Enterprise Coding & Development in the Real World

Explain what separates enterprise code from a personal project — and why the difference is mostly about the next person, not the machine

Walk through a real first day: clone the repo, open VS Code, pick the interpreter, activate the environment, install packages, run the app

Follow one change from ticket to production — branch, pull request, review, CI, staging, release, and the monitoring that closes the loop

Name the core roles on an enterprise development team and know when each one matters in your sprint

Install and manage Python versions, and explain what the interpreter actually does with your source file

Create and share virtual environments, choose between venv and Conda, and defend the choice

Manage dependencies with pip and requirements files, and apply semantic versioning and pinning correctly

Build a reproducible environment a new developer can stand up from git clone to passing tests in five minutes

Navigate VS Code like a professional: terminal, explorer, extensions, debugger, interpreter selector, and Git panel

Configure extensions and kernels, and diagnose the single most misunderstood error in Python — the kernel pointing at the wrong environment

Work confidently at the command line, and read any command's flags and arguments without guessing

Use Jupyter notebooks properly, and explain why notebooks should never become production code

Step through code with a real debugger — breakpoints, the variables panel, the call stack, and a watch expression

Read an enterprise repository folder by folder, and place a new file correctly on the first try

Explain the src layout, and recognise when a utils module has become a dumping ground

Keep data and documentation out of the places they cause damage, and recover when something is already committed

Read and choose between config.py, YAML, JSON, TOML and INI for a given settings file

Explain how environment variables let identical code behave differently across development, testing and production

Tell a secret from ordinary configuration, and respond correctly to a leaked credential

Explain why production secrets live in a secret manager, and tell Azure Key Vault, AWS Secrets Manager and GitHub Secrets apart

Use git clone, fetch, pull, commit, push and merge precisely — and stop confusing fetch with pull

Create and merge branches, follow a feature branch workflow, and resolve a real merge conflict

Write a pull request worth reviewing, and know when to approve, request changes, or block one

Tag a release, apply semantic versioning, and name the Git habits that keep a repo debuggable a year later

Name the environments a change passes through from Dev to Production, and what gates each one

Explain build-once-promote-many, and why rebuilding between stages undoes every test that came before

Choose between rolling back and fixing forward, and explain why a schema migration makes that harder

Explain CI/CD precisely, including the real difference between continuous delivery and continuous deployment

Read a failing pipeline log and find the actual error rather than the last line

Tell GitHub Actions, Azure DevOps and Jenkins apart, and know what each is actually good at

Explain how data and analytics teams work, and why analytics code fails silently where application code fails loudly

Read int, float, decimal, date, timestamp, array, struct, map and null correctly, and know why float is wrong for money

Handle dates, time zones and nulls without producing off-by-one-day errors or broken aggregates

Read a nested JSON payload, plan how to flatten it, and handle a source that changes shape without warning

Write a README, comments and docstrings that actually help the next person, and know when a decision belongs in an ADR

Use Python's logging module instead of print(), and handle exceptions without hiding them

Configure Black, Ruff or Flake8 for a team, and wire quality checks into pre-commit and CI

Explain what a test suite really buys a team, and read a coverage number correctly

Write pytest tests with fixtures, parametrisation, and mocking at the right boundary

Tell unit, integration, regression, smoke and end-to-end tests apart, and read a failing test's output to find the bug

Read a REST endpoint and predict what it does from the method and path alone

Diagnose an API problem from its status code, and tell API keys, bearer tokens and OAuth flows apart

Call an API from Python with proper timeouts, retries with backoff, and pagination

Map a need to the right cloud service category, and translate service names between Azure, AWS and GCP

Read a Dockerfile line by line, and explain why instruction order decides how long your builds take

Distinguish monitoring from observability, and write a structured log line that is still useful six months later

Walk a change through an entire enterprise organization's tooling, start to finish, without needing anyone to explain it