String validation (min, max, regex) in FastAPI - Step-by-Step Execution

Concept Flow - String validation (min, max, regex)

Define Pydantic Model with String Field

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Add min_length, max_length, regex Constraints

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Receive Input Data in FastAPI Endpoint

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Validate Input Against Constraints

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Process Request

Input string is checked against minimum length, maximum length, and regex pattern before processing or error response.

Execution Sample

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel, constr

class User(BaseModel):
    username: constr(min_length=3, max_length=10, regex='^[a-zA-Z0-9_]+$')

app = FastAPI()

Defines a FastAPI model with a username string that must be 3-10 characters and match a regex pattern.

Execution Table

Step	Input username	Check min_length >=3	Check max_length <=10	Check regex match	Validation Result
1	"ab"	False (length 2 < 3)	Skipped	Skipped	Invalid - too short
2	"abc"	True (length 3 >= 3)	True (length 3 <= 10)	True (matches)	Valid
3	"abcdefghijk"	True (length 11 >= 3)	False (length 11 > 10)	Skipped	Invalid - too long
4	"abc!def"	True (length 7 >= 3)	True (length 7 <= 10)	False (contains '!')	Invalid - regex mismatch
5	"user_123"	True (length 8 >= 3)	True (length 8 <= 10)	True (matches)	Valid

💡 Validation stops at first failed check or passes if all checks succeed.

Variable Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5
username	None	"ab"	"abc"	"abcdefghijk"	"abc!def"	"user_123"
min_length_check	N/A	False	True	True	True	True
max_length_check	N/A	Skipped	True	False	True	True
regex_check	N/A	Skipped	True	Skipped	False	True
validation_result	N/A	Invalid	Valid	Invalid	Invalid	Valid

Key Moments - 3 Insights

Why does validation stop after the min_length check fails?

Because the execution_table shows that once min_length is false (step 1), max_length and regex checks are skipped, so validation stops early to save time.

What happens if the input is too long but matches regex?

At step 3, max_length check fails even though regex matches, so validation returns invalid due to length, as shown in the execution_table.

Why is regex check skipped when min_length or max_length fails?

Validation stops at the first failure to avoid unnecessary checks, so regex is only checked if length constraints pass, as seen in steps 1 and 3.

Visual Quiz - 3 Questions

Look at the execution_table, what is the validation result at step 4 for input "abc!def"?

A Invalid - regex mismatch

B Invalid - too short

C Valid

D Invalid - too long

💡 Hint

Check the regex match column at step 4 in the execution_table.

At which step does the max_length check fail?

A Step 1

B Step 5

C Step 3

D Step 2

💡 Hint

Look at the max_length check column in the execution_table.

If the input "user!name" is tested, which validation check will fail first?

A max_length

B regex

C min_length

D None, it will be valid

💡 Hint

Refer to regex check behavior in the execution_table and variable_tracker.

Concept Snapshot

Use Pydantic's constr type to validate strings in FastAPI.
Set min_length and max_length to limit length.
Use regex to enforce pattern rules.
Validation stops at first failure.
Invalid input returns error response automatically.

Full Transcript

This visual execution shows how FastAPI uses Pydantic to validate string inputs with minimum length, maximum length, and regex pattern constraints. The flow starts by defining a model with these rules. When input arrives, it checks min_length first, then max_length, then regex. If any check fails, validation stops and returns an error. If all pass, the input is accepted. The execution table traces five example inputs step-by-step, showing which checks pass or fail and the final validation result. The variable tracker records how each variable changes after each input. Key moments clarify why validation stops early and how regex is only checked if length is valid. The quiz tests understanding of these steps. The snapshot summarizes how to use constr for string validation in FastAPI.