AI Time Estimates for Coding Tasks

Build a Python web scraper that extracts product pricing and review data from 5 competitor e-commerce websites, handling varied page structures, potential anti-scraping measures, and outputting structured data.

Build a Python web scraper targeting 10 e-commerce sites to extract competitor pricing data and persist results to a database. Requires per-site selector engineering, anti-bot mitigation, data modeling, and ongoing maintenance as sites change.

Containerise an existing Python web application using a multi-stage Dockerfile to separate build and runtime stages, and a docker-compose.yml for local development with volume mounts, environment variables, and service orchestration.

Configure a GitHub Actions workflow that automatically runs tests, builds the Node.js project, and deploys it on every push to the main branch, including secrets management and deployment target integration.

Write Python code that parses JSON API responses, loads data into PostgreSQL, and includes error handling and logging.

Build a Python web scraper for Zillow real estate listings that extracts, normalizes data, and computes price-per-square-foot statistics grouped by neighborhood

Debug and refactor a Python/pandas CSV processing script: identify performance bottlenecks, fix bugs, and optimize for speed and maintainability.

Writing PostgreSQL SQL queries to calculate user retention metrics and build cohort analysis tables, covering concepts such as date-truncated cohort assignment, week-over-week or month-over-month retention rates, and the self-joins or window functions needed to track user activity across time periods.

Write Python code to ingest messy CSV files of customer transaction data, remove duplicate rows, and handle missing values using appropriate strategies (drop, fill, interpolate, etc.).

Write a Python script that reads one or more CSV files, normalizes date columns to a consistent format, and flags rows that share the same email address or phone number as potential duplicates.

Write Python code to scrape real estate listings from a target website, parse structured fields (price, location, features), and export results to a CSV file. Complexity varies significantly depending on whether the site uses server-side HTML vs. JavaScript rendering, paginated results, and anti-bot protections.