You will get a Python data cleaning and API automation script
Project details
I will build a practical Python script or workflow to collect, clean, validate, and export your data from APIs, CSV files, spreadsheets, or simple web sources. The deliverable includes runnable code, sample output, and clear README notes so you can review the logic and reuse the workflow. I focus on clean assumptions, reproducible outputs, and straightforward communication rather than black-box automation.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$80
|
Standard
$180
|
Advanced
$350
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Pages Mined/Scraped | 100 | 500 | 1000 |
Number of Sources Mined/Scraped | 1 | 2 | 3 |
Number of Revisions | 1 | 2 | 2 |
About Martin
Python Market Data & Backtesting Automation Developer
Beijing, China - 3:40 am local time
My work focuses on turning messy API or market data into clean, reproducible datasets and scripts that clients can actually run, audit, and extend.
I can help with:
- Python API integrations and data collection scripts
- Crypto, stock, odds, and prediction-market data workflows
- Polymarket / market-window data normalization
- CSV, JSONL, Parquet, SQLite, and PostgreSQL pipelines
- Backtesting notebooks and research scripts
- Market data validation, timestamp alignment, and missing-window checks
- Streamlit dashboards and data monitoring tools
- Alerting workflows through Telegram, Discord, Twilio, or similar tools
One example project is a sanitized BTC 5-minute prediction-market research system covering market data normalization, read-only backtesting, parameter sweeps, data-quality checks, and research workflow design.
I prefer clear, practical deliverables: working code, sample output, README instructions, and explicit assumptions. For trading or market-related work, I do not promise profits. I build reliable data and research tooling.
Steps for completing your project
After purchasing the project, send requirements so Martin can start the project.
Delivery time starts when Martin receives requirements from you.
Martin works on your project following the steps below.
Revisions may occur after the delivery date.
Confirm scope and sample data
I review your source details, sample files, expected output, and validation rules before implementation.
Build and test the workflow
I develop the Python script or notebook, run it on sample data, and check the output for consistency.