Multiple Conditions in List Comprehension: The Complete Logic Guide (2026)

In the real world, filtering logic is rarely simple. You almost never just say "Get me numbers greater than 5." You say, "Get me numbers greater than 5, but only if they are even, and exclude the number 88."

Standard for loops handle this complexity with nested if blocks. List comprehensions handle it with boolean logic operators.

[!NOTE] Logic Cheatsheet

• AND: if condition1 and condition2
• OR: if condition1 or condition2
• NOT: if not condition

Table of Contents

1. AND Logic: Two Ways to Chain (Visualized)
2. OR Logic: The Syntax Rule
3. Combining AND + OR (Parentheses Logic)
4. Performance: Short-Circuiting
5. Refactoring Complex Logic
6. Exercises
7. FAQ
8. Test Your Knowledge (Quiz)

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AND Logic: Two Ways to Chain (Visualized)

When you need multiple conditions to ALL be true (Intersecting sets), you have two syntactic options in Python.

Method 1: The Logical and (Preferred)

[x for x in range(20) if x % 2 == 0 and x > 10]

Method 2: The Daisy Chain

[x for x in range(20) if x % 2 == 0 if x > 10]

Visualizing the Chain:

   [ Item ] ---> [ Check 1? ] --(Yes)--> [ Check 2? ] --(Yes)--> [ KEEP ]
                      |
                     (No)
                      |
                  (Discard)

Method 2 is identical to Method 1, but most developers prefer and because it reads more like a sentence.

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OR Logic: The Syntax Rule

When you need AT LEAST ONE condition to be true (Union of sets), you must use the or keyword. You cannot chain if statements for OR logic.

Example: Keep if divisible by 2 OR 3

[x for x in range(15) if x % 2 == 0 or x % 3 == 0]
# Result: [0, 2, 3, 4, 6, 8, 9, 10, 12, 14]

Visualizing OR:

   [ Item ] ---> [ Check 1? ] --(Yes)--> [ KEEP ]
                      |
                     (No)
                      |
                      v
                 [ Check 2? ] --(Yes)--> [ KEEP ]

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Combining AND + OR (Parentheses Logic)

This is where bugs happen. If you mix and and or, Python follows standard operator precedence (AND binds tighter than OR). Always use parentheses to make your intent explicit.

Scenario: "I want numbers that are (Divisible by 2 OR 3) AND (Not equal to 0)."

Bad Code (Ambiguous):

[x for x in data if x % 2 == 0 or x % 3 == 0 and x != 0]

Depending on precedence, this might let 0 through.

Good Code (Explicit):

[x for x in data if (x % 2 == 0 or x % 3 == 0) and x != 0]

De Morgan's Laws (Simplification)

Sometimes negative logic is confusing. Remember De Morgan's Law:

• not (A or B) is the same as not A and not B.
• not (A and B) is the same as not A or not B.

Confusing:

[x for x in data if not (x < 5 or x > 10)]

Simplified:

[x for x in data if x >= 5 and x <= 10]

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Performance: Short-Circuiting

Python evaluates boolean expressions left-to-right and stops as soon as the result is determined. This is called Short-Circuiting.

• False and (...) -> Stops immediately (Entire result is False).
• True or (...) -> Stops immediately (Entire result is True).

Why does this matter? Performance.

If you have one "Cheap" check and one "Expensive" check, put the cheap one first.

# Scenario: Check if number is positive AND if it passes a heavy CPU function

# FAST:
[x for x in data if x > 0 and heavy_validation(x)]
# logic: If x is -5, 'x > 0' is False. Python skips calling 'heavy_validation'.

# SLOW:
[x for x in data if heavy_validation(x) and x > 0]
# logic: Calls function for EVERY item, even -5.

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Refactoring Complex Logic

There is a strict limit to how much logic you should cram into one syntax line. That limit is usually "Does it fit on one line?"

If your filter looks like this:

[x for x in users if (x.is_active or x.is_admin) and x.age > 18 and x.country == 'US']

Stop. This is unreadable/unmaintainable.

Solution: Extract to Function Define a predicate function with a good name.

def is_valid_us_user(user):
    has_permission = user.is_active or user.is_admin
    is_adult = user.age > 18
    return has_permission and is_adult and user.country == 'US'

# The Comprehension becomes clean again:
valid_users = [u for u in users if is_valid_us_user(u)]

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Exercises

Try to translate these requirements into a comprehension condition.

1. The Range check Requirement: Numbers between 10 and 20 (inclusive).

• Can you use chained comparison?

2. The Exclusion Requirement: Strings starting with 'A' but NOT 'Apple'.

3. The Valid User Requirement: Users where name is not None and age is greater than 0.

Solutions

1. [x for x in nums if 10 <= x <= 20] (Python supports math chaining!)
2. [s for s in strings if s.startswith('A') and s != 'Apple']
3. [u for u in users if u.name and u.age > 0]

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FAQ

Q1: Can I use in for multiple logical checks?

A: Yes! Instead of x == 1 or x == 2 or x == 3, stick them in a set: if x in {1, 2, 3}. This is cleaner and faster.

Q2: Is there a limit to how many ands I can use?

A: No technical limit, but readability suffers after 2 or 3. If you force your teammates to scroll horizontally, they will dislike your code.

Q3: How do chained ifs handle else?

A: They don't. You cannot use else in the filtering section, regardless of how many ifs you chain.

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Test Your Knowledge

Conclusion

Logic is the heart of filtering. By mastering and, or, and the art of Short-Circuiting, you can write list comprehensions that are not only correct but highly performant.

Next Steps:

• You know filtering. Now look at structure: Nested List Comprehensions
• Go 3D: Flattening Lists