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Fastmarkets API Data Pipeline

A Python-based ETL pipeline that extracts commodity pricing data from the Fastmarkets API, transforms it into structured format, and generates analytical visualizations.

Project Overview

This project demonstrates a complete data engineering workflow:

  • Authenticates with the Fastmarkets API using service credentials
  • Extracts instrument metadata and historical price data
  • Transforms nested JSON responses into structured tables
  • Exports cleaned data to CSV format
  • Generates price fluctuation charts for analysis

Features

  • Secure API authentication with bearer tokens
  • Data extraction from multiple endpoints
  • JSON to structured data transformation using pandas
  • Data type validation and cleaning
  • Automated CSV export with proper file handling
  • Price trend visualization with matplotlib
  • Comprehensive error handling and logging

Technologies Used

  • Python 3.x
  • Requests (API calls)
  • Pandas (Data transformation)
  • Matplotlib (Data visualization)
  • OS (File system operations)

About

This python file uses the requests, pandas and matplotlib libraries to connect to an API and create a .csv file with historical physical prices data and a .png file with the price fluctuations visualized as a chart.

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