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A/B testing & experimentation

User bucketing, experiment metrics, statistical comparison, and rollout guardrails.

5 matches
A/B testing & experimentation easy

How to Do Random Assignment in Python for A/B Tests

Assign each item to a binary group (0 or 1) with uniform probability using a small reusable function, optionally weighted, for A/B testing mocks.

random ab-testing assignment
Python
import random

def random_assignment_uniform_mock(items, weights=None):
    """Assign each item to a group (0 or 1) with uniform probability."""
    if weights is None:
        # Default: each item independently gets 0 or 1 with 50% probability
        return [random.randint(0, 1) for _ in items]
    # Optional weight…
13 0 Open
A/B testing & experimentation easy

How to Mock Stratified Assignment by Segment in Python

Simulate stratified assignment for A/B experiments by sampling a fixed proportion of units from each segment, with deterministic seeds for reproducibility.

ab-testing sampling random
Python
import random

def stratified_assignment(segments, seed=None):
    """
    Mock stratified assignment: given a dict of segment -> population size,
    return a dict of segment -> sampled unit ids (deterministic with seed).
    """
    if seed is not None:
        random.seed(seed)
    rng = random.Random(seed)
    res…
12 0 Open
A/B testing & experimentation medium

How to Perform Intent-to-Treat Analysis in Python

Runs an intent-to-treat analysis on mock A/B test data, comparing outcomes by initial group assignment with a t-test for significance.

ab-testing intent-to-treat statistics
Python
import pandas as pd
import numpy as np


def intent_to_treat_analysis(data):
    """Perform intent-to-treat (ITT) analysis.

    ITT compares outcomes based on initial treatment assignment,
    regardless of whether participants actually received the treatment.
    """
    # Create a copy to avoid mutating the origina…
13 0 Open
A/B testing & experimentation easy

How to hash user IDs to experiment buckets in Python

Deterministically map a user ID to an experiment bucket using MD5 hashing, ensuring stable and consistent assignment for A/B testing.

hashing ab-testing experiments
Python
import hashlib


def hash_user_to_bucket(user_id: str, num_buckets: int = 10) -> int:
    """Deterministically map a user ID to an experiment bucket (0..num_buckets-1)."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest, 16) % num_buckets


if __name__ == "__main__":
    mock_users …
12 0 Open
A/B testing & experimentation medium

How to join assignment logs with outcomes in Python

Merge submission log entries with grading outcomes using left join and full outer join patterns in pure Python.

join data-merge ab-testing
Python
from datetime import datetime, timedelta

class AssignmentLog:
    def __init__(self):
        self.logs = [
            {"assignment_id": 101, "student_id": "S001", "submitted_at": "2024-03-01 10:30:00"},
            {"assignment_id": 101, "student_id": "S002", "submitted_at": "2024-03-02 14:15:00"},
            {"as…
12 0 Open

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A/B testing & experimentation — Python code examples

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This page collects a/b testing & experimentation snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.

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