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Generate Data Helper for Beginners in Python
Define two functions that create a random list of integers and then compute basic summary statistics like count, total, average, maximum, and minimum using simple loops.
from random import randint
def build_dataset(size: int, max_val: int) -> list[int]:
data = []
for _ in range(size):
data.append(randint(1, max_val))
return data
def summarize(data: list[int]) -> dict[str, float]:
total = 0
maximum = data[0]
minimum = data[0]
for value in data:
…How to Calculate the Average of a List of Numbers in Python
Compute the arithmetic mean of a numeric list using Python's built-in sum() and len() functions, returning 0.0 for an empty list.
def calculate_average(numbers):
if not numbers:
return 0.0
return sum(numbers) / len(numbers)
if __name__ == "__main__":
sample_numbers = [10, 20, 30, 40, 50]
result = calculate_average(sample_numbers)
print(f"Average: {result}")How to Compute a Moving Average in Python
This code computes the moving average over a numeric list using an efficient sliding window sum, avoiding recomputation of each window.
def moving_average(data, window_size):
"""
Compute the moving average over a numeric list.
Args:
data: List of numeric values
window_size: Size of the sliding window (positive integer)
Returns:
List of moving averages, each representing the mean of a window
"""
…How to Filter Even Numbers and Square Them in Python
Create two beginner-friendly helper functions that filter even numbers and compute squares of a number list using loops, then print the results along with the sum and average.
def get_even_numbers(numbers):
evens = []
for num in numbers:
if num % 2 == 0:
evens.append(num)
return evens
def get_squares(numbers):
squares = []
for num in numbers:
squares.append(num ** 2)
return squares
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers …How to Summarize a List of Numbers in Python
Loop over a list of numbers to compute total, count, average, min, and max, then return them in a dictionary.
def summarize_numbers(numbers):
"""Return a dict with basic stats for a list of numbers."""
total = 0
count = 0
smallest = numbers[0]
largest = numbers[0]
for num in numbers:
total += num
count += 1
if num < smallest:
smallest = num
if num > largest:…How to summarize and transform lists in Python
Compute count, sum, min, max, and average for a list and multiply each element by a factor using simple loops and built-in functions.
def summarize(data):
"""Return a summary of a list: count, sum, min, max, average."""
count = len(data)
total = sum(data)
minimum = min(data)
maximum = max(data)
average = total / count if count else 0
return count, total, minimum, maximum, average
def multiply_elements(data, factor=2):
…How to Apply a Function to Sliding Window Slices in Python
This Python code applies a given function to every contiguous window of a specified size in a list, returning a list of results.
def apply_to_sliding_windows(data, window_size, func):
return [func(data[i:i + window_size]) for i in range(len(data) - window_size + 1)]
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5, 6]
window_size = 3
results = apply_to_sliding_windows(numbers, window_size, sum)
print(results)
results…How to Implement a Moving Average from a Data Stream in Python
Implement a MovingAverage class using a deque and running sum to compute the average of the last k values from a continuous data stream.
from collections import deque
class MovingAverage:
def __init__(self, size):
self.size = size
self.queue = deque()
self.window_sum = 0
def next(self, val):
self.queue.append(val)
self.window_sum += val
if len(self.queue) > self.size:
self.window_su…How to partition a list into n nearly equal parts in Python
Divide a list into n contiguous chunks of nearly equal size using an average-length calculation that distributes the remainder evenly.
def partition(lst, n):
"""Partition a list into n nearly equal contiguous parts."""
if n <= 0:
raise ValueError("n must be positive")
if not lst:
return [[] for _ in range(n)]
parts = []
avg = len(lst) / n
last_idx = 0.0
while last_idx < len(lst):
end_idx =…How to Log Prompts and Completions as JSONL Audit Files in Python
Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.
import json
from pathlib import Path
from datetime import datetime
def audit_jsonl(filepath):
logs = []
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
entry = json.loads(line)
logs.ap…How to Group Data by Key in Python
Group a list of dictionaries by a specified key using a defaultdict and compute per-group averages.
