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Python’s Predefined Keywords: A Practical Guide

Python comes with a rich set of predefined keywords that form the backbone of its syntax. These aren't functions you define — they’re built into the language and serve specific roles in control flow, error handling, logic, and structure. Here’s a walk-through of the most essential ones, with explanations and syntax examples to help you master them.

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Exception Handling

Python’s exception handling is clean and readable, thanks to keywords like try, except, finally, raise, and assert.

• try: Begins a block of code that might raise an exception.

  try:
      risky_operation()

• except: Catches and handles exceptions raised in the try block.

  except ValueError:
      print("Invalid value")

• finally: Runs regardless of whether an exception occurred — perfect for cleanup.

  finally:
      close_resources()

• raise: Manually triggers an exception.

  raise RuntimeError("Something went wrong")

• assert: Validates a condition and raises AssertionError if it fails.

  assert x > 0, "x must be positive"

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Looping and Control Flow

Python’s loop constructs are intuitive and flexible, allowing you to iterate, skip, or exit based on conditions.

• for: Iterates over items in a sequence.

  for item in items:
      print(item)

• while: Loops as long as a condition is true.

  while not done:
      process()

• break: Exits the loop immediately.

  if error_detected:
      break

• continue: Skips the current iteration and moves to the next.

  if not valid:
      continue

• pass: A no-op placeholder — useful when the syntax requires a block but you don’t want to do anything yet.

  if condition_met:
      pass

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Conditional Logic

Python’s conditional keywords let you branch your logic cleanly.

• if: Executes a block if the condition is true.

  if score >= 90:
      print("Excellent")

• elif: Adds additional conditions.

  elif score >= 75:
      print("Good")

• else: Executes if no prior conditions matched.

  else:
      print("Needs improvement")

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Functions and Classes

Defining reusable blocks of logic or object-oriented structures is straightforward with these keywords.

• def: Declares a function.

  def greet(name):
      return f"Hello, {name}"

• class: Declares a class.

  class User:
      def __init__(self, name):
          self.name = name

• return: Sends a value back from a function.

  return result

• yield: Used in generators to return a value and pause execution.

  yield item

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Importing Modules

Python’s modularity is powered by its import system.

• import: Brings in a module.

  import os

• from: Imports specific parts of a module.

  from math import sqrt

• as: Assigns an alias to a module or function.

  import numpy as np

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Other Useful Keywords

These keywords support context management, scope control, and logical operations.

• with: Manages resources like files or locks using context managers.

  with open("data.txt") as file:
      content = file.read()

• lambda: Creates anonymous functions.

  square = lambda x: x * x

• global: Declares a variable as global inside a function.

  global counter

• nonlocal: Refers to variables in the nearest enclosing scope (not global).

  nonlocal total

• del: Deletes a variable or item.

  del my_list[0]

• is: Checks identity (not equality).

  if a is b:
      print("Same object")

• in: Checks membership.

  if "admin" in roles:
      grant_access()

• not, and, or: Logical operators.

  if not error and ready or override:
      proceed()

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