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Python Programming Applied Python: Web, Automation And Databases Flashcards

50 question-and-answer cards covering Applied Python: Web, Automation And Databases as it is examined in Python Programming. 24 of them are printed below, taken from across the deck — no signup, no paywall on the preview.

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24 sample cards from the Applied Python: Web, Automation And Databases deck

Sampled from the end of the deck, so these are different cards from the ones shown on the syllabus page.

  1. What is web scraping?

    The automated extraction of data from websites by downloading HTML pages and parsing their content programmatically.

  2. What is BeautifulSoup used for in Python web scraping?

    A library for parsing HTML/XML documents into a navigable tree, allowing you to search and extract elements by tag, attribute, class, or CSS selector.

  3. In BeautifulSoup, what is the difference between find() and find_all()?

    find() returns the first matching element (or None); find_all() returns a list of all matching elements.

  4. What is the purpose of the robots.txt file in the context of web scraping?

    A file at a site's root that tells crawlers which paths they are allowed or disallowed from accessing; ethical scrapers should respect it.

  5. When is Selenium preferred over requests + BeautifulSoup for scraping?

    When the target content is rendered dynamically by JavaScript, since Selenium drives a real browser that executes JS, whereas requests only fetches the raw HTML.

  6. What is a CSS selector in scraping, and which BeautifulSoup method uses them?

    A pattern to target HTML elements (e.g., 'div.price', '#id'). BeautifulSoup's select() method returns all elements matching a CSS selector.

  7. What is Scrapy?

    A complete Python framework for large-scale web scraping/crawling, providing built-in support for requests, parsing, item pipelines, concurrency, and exporting data.

  8. What is a web application framework?

    A software framework that provides tools and structure (routing, templating, request/response handling) to build web applications without writing low-level HTTP code.

  9. What is the key difference between Flask and Django?

    Flask is a lightweight microframework (minimal, add components as needed); Django is a full-featured 'batteries-included' framework with built-in ORM, admin, auth, and more.

  10. In Flask, how do you define a route that maps a URL to a function?

    Use the @app.route('/path') decorator above the view function, e.g., @app.route('/hello') def hello(): return 'Hi'.

  11. What is the role of a template engine like Jinja2 in web frameworks?

    It renders dynamic HTML by combining template files with Python data, using placeholders ({{ var }}) and control structures ({% for %}) to produce the final page.

  12. What does the MVC (or Django's MVT) architectural pattern stand for?

    Model-View-Controller (data, presentation, logic). Django uses MVT: Model, View (logic), Template (presentation).

  13. What is WSGI?

    Web Server Gateway Interface, the standard Python specification that defines how web servers communicate with Python web applications/frameworks.

  14. Name a modern asynchronous Python web framework and its key feature.

    FastAPI, which supports async/await, automatic OpenAPI docs, and request validation via Python type hints (Pydantic).

  15. What is task automation in Python and give one common use case.

    Writing scripts to perform repetitive tasks automatically. Common uses: file/folder management, sending emails, data backups, report generation, or scheduled jobs.

  16. Which Python modules are commonly used for file system automation tasks?

    os, shutil (file copy/move/delete), pathlib (object-oriented paths), and glob (pattern-based file matching).

  17. How can you schedule a Python script to run periodically on a Unix/Linux system?

    Using cron (a crontab entry); on Windows, Task Scheduler; or within Python using the schedule library or APScheduler.

  18. What is the purpose of the subprocess module?

    It lets a Python script spawn and run external programs/system commands, connect to their input/output/error streams, and obtain their return codes.

  19. What is a CLI (command-line tool) and why build one in Python?

    A program operated through text commands in a terminal. Building one in Python lets you create reusable, scriptable utilities that accept arguments and options.

  20. Which standard-library module parses command-line arguments, and name one third-party alternative.

    Standard library: argparse. Popular third-party alternatives: Click and Typer.

  21. What is the difference between a positional argument and an optional argument in argparse?

    A positional argument is required and identified by its position; an optional argument is prefixed with -/-- (a flag) and is generally not mandatory.

  22. Explain the difference between concurrency and parallelism.

    Concurrency is managing multiple tasks that make progress by interleaving (not necessarily at the same instant); parallelism is executing multiple tasks literally simultaneously on multiple CPU cores.

  23. What is Python's GIL and how does it affect threading?

    The Global Interpreter Lock allows only one thread to execute Python bytecode at a time, so threads do not give true parallelism for CPU-bound work (but help with I/O-bound tasks).

  24. When should you use threading vs multiprocessing vs asyncio in Python?

    threading and asyncio for I/O-bound tasks (asyncio for high-concurrency I/O); multiprocessing for CPU-bound tasks since it bypasses the GIL by using separate processes.

What this deck covers

This deck covers the Applied Python: Web, Automation And Databases portion of the Python Programming syllabus in question-and-answer form. Browse the full Python Programming syllabus to see how it fits with the rest.

Answers are written to be recallable, not just readable — averaging about 143 characters, which is long enough to carry the reasoning and short enough to say out loud.

A deck like this earns its keep on the second and third pass. Read the syllabus first so you know the shape of the subject, then use the cards to find the specific facts that have not stuck.

Applied Python: Web, Automation And Databases flashcards FAQ

How many Applied Python: Web, Automation And Databases flashcards are in this Python Programming deck?

50 cards. This page previews 24 of them, sampled evenly across the deck so you can judge the difficulty before installing anything.

Are these Python Programming flashcards free?

Yes. The preview here is free to read with no signup, and the full 50-card deck is free inside the Examius app.

What do the Applied Python: Web, Automation And Databases cards cover?

They follow the Applied Python: Web, Automation And Databases portion of the Python Programming syllabus, in question-and-answer form.

How should I use these flashcards?

Read the syllabus first so you know the shape of the subject, then drill the deck. Examius schedules each card with spaced repetition, so cards you keep missing come back sooner and ones you know drift further apart.