredibly powerful. csv, json, re, datetime, statistics, argparse, dataclasses — these handle 90% of data processing needs.
The Full Catalog
All tools are MIT licensed and free on GitHub:
| Tool | What It Does | Dependencies |
|---|---|---|
| CSV Cleaner | Fix messy CSV files | None |
| Polymarket Scanner | Find market mispricings | requests |
| PromptLab | Test LLM prompts | requests, pyyaml |
Pro versions with advanced features available at vesperfinch.gumroad.com.
What is the most useful zero-dependency Python tool you have found?
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