from collections import defaultdict
def group_by_key(data, key):
grouped = defaultdict(list)
for item in data:
grouped[item[key]].append(item)
return dict(grouped)
if __name__ == "__main__":
records = [
{"name": "Alice", "dept": "Engineering", "score": 85},
{"name": "Bob", "de…How to Implement a Sliding Window Average in Python
Compute the average of the most recent N values in a stream using a bounded deque, efficiently updating the total as new values arrive.
from collections import deque
class SlidingWindowAverage:
def __init__(self, window_size):
self.window_size = window_size
self.window = deque(maxlen=window_size)
self.total = 0
def add(self, value):
if len(self.window) == self.window_size:
self.total -= self.windo…How to Take Periodic Snapshots of Aggregate State in Python
Build a Python class that accumulates values and periodically captures immutable snapshots of total, count, and average for later analysis.
import time
import random
from collections import defaultdict
class SnapshotAggregator:
def __init__(self):
self.total = 0
self.count = 0
self.history = []
def add(self, value):
self.total += value
self.count += 1
def snapshot(self):
avg = self.total / se…Sliding Window Average with Deque in Python
Computes the running average of a sliding window over streaming numbers using a collections.deque for O(1) pop-left operations.
from collections import deque
class SlidingAverage:
def __init__(self, window_size):
self.window_size = window_size
self.window = deque()
self.total = 0
def add(self, value):
self.window.append(value)
self.total += value
if len(self.window) > self.window_size:
…How to Build a Consumer Lag Gauge in Python
Simulate Kafka consumer lag with a Python class that tracks lag over time and reports health and averages.
import time
import random
from collections import deque
class ConsumerLagGauge:
"""Mock consumer lag gauge measuring how far behind a consumer is."""
def __init__(self, producer_rate=10, consumer_rate=7, initial_lag=0):
self.producer_rate = producer_rate
self.consumer_rate = consumer_rate
…How to Process System Metrics (RSS, CPU) in Python
Simulate and aggregate RSS and CPU system metrics to compute averages and maximums for monitoring dashboards.
import random
import time
from collections import namedtuple
Metric = namedtuple("Metric", ["name", "value", "unit"])
def generate_metrics(num_metrics: int = 5) -> list:
"""Simulate a batch of system metrics."""
metrics = []
for i in range(num_metrics):
rss = random.randint(50, 500) # MB
…Track Success Rates and Latency in Python: SRE Metrics Helper
A beginner-friendly Python class to record request outcomes and latencies, then report success rate, average latency, and p99.
import random
import time
from collections import defaultdict
class MetricsTracker:
"""Simple helper to track success rates and latencies for SRE beginners."""
def __init__(self):
self.successes = 0
self.failures = 0
self.latencies = []
def record(self, success, latency_ms):
…Sliding Window Streaming Mock in Python
A simple Python class that maintains a sliding window of recent streaming values and computes the running average.
import time
import random
class StreamingMock:
"""Produces a stream of numbers using a sliding window."""
def __init__(self, window_size=5):
self.window = []
self.window_size = window_size
def push(self, value):
"""Add a value, sliding the window forward."""
s…How to Calculate Weighted Grades and Generate Mock Notes in Python
Compute a weighted physics grade from exam and homework scores, then generate a performance-based mock note with percentage and feedback.
def get_physics_grade(exam_score, homework_score):
"""Calculate final grade from exam and homework scores."""
exam_weight = 0.7
homework_weight = 0.3
return (exam_score * exam_weight) + (homework_score * homework_weight)
def mock_note(correct_score, max_score, student_name):
"""Generate a mock no…How to Build a Synthetic Monitor Mock in Python
Simulates a synthetic monitoring system in Python that collects latency samples, averages them, and reports service status as UP or DEGRADED.
import random
import time
from dataclasses import dataclass, field
from statistics import mean
@dataclass
class SyntheticMonitor:
service: str
endpoint: str
latency_ms: list[float] = field(default_factory=list)
def check(self) -> float:
latency = random.uniform(50.0, 250.0)
self.late…Browse by section
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