Python Collections & Data Structures

What you will be able to do

• Choose the optimal built-in data structure based on time and space complexity
• Write idiomatic list, dictionary and set comprehensions
• Use collections module structures: deque, Counter, defaultdict and namedtuple
• Implement priority queues and min-heaps using heapq
• Understand memory footprints and mutability nuances across Python collections

What you will learn

1. 4.1Built-in Sequences & Mappings4 lessons

   Deep dive into lists, tuples, sets, and dictionaries under the hood.

   1. List Memory Growth, Slicing and Complexity18 min
   2. Tuples as Immutable Records and Hashable Keys15 min
   3. Hash Tables: Sets and Dictionaries Under the Hood20 min
   4. Dictionary Views, Sorting and Merging15 min
2. 4.2Sorting & Comparing4 lessons

   Sort lists by any field with sorted, key functions, itemgetter and attrgetter, order your own objects with __lt__ and dataclass order=True, and use min, max and bisect.

   1. sorted() vs .sort(), reverse and Stability16 min
   2. Key Functions, lambda, itemgetter and attrgetter18 min
   3. Sorting Your Own Objects: __lt__, order=True, min, max and bisect18 min
   4. Sorting and Comparing Checkpoint22 min
3. 4.3Advanced Collections & Heaps4 lessons

   Specialized container datatypes in the Python standard library.

   1. Double-Ended Queues with collections.deque18 min
   2. Counting Frequencies with collections.Counter15 min
   3. Default Values with collections.defaultdict15 min
   4. Priority Queues and Min-Heaps with heapq20 min
4. 4.4Collections Mini Projects3 lessons

   A marks analyser, a priority support ticket queue and the Course Enrollment System capstone for the whole Python foundation.

   1. Build a Marks and Results Analyser60 min
   2. Build a Support Ticket Queue with Priorities60 min
   3. Course Enrollment System: Python Foundation Capstone120 min