A/B testing & experimentation
User bucketing, experiment metrics, statistical comparison, and rollout guardrails.
How to Hash a User ID to an Experiment Bucket in Python
Deterministically map a user ID to one of N experiment buckets using MD5 hashing and modulo arithmetic.
import hashlib
def hash_to_bucket(user_id: str, num_buckets: int = 10) -> int:
"""Deterministically map a user_id to a bucket (0 to num_buckets-1)."""
digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
return int(digest[:8], 16) % num_buckets
if __name__ == "__main__":
# Mock experiment: split…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.
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…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.
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__":
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A/B testing & experimentation — Python code examples
What you will find here
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.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.