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Portal | Level: L0: Entry | Topics: Python Automation | Domain: DevOps & Tooling

Python for DevOps Automation - Skill Check

Mental model (bottom-up)

Python is an interpreter + standard library that's great at orchestration and data shaping. You win by: timeouts, input validation, idempotency, and good error messages.

Visual stack

[Your script  ]  CLI, config, logging, exit codes
|
[Stdlib       ]  subprocess, pathlib, json, logging, argparse
|
[Interpreter  ]  imports, bytecode, runtime
|
[OS           ]  processes, files, sockets

Glossary

  • venv - per-project dependency isolation
  • module/package - importable code unit / directory of modules
  • exception - error object used for control flow on failure
  • idempotent - safe to run multiple times without changing result
  • timeout - upper bound on waiting; prevents hangs
  • schema - expected shape/types of input data

Roadmap core (10, easy -> hard)

  • What's the difference: list vs tuple?
  • List mutable; tuple immutable.
  • What's a dict used for?
  • Key/value mapping; fast lookup by key.
  • What is a virtual environment and why use it?
  • Isolated deps per project; avoids system Python conflicts.
  • How do you read a file safely?
  • with open(...) as f: ensures close even on exceptions.
  • Exceptions: try/except/finally purpose?
  • Handle failures; finally runs cleanup regardless.
  • What's the difference: subprocess.run() vs os.system()?
  • subprocess gives control and avoids shell injection; os.system is blunt.
  • JSON/YAML parsing basics?
  • Parse then validate shape/types; don't assume keys exist.
  • Write a CLI in Python (the right way)?
  • argparse (or click/typer in many shops) with subcommands.
  • Concurrency: threads vs processes (in one line)?
  • Threads share memory; processes parallelize CPU-bound.
  • Packaging for reuse?
  • pyproject.toml + pinned deps + entrypoints + tests.

Automation essentials (easy -> hard)

  • How do you make HTTP calls?
  • Use requests (common) or httpx; set timeouts.
  • Why always set timeouts?
  • Prevent hangs; makes retries/backoff meaningful.
  • How do you run shell commands safely?
  • subprocess.run([...], check=True, text=True, capture_output=True)
  • How do you stream output without buffering everything?
  • Use subprocess.Popen with iterated reads or run without capture.
  • What's the right default logging setup?
  • logging module + structured fields; avoid printing secrets.
  • How do you handle config?
  • CLI args override env override config file; validate at startup.
  • How do you model external state safely?
  • Make operations idempotent; retry on transient errors; use locks when needed.
  • When do you move from scripts to a package?
  • Reuse across repos, need tests/versions, or multiple CLIs.

Data & file formats (easy -> hard)

  • JSON vs YAML tradeoff?
  • JSON strict and machine-safe; YAML flexible but can surprise.
  • How do you validate input data?
  • Type checks + required keys; optionally schema validation.
  • What's the safe pattern for writing files?
  • Write temp + fsync (if needed) + atomic rename.
  • Why avoid parsing with regex alone?
  • Edge cases and ambiguity; use proper parsers when formats exist.
  • How do you handle large files?
  • Stream line-by-line; avoid reading whole file into memory.

Testing (easy -> hard)

  • Why write tests for infra scripts?
  • Prevents regressions; locks invariants; safer refactors.
  • Unit vs integration tests?
  • Unit: pure functions; Integration: real system interactions.
  • What's a good "minimal test harness"?
  • pytest + temp dirs + fixtures + golden files.
  • Mocking: when is it harmful?
  • Over-mocking hides real behavior; prefer integration tests for APIs.
  • How do you test CLI tools?
  • Run subprocess; assert exit codes and output; use temp workspace.

Sources

  • Python docs, subprocess docs, argparse docs, logging docs.
  • https://docs.python.org/3/

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