Python Programming Advanced Topics and Applied Libraries Syllabus

Advanced Topics and Applied Libraries syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Advanced Topics and Applied Libraries in Python Programming, not a summary of it.

1. 1

   Working with Data Formats

   4 topics

   • JSON Processing
   • CSV Files
   • XML Parsing with ElementTree
   • Regular Expressions with re
2. 2

   Concurrency and Parallelism

   4 topics

   • Threading
   • Multiprocessing
   • Asynchronous Programming
   • The Global Interpreter Lock (GIL)
3. 3

   Testing and Debugging

   4 topics

   • Unit Testing with unittest
   • Testing with pytest
   • Debugging with pdb
   • Logging
4. 4

   Network and Web Programming

   4 topics

   • Socket Programming
   • HTTP Requests
   • Web Frameworks Overview
   • REST APIs
5. 5

   Data Science and Numerical Libraries

   4 topics

   • NumPy Arrays
   • Data Analysis with Pandas
   • Data Visualization with Matplotlib
   • Introduction to Machine Learning Libraries
6. 6

   Type Hints and Modern Python

   4 topics

   • Type Annotations and the typing Module
   • Static Type Checking with mypy
   • Structural Pattern Matching
   • Walrus Operator and Recent Features

Advanced Topics and Applied Libraries flashcards for Python Programming

18 of 55 cards from the Advanced Topics and Applied Libraries deck — real questions with worked answers.

1. Which Python standard-library module is used to encode Python objects to JSON strings and decode JSON back to Python objects?

   The json module.

2. What is the difference between json.dumps() and json.dump()?

   json.dumps() returns a JSON-formatted string; json.dump() writes the JSON output directly to a file-like object.

3. What is the difference between json.loads() and json.load()?

   json.loads() parses a JSON string into a Python object; json.load() reads and parses JSON from a file-like object.

4. How does Python's json module map JSON types to Python types when decoding (object, array, true/false, null)?

   JSON object → dict, array → list, string → str, number → int/float, true/false → True/False, null → None.

5. Which json.dumps() argument pretty-prints the output with indentation, and what does sort_keys do?

   indent (e.g. indent=4) adds indentation for readability; sort_keys=True sorts dictionary keys alphabetically in the output.

6. In the csv module, what is the difference between csv.reader and csv.DictReader?

   csv.reader yields each row as a list of strings; csv.DictReader yields each row as a dict keyed by the header (first) row's field names.

7. When opening a file for use with the csv module, what argument should you pass to open() to avoid extra blank lines, and why?

   Pass newline='' so the csv module handles line endings itself and does not insert blank rows on some platforms (e.g. Windows).

8. Which csv writer methods write a single row versus multiple rows at once?

   writerow() writes one row (a sequence); writerows() writes multiple rows (an iterable of sequences).

9. In the csv module, what does the delimiter parameter control, and what is its default?

   delimiter sets the character separating fields; the default is a comma (',').

10. Which standard-library module parses XML using the ElementTree API, and what are the two core object types it works with?

    xml.etree.ElementTree; it works with the ElementTree (whole document) and Element (individual nodes) objects.

11. In ElementTree, how do you parse an XML file and obtain the root element?

    tree = ET.parse('file.xml') then root = tree.getroot() (or use ET.fromstring(text) to parse a string, which returns the root directly).

12. For an ElementTree Element, what do .tag, .attrib, and .text represent?

    .tag is the element's name, .attrib is a dict of its attributes, and .text is the text content between its opening and closing tags.

13. In ElementTree, what is the difference between element.find() and element.findall()?

    find() returns the first matching sub-element (or None); findall() returns a list of all matching direct sub-elements.

14. Which Python module provides regular-expression support, and what is the benefit of using raw strings for patterns?

    The re module; raw strings (r'...') prevent Python from interpreting backslashes, so regex escapes like \d are passed to the engine intact.

15. In the re module, what is the difference between re.match() and re.search()?

    re.match() checks for a match only at the beginning of the string; re.search() scans the whole string for the first match anywhere.

16. What does re.findall() return versus re.finditer()?

    re.findall() returns a list of all matching substrings (or tuples of groups); re.finditer() returns an iterator of match objects.

17. In regex, what do the metacharacters \d, \w, and \s match?

    \d matches any digit, \w matches any word character (letter, digit, or underscore), and \s matches any whitespace character.

18. In regex quantifiers, what do *, +, and ? mean?

    * matches 0 or more of the preceding element, + matches 1 or more, and ? matches 0 or 1 (optional).

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