Conditional Statements
if, elif, else
Python uses if, elif, and else for decision-making. Conditions are evaluated top-down, and the first true branch executes. Python treats 0, None, [], {}, "", and False as falsy — everything else is truthy.
✅ Avoid Deep Nesting
# Instead of: if user: if user.is_active: if user.is_admin: do_admin_stuff() # Prefer: if not user or not user.is_active or not user.is_admin: return do_admin_stuff() ✅ Use Ternary Expressions for Simple Conditions
status = "active" if user.is_active else "inactive" ✅ Leverage Truthy/Falsy Evaluations
if items: # Instead of if len(items) > 0 process(items) ✅ Use in and not in for Clean Membership Checks
if role in {"admin", "moderator"}: grant_access() Looping Constructs
Python offers for and while loops, both supporting an optional else block that runs only if the loop is not exited via break. Useful for search-style logic.
✅ for Loops with range, enumerate, zip
# range for i in range(1, 6): print(i) # enumerate for i, item in enumerate(items, start=1): print(f"{i}: {item}") # zip for name, score in zip(names, scores): print(f"{name}: {score}") ✅ while Loop + else
i = 0 while i < 5: if should_stop(i): break i += 1 else: print("Completed without break") ✅ break, continue, pass
for x in data: if x == target: break # Exit loop early if x < 0: continue # Skip this iteration process(x) def todo(): pass # Placeholder for future code Comprehensions with Conditions
Python comprehensions provide a clean and expressive way to build sequences. Conditions can be added inline to filter or transform items.
✅ List Comprehension with if
# Filter even numbers evens = [x for x in nums if x % 2 == 0] ✅ List Comprehension with if-else
# Tag even/odd labels = ["even" if x % 2 == 0 else "odd" for x in nums] ✅ Dict Comprehension with Condition
# Squared values for positives only squared = {x: x**2 for x in nums if x > 0} ✅ Set Comprehension with Condition
# Unique lowercase characters chars = {c.lower() for c in text if c.isalpha()} Pattern Matching (match-case)
Introduced in Python 3.10, match-case provides cleaner alternatives to long if-elif chains. It supports structural pattern matching, guards, and destructuring.
✅ Basic Matching
match command: case "start": run() case "stop": shutdown() case _: print("Unknown command") ✅ Match with Guards (Conditions)
match user: case {"role": "admin"} if user["active"]: grant_access() case _: deny_access() ✅ Destructuring Tuples / Sequences
match point: case (0, 0): print("Origin") case (x, 0): print(f"X-axis at {x}") case (x, y): print(f"Point at ({x}, {y})") ✅ Matching Class Attributes
class User: def __init__(self, name, active): self.name = name; self.active = active match u: case User(name="admin", active=True): print("Admin is active") Best Practices & Tips
✅ Use loop-else for Search Logic
The else clause on loops executes only if the loop wasn't broken. Ideal for search patterns.
for user in users: if user.is_admin: notify(user) break else: log("No admin found") ✅ Avoid Deep Nesting
Flatten logic by returning early or using guard clauses.
# ❌ Deeply nested if user: if user.active: if user.role == "admin": grant_access() # ✅ Cleaner if not user or not user.active or user.role != "admin": return grant_access() ✅ Use Pythonic Alternatives
Replace flag variables with early exits
Use comprehensions instead of loop-based filtering
Use
any(),all(),filter(),map()where appropriate
# Example: Check if any item is negative if any(x < 0 for x in nums): warn() # Efficient – any() stops early when it finds the first True. # Filter positive numbers positives = [x for x in nums if x > 0] # Faster – List comprehensions execute in C under the hood. # all() – Checks if All Conditions are True if all(x > 0 for x in nums): print("All numbers are positive") # filter() – Functional Filtering positives = list(filter(lambda x: x > 0, nums)) #Returns a filtered iterator, saving memory for large datasets. # map() – Apply a Function to Each Element squared = list(map(lambda x: x**2, nums)) 
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