Data Scientist Toolkit
Data scientists spend their days building models, cleaning data, and communicating results. But between the notebooks and the presentations, there is a steady stream of micro-tasks: formatting JSON API responses, testing regex patterns for text extraction, converting timestamps, and comparing output files. These free, browser-based tools handle that work instantly so you can focus on the analysis.
JSON Formatter & Validator
Pretty-print and validate JSON from REST APIs, data pipeline outputs, and configuration files. The formatted view helps you understand nested data structures before parsing them in pandas or writing schema definitions.
RegExp Tester
Build regex patterns for text extraction, data cleaning, and log parsing. Test patterns against sample data with live highlighting before deploying them in Python re calls or pandas str.extract().
Timestamp Converter
Convert Unix epoch timestamps to human-readable dates and back. Essential when working with time-series data, correlating events from different sources, or debugging timezone issues in datasets.
JSON to YAML Converter
Convert JSON configuration to YAML for ML pipeline definitions (Kubeflow, MLflow), Docker Compose files, and experiment tracking configurations.
Base64 Encoder / Decoder
Decode Base64-encoded data from APIs, encode binary model artifacts for transmission, or inspect encoded values in notebook environments without writing utility functions.
Code Diff Tool
Compare two versions of a notebook script, model configuration, or data pipeline definition side by side. Essential for tracking changes between experiment runs.
Character Counter
Count characters, words, and tokens in text data for NLP preprocessing. Verify text length constraints for model inputs, API character limits, and database field requirements.
Duplicate Line Remover
Deduplicate lists of feature names, column headers, or category labels. Clean up exported data before importing into analysis tools or feature stores.
MD5 / Hash Generator
Generate SHA-256 hashes for dataset versioning, model artifact tracking, and ensuring data integrity across pipeline stages. Create reproducible identifiers for experiment tracking.
URL Encoder / Decoder
Encode query parameters for data API calls or decode percent-encoded URLs from web-scraped datasets. Prevents encoding issues in data collection pipelines.
Color Converter
Convert colors between HEX, RGB, and HSL for custom matplotlib, seaborn, or Plotly visualizations. Match brand colors or design specifications without opening a separate tool.
Code to Image
Turn Python code snippets into clean, shareable images for presentations, research papers, and blog posts. Syntax-highlighted code images look better than screenshots in slides.