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How to Use List Comprehensions and Generators in Python
Analyze a list of numbers using a list comprehension to square evens, a generator for sum, and a generator expression for the maximum squared value.
def analyze_numbers(numbers):
squared = [n ** 2 for n in numbers if n % 2 == 0]
total = sum(n for n in numbers)
max_squared = max((n ** 2 for n in numbers), default=0)
return squared, total, max_squared
if __name__ == "__main__":
data = [1, 2, 3, 4, 5, 6]
evens_squared, total_sum, max_sq = an…Normalize Data in Python with Comprehensions and Generators
Clean a list by dropping None values with a comprehension, then min-max normalize it using a lazy generator expression — a beginner-friendly data preparation pattern.
import statistics
# Sample raw data including missing and outlier-ish values
raw = [22, 18, None, 25, 30, 19, 22, 17, None, 28, 24]
# Clean the data: drop None values using a list comprehension
clean = [x for x in raw if x is not None]
# Normalize using min-max scaling with a generator expression
min_val = min(clea…How to Keep Last K Turns in a Memory Buffer in Python
A TurnBuffer class using deque with maxlen to keep only the most recent k conversation turns in memory for LLM context.
from collections import deque
class TurnBuffer:
def __init__(self, k):
self.k = k
self.turns = deque(maxlen=k)
def add(self, turn):
self.turns.append(turn)
def last_k(self):
return list(self.turns)
if __name__ == "__main__":
buffer = TurnBuffer(3)
buffer.add("tu…How to Truncate Text to a Token Budget in Python
Truncate a string to a maximum token budget for LLM context using the tiktoken library and OpenAI's tokenizer.
import tiktoken
def truncate_to_token_budget(text, max_tokens, model="gpt-3.5-turbo"):
enc = tiktoken.encoding_for_model(model)
tokens = enc.encode(text)
if len(tokens) <= max_tokens:
return text
truncated_tokens = tokens[:max_tokens]
return enc.decode(truncated_tokens)
if __name__ == "__…How to Generate Thumbnails While Maintaining Aspect Ratio in Python
Resize images to fit within maximum dimensions while preserving the original aspect ratio using Pillow (PIL).
from PIL import Image
def thumbnail_with_aspect_ratio(image_path, output_path, max_width, max_height):
with Image.open(image_path) as img:
# Get original dimensions
width, height = img.size
# Calculate scaling ratio to fit within max dimensions
ratio = min(max_width / width, max_h…How to Mock Auto Scaling Policy Scale Out in Python
Define a mock auto-scaling function that scales out capacity by a factor up to a max, simulating AWS-like events.
def mock_scale_out(current_capacity: int, max_capacity: int, scale_factor: int = 1) -> tuple:
"""
Mock auto-scaling policy: scales out by the specified factor
if capacity allows, capped at max_capacity.
"""
if current_capacity >= max_capacity:
return current_capacity, False
new_cap…Fixed Window Counter Rate Limiting in Python
A simple fixed window counter rate limiter that allows a maximum number of requests per 60-second window, with a mock time simulation.
from collections import deque
from time import time
class FixedWindowCounter:
def __init__(self, max_requests):
self.max_requests = max_requests
self.window_start = int(time())
self.window_count = 0
def allow_request(self):
current_time = int(time())
if current_time >=…How to Implement a Rate Limiter in Python
A beginner-friendly Python class that tracks call timestamps with a deque to allow or block calls based on a max rate per time period.
import time
from collections import deque
class RateLimiter:
"""Simple rate limiter for beginners."""
def __init__(self, max_calls: int, period_seconds: float):
self.max_calls = max_calls
self.period = period_seconds
self.calls = deque()
def allow(self) -> bool:
"""Retur…How to implement rate limiting in Python
Build a simple sliding-window rate limiter in Python that enforces a max number of calls per time period and formats data with timestamps.
import time
class RateLimiter:
def __init__(self, max_calls, period):
self.max_calls = max_calls
self.period = period
self.calls = []
def allow(self):
now = time.time()
# Remove calls older than the period window
self.calls = [t for t in self.calls if now -…Rate Limit per User ID in Python with a Dict Mock
Implements a simple sliding window rate limiter using a defaultdict of timestamps per user ID, blocking requests that exceed a max count within a time window.
import time
from collections import defaultdict
class RateLimiter:
def __init__(self, max_requests, window_seconds):
self.max_requests = max_requests
self.window_seconds = window_seconds
self.user_timestamps = defaultdict(list)
def allow_request(self, user_id):
now = time.tim…Rate Limiting with a Simple Python RateLimiter Class
A beginner-friendly Python rate limiter that tracks call timestamps and enforces a maximum number of calls within a rolling time window, with a helper to validate positive integers.
import time
class RateLimiter:
def __init__(self, max_calls, period_seconds):
self.max_calls = max_calls
self.period_seconds = period_seconds
self.calls = []
def is_allowed(self):
now = time.time()
while self.calls and now - self.calls[0] >= self.period_seconds:
…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
…How to Mock a Kubernetes Rolling Update with maxSurge in Python
Simulate a Kubernetes rolling update with maxSurge policy, tracking peak and final replica counts during roll transitions.
from collections import deque
class RollingUpdateMaxSurge:
def __init__(self, replicas, max_surge):
self.replicas = replicas
self.max_surge = max_surge
self.available = replicas
self.history = deque()
def roll(self, desired_replicas):
"""
Simulate a rolling upd…PodDisruptionBudget minAvailable in Python
Simulate a Kubernetes PodDisruptionBudget check for minAvailable and maxUnavailable constraints with a Python class.
class PodDisruptionBudget:
def __init__(self, name, min_available=None, max_unavailable=None):
self.name = name
self.min_available = min_available
self.max_unavailable = max_unavailable
def check_availability(self, ready_pods):
if self.min_available is not None:
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