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Dict Comprehension to Map Keys to Lengths in Python
Build a dictionary that maps each word to its character count using a dictionary comprehension.
words = ["apple", "banana", "cherry", "date", "elderberry"]
word_lengths = {word: len(word) for word in words}
print(word_lengths)How to Build a Backpressure Generator Pause Producer Demo in Python
Demonstrates a producer–consumer pattern with a fixed-size buffer that pauses production when full, simulating backpressure.
import time
import collections
def producer(buffer, max_size, items):
"""Adds items to the buffer until full, then pauses."""
for item in items:
while len(buffer) >= max_size:
print(f"Buffer full ({len(buffer)}/{max_size}) — producer paused")
time.sleep(0.1)
buffer.appe…How to Build a Sliding Window Generator in Python
Create a generator that yields fixed