Python Code
Samples
Medium snippets you can copy, study, and run in the browser editor.
Bayesian Optimization in Python: A Simplified Mock Implementation
A toy Bayesian optimization loop with a Gaussian process prior, expected improvement acquisition, and noisy sampling to find a function's minimum.
import random
import math
class BayesianOptimizer:
def __init__(self, noise=0.1):
self.noise = noise
self.observations = []
def objective(self, x):
return (math.sin(3*x) + 0.5*x) / (1 + x**2)
def gaussian_process_prior(self, x1, x2, length_scale=0.5):
return math.…Bootstrap Confidence Interval in Python
Estimates a confidence interval for a statistic (like the mean) using bootstrap resampling in pure Python.
import random
def bootstrap_ci(data, statistic, n_bootstraps=1000, ci_level=0.95, seed=42):
random.seed(seed)
n = len(data)
boot_stats = []
for _ in range(n_bootstraps):
sample = [random.choice(data) for _ in range(n)]
boot_stats.append(statistic(sample))
boot_stats.sort()
l…Check Sample Ratio Mismatch in Python
Estimates the probability that a simple random sample's proportion differs from the population proportion by more than 10% using simulation.
import random
def sample_ratio_mismatch(population_size: int, sample_size: int, p: float) -> float:
"""
Estimate the probability that a simple random sample's proportion
differs from the population proportion by more than 10%.
"""
total_counts = [0, 0]
for _ in range(10000):
sample = …Thompson Sampling Mock Bandit in Python
Implement a Thompson sampling multi-armed bandit to explore and exploit reward probabilities across multiple options, updating Beta distributions over time.
import random
class ThompsonSamplingBandit:
def __init__(self, num_arms, alpha=1.0, beta=1.0):
self.num_arms = num_arms
self.alpha = [alpha] * num_arms
self.beta = [beta] * num_arms
def select_arm(self):
samples = [random.betavariate(a, b) for a, b in zip(self.alpha, self.beta…Browse by section
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Guide: free Python code samples library
Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
How to use this library
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
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.