Querying with filter and filter_by in Flask - Performance & Optimization

Performance: Querying with filter and filter_by

MEDIUM IMPACT

This affects how quickly the database returns filtered data and how much processing the server does before sending results.

Filtering database records in Flask SQLAlchemy

Flask

User.query.filter(User.name.like('john%')).all()

Starts with fixed string, allowing index use and faster query execution.

📈 Performance GainReduces query time by 80%, improving LCP

Filtering database records in Flask SQLAlchemy

Flask

User.query.filter(User.name.like('%john%')).all()

Using a wildcard at the start of LIKE disables index use, causing full table scans.

📉 Performance CostBlocks rendering for 100+ ms on large tables due to slow query

Performance Comparison

Pattern	DOM Operations	Reflows	Paint Cost	Verdict
filter with leading wildcard	N/A	N/A	Delays initial paint due to slow data	[X] Bad
filter with indexed prefix	N/A	N/A	Faster data arrival improves paint	[OK] Good
filter for equality	N/A	N/A	Slightly slower server processing	[!] OK
filter_by for equality	N/A	N/A	Optimized server processing	[OK] Good

Rendering Pipeline

The database query runs before the browser rendering starts. Slow queries delay data arrival, increasing LCP. Efficient filters reduce server processing time, speeding up data delivery and page paint.

→Server Processing

→Network Transfer

→Browser Rendering

⚠️ BottleneckServer Processing (slow database queries)

Core Web Vital Affected

LCP

This affects how quickly the database returns filtered data and how much processing the server does before sending results.

Optimization Tips

1Avoid leading wildcards in LIKE filters to enable index use.

2Use filter_by for simple equality filters to reduce server processing time.

3Index columns used in filters to speed up database queries and improve LCP.

Performance Quiz - 3 Questions

Which filter pattern is faster for simple equality in Flask SQLAlchemy?

A filter(User.age == 30)

B filter_by(age=30)

C filter(User.age.like('%30%'))

D filter(User.age != 30)

DevTools: Network and Performance panels

How to check: 1. Open DevTools and go to Network tab. 2. Reload page and find API/database request. 3. Check request duration and response size. 4. Use Performance tab to see when main content paints.

What to look for: Look for long server response times delaying Largest Contentful Paint (LCP). Faster queries show shorter wait times and quicker paint.

Practice

1. What is the main difference between filter and filter_by in Flask querying?

easy

A. filter is used only for deleting records; filter_by is for selecting.

B. filter_by allows complex expressions; filter uses simple keyword arguments.

C. filter allows complex expressions; filter_by uses simple keyword arguments.

D. filter and filter_by are exactly the same in usage.

Solution

1. Step 1: Understand filter usage

   filter accepts expressions like User.age > 20, allowing detailed conditions.

2. Step 2: Understand filter_by usage

   filter_by uses simple keyword arguments like filter_by(name='John') for equality checks.

3. Final Answer:

   filter allows complex expressions; filter_by uses simple keyword arguments. -> Option C

4. Quick Check:

   filter = complex, filter_by = simple keyword [OK]

Hint: Remember: filter = expressions, filter_by = simple equals [OK]

Common Mistakes:

• Thinking filter_by supports complex expressions
• Confusing filter_by with filter in syntax
• Assuming both methods behave identically

2. Which of the following is the correct syntax to filter users with age 30 using filter_by?

easy

A. User.query.filter_by('age == 30').all()

B. User.query.filter_by(age=30).all()

C. User.query.filter_by(age == 30).all()

D. User.query.filter_by(age > 30).all()

Solution

1. Step 1: Check filter_by syntax

   filter_by accepts keyword arguments like age=30, not expressions or strings.

2. Step 2: Identify correct usage

   Only User.query.filter_by(age=30).all() uses correct keyword argument syntax.

3. Final Answer:

   User.query.filter_by(age=30).all() -> Option B

4. Quick Check:

   filter_by uses keyword arguments [OK]

Hint: Use keyword arguments without quotes or operators in filter_by [OK]

Common Mistakes:

• Passing expressions or strings to filter_by
• Using comparison operators inside filter_by
• Confusing filter_by with filter syntax

3. Given the model User with fields name and age, what will this query return?

users = User.query.filter(User.age > 25).filter_by(name='Alice').all()

medium

A. All users named Alice older than 25

B. All users older than 25, ignoring name

C. All users named Alice, ignoring age

D. Syntax error due to mixing filter and filter_by

Solution

1. Step 1: Understand chaining filters

   Chaining filter and filter_by combines conditions with AND logic.

2. Step 2: Analyze conditions

   filter(User.age > 25) filters age > 25, filter_by(name='Alice') filters name = 'Alice'. Both apply together.

3. Final Answer:

   All users named Alice older than 25 -> Option A

4. Quick Check:

   Chained filters combine conditions [OK]

Hint: Chained filters combine all conditions with AND [OK]

Common Mistakes:

• Thinking filter_by overrides filter
• Assuming only one filter applies
• Believing mixing filter and filter_by causes error

4. What is wrong with this query?

users = User.query.filter_by(User.age > 20).all()

medium

A. filter_by requires a list, not a condition

B. User.age > 20 is a valid filter_by argument

C. The query is correct and returns users older than 20

D. filter_by does not accept expressions, only keyword arguments

Solution

1. Step 1: Check filter_by argument type

   filter_by only accepts keyword arguments like age=20, not expressions.

2. Step 2: Identify error in usage

   Passing User.age > 20 is an expression, invalid for filter_by.

3. Final Answer:

   filter_by does not accept expressions, only keyword arguments -> Option D

4. Quick Check:

   filter_by = keyword args only [OK]

Hint: filter_by needs simple key=value pairs, not expressions [OK]

Common Mistakes:

• Passing expressions to filter_by
• Confusing filter_by with filter syntax
• Expecting filter_by to parse conditions

5. You want to find all users whose name starts with 'J' and are younger than 40. Which query correctly uses filter and filter_by together?

hard

A. User.query.filter(User.name.like('J%')).filter(User.age < 40).all()

B. User.query.filter_by(name='J%').filter_by(age < 40).all()

C. User.query.filter(User.name.like('J%')).filter_by(age=40).all()

D. User.query.filter_by(name.like('J%')).filter(User.age < 40).all()

Solution

1. Step 1: Use filter for complex conditions

   Checking if name starts with 'J' requires like('J%'), which is an expression needing filter.

2. Step 2: Use filter for age less than 40

   Age < 40 is also an expression, so filter is needed again. filter_by cannot handle expressions.

3. Step 3: Verify option correctness

   User.query.filter(User.name.like('J%')).filter(User.age < 40).all() uses filter twice with correct expressions. Others misuse filter_by or syntax.

4. Final Answer:

   User.query.filter(User.name.like('J%')).filter(User.age < 40).all() -> Option A

5. Quick Check:

   Use filter for expressions, filter_by for simple equals [OK]

Hint: Use filter for expressions like like() and comparisons [OK]

Common Mistakes:

• Using filter_by with expressions like like() or <
• Mixing filter_by with invalid syntax
• Assuming filter_by can handle partial matches