Working with Data Structures in Python

This section explores Python’s built-in data structures in greater detail, covering both familiar concepts and new techniques.

Lists: Advanced Usage

Python’s list data type offers several useful methods for manipulation:

Essential List Methods

• append(x)
  Adds an item to the end of the list. Equivalent to a[len(a):] = [x].
• extend(iterable)
  Extends the list by appending all items from an iterable. Similar to a[len(a):] = iterable.
• insert(i, x)
  Inserts an item at a specified position. The index argument determines where the insertion occurs, so insert(0, x) adds to the beginning, while insert(len(a), x) behaves like append(x).
• remove(x)
  Removes the first occurrence of a value. Raises ValueError if the value doesn’t exist.
• pop([i])
  Removes and returns an item at the given index (last item if no index is provided). Raises IndexError for invalid indices.
• clear()
  Removes all items from the list. Equivalent to del a[:].
• index(x[, start[, end]])
  Returns the first index of a value, with optional search bounds. Raises ValueError if not found.
• count(x)
  Counts occurrences of a value in the list.
• sort(*, key=None, reverse=False)
  Sorts items in place. Parameters allow customization (see sorted() for details).
• reverse()
  Reverses list elements in place.
• copy()
  Returns a shallow copy of the list. Equivalent to a[:].

Practical Example

fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']
print(fruits.count('apple'))  # Output: 2
fruits.reverse()
print(fruits)  # Output: ['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange']
fruits.sort()
print(fruits)  # Output: ['apple', 'apple', 'banana', 'banana', 'kiwi', 'orange', 'pear']

Note that methods like insert(), remove(), and sort() modify the list and return None by design—a Python convention for mutable data structures.

Special Considerations

• Not all data types are comparable. For example, [None, 'hello', 10] cannot be sorted due to incompatible types.
• Some types lack defined ordering (e.g., complex numbers with 3+4j < 5+7j is invalid).

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Using Lists as Stacks

Lists efficiently emulate stacks (last-in, first-out):

• Push: Use append()
• Pop: Use pop()

Example:

stack = [3, 4, 5]
stack.append(6)  # Stack becomes [3, 4, 5, 6]
stack.pop()      # Returns 6

Using Lists as Queues (Inefficient)

For queues (first-in, first-out), lists are suboptimal because popping from the front is slow. Instead, use collections.deque:

from collections import deque
queue = deque(["Eric", "John", "Michael"])
queue.append("Terry")  
queue.popleft()  # Returns "Eric"

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List Comprehensions

A concise way to create lists by applying operations to iterables:

squares = [x**2 for x in range(10)]  # [0, 1, 4, 9, ..., 81]

Comprehensions can include multiple for and if clauses:

[(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]
# Output: [(1, 3), (1, 4), (2, 3), ...]

Nested List Comprehensions

Useful for complex structures like matrix transposition:

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
[[row[i] for row in matrix] for i in range(3)]  # Transposes rows/columns

For real-world use, prefer zip(*matrix).

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Tuples

Immutable sequences, often for heterogeneous data:

t = 12345, 54321, 'hello!'
x, y, z = t  # Unpacking

• Empty tuples: ()
• Singleton tuples require a trailing comma: ('hello',)

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Sets

Unordered collections of unique elements:

basket = {'apple', 'orange', 'apple'}  # Duplicates removed
print('orange' in basket)  # Membership test: True

Set operations (|, &, -, ^) are supported.

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Dictionaries

Key-value mappings with unique, immutable keys:

tel = {'jack': 4098, 'sape': 4139}
tel['guido'] = 4127  # Add/update
print(list(tel))      # ['jack', 'sape', 'guido']

Dictionary comprehensions:

{x: x**2 for x in (2, 4, 6)}  # {2: 4, 4: 16, 6: 36}

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Looping Techniques

• Dictionaries: Use items():pythonCopyfor k, v in knights.items(): print(k, v)
• Sequences: Use enumerate() for indices:pythonCopyfor i, v in enumerate([‘tic’, ‘tac’]): print(i, v)
• Multiple sequences: Combine with zip():pythonCopyfor q, a in zip(questions, answers): print(f”What’s your {q}? It’s {a}.”)
• Reversed/Sorted:pythonCopyfor i in reversed(range(1, 10, 2)): print(i) # 9, 7, …, 1 for f in sorted(set(basket)): print(f) # Unique items sorted

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Comparisons and Conditions

• Chained comparisons: a < b == c
• Short-circuit operators: or/and return the last evaluated argument.
• Sequence comparisons are lexicographical.

Example:

(1, 2, 3) < (1, 2, 4)  # True
'ABC' < 'Python'        # True