Python Essentials: Functions, Loops, Data Structures & More

Posted on Mar 23, 2025 in Telecommunication Technologies

Python Essentials

1. Functions

• Defining a Function:

  python
  def function_name(parameters): # Code block

• Calling a Function:

  python
  function_name(arguments)

• Default Parameters:

  python
  def greet(name="User"): print(f"Hello, {name}!") greet() # "Hello, User!" greet("Alice") # "Hello, Alice!"

• Return Statement:

  python
  def add(a, b): return a + b result = add(3, 5) # result is 8

• Function Scope (Local vs Global):

  • Local variables are accessible only within the function.
  • Global variables are accessible throughout the program.

2. Loops

• For Loop (List Iteration):

  python
  for i in range(len(my_list)): print(my_list[i])

• For Loop (Range):

  python
  for i in range(0, 5): # Iterates from 0 to 4 print(i)

• Nested Loops (For Matrices):

  python
  matrix = [[1, 2], [3, 4]] for row in matrix: for element in row: print(element)

• List Iteration & Modification During Loop:

  • Be careful when modifying a list while iterating, as it may skip elements.
  • Consider iterating over a copy or using list comprehensions to avoid issues.

3. Data Structures

• Lists:

  • Mutable: You can modify lists after creation.
  • Example:
    python
    my_list = [1, 2, 3] my_list[0] = 10 # my_list becomes [10, 2, 3]

• Tuples:

  • Immutable: Once created, elements cannot be changed.
  • Example:
    python
    my_tuple = (1, 2, 3) # my_tuple[0] = 10 # ERROR

• Sets:

  • Unordered collection of unique elements.
  • Set operations:
    • Combines: s1 | s2
    • Returns what is common to both sides: s1 & s2
    • Returns elements in the 1st set that aren’t common: s1 - s2
    • Returns elements that are not common in both: s1 ^ s2

• Dictionaries:

  • Access elements by keys.
  • Example:
    python
    d = {"apple": 3, "banana": 5} print(d["apple"]) # 3

• Common Methods for Dictionaries:

  • .items(): Returns a list of (key, value) pairs.
  • .keys(): Returns a list of keys.
  • .values(): Returns a list of values.

4. Strings

• String Indexing:

  python
  my_string = "Hello" print(my_string[0]) # 'H'

• Slicing:

  python
  my_string = "Hello" print(my_string[:3]) # 'Hel'

• String Methods:

  • .upper(): Converts to uppercase.
  • .lower(): Converts to lowercase.
  • .split(): Splits a string into a list based on a delimiter.
    python
    my_string = "Hello World" print(my_string.split()) # ['Hello', 'World']

5. Conditionals

• If Statements:

  python
  if condition: # Code block if condition is true

• Logical Operators:

  • and: Returns true if both conditions are true.
  • or: Returns true if at least one condition is true.
  • not: Reverses the Boolean value.

• Modifying Elements Based on Conditions:

  python
  nums = [1, 2, 3, 4, 5] for i in range(len(nums)): if nums[i] % 2 == 0: nums[i] = 0 print(nums) # [1, 0, 3, 0, 5]

6. File Handling

• Reading Files:
  • .read(): Reads the entire file content.
  • .readline(): Reads one line at a time.
  • .readlines(): Reads all lines into a list.
  • Example:
    python
    with open("file.txt", "r") as infile: for line in infile: print(line.strip())

7. List Operations

• List Repetition:

  python
  my_list = [1, 2] new_list = my_list * 3 # [1, 2, 1, 2, 1, 2]

• List Comprehension:

  python
  nums = [1, 2, 3, 4] squares = [x**2 for x in nums if x % 2 == 0] # [4, 16]

• Modifying Lists During Iteration:

  • Avoid modifying a list while iterating over it. This can lead to unexpected behavior.
  • Use list comprehensions or iterate over a copy.

8. Common Functions

• max(): Returns the maximum value from an iterable.

  python
  max([1, 2, 3]) # 3

• sum(): Returns the sum of all elements in an iterable.

  python
  sum([1, 2, 3]) # 6

• len(): Returns the length of an iterable.

  python
  len([1, 2, 3]) # 3

9. Debugging Tips

• Variable Assignment & References:
  • Assigning a variable to another creates a reference to the same object (in case of mutable types).
  • Modifying a mutable object through one reference will affect all references to that object.
• Avoid Modifying Lists During Iteration:
  • This can cause some elements to be skipped, leading to unexpected results. Instead, use a copy of the list or list comprehensions.