AI Time Estimates for Coding Tasks

Building a Stripe Checkout integration with subscription billing for a SaaS product, including webhook event handling and the Stripe customer portal. This is a moderately complex, well-scoped backend/fullstack coding task — Stripe's documentation is excellent, but the surface area (checkout sessions, subscription lifecycle events, webhook signature verification, portal configuration) accumulates quickly for non-experts, and edge cases around subscription state transitions are where most implementations fall short.

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.).

Take a messy, inconsistently formatted business expense spreadsheet and redesign it as a normalized relational database schema with proper tables, keys, and relationships.

Build a Python web scraper that monitors competitor product prices and automatically updates a local database on a 6-hour schedule

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.

Diagnose intermittent 500 errors on a WordPress site by accessing the server and inspecting error logs, PHP logs, and server configuration.

Debug and refactor a slow Python data processing script, adding type hints and improving efficiency

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.

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.

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

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.

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.

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

Write Python code to parse CSV files, clean missing data, and generate statistical summaries with visualizations

Build a Python web scraper that collects real estate listings from multiple websites and stores the aggregated, structured data in a database.

Debug and fix a Python script that processes image metadata and returns null values inconsistently

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.

Build a Python ETL script to extract customer transaction data from PostgreSQL, apply transformations, and load into a data warehouse

Build a Python script that calls a weather API (e.g. OpenWeatherMap), retrieves forecast data for 5 major cities, and generates readable weekly summary reports from that data.

Debug a Python function that sorts a list of dictionaries by multiple nested keys incorrectly. Involves reading existing code, identifying the sorting logic bug (likely key extraction, nested access, or comparator ordering), and writing a verified fix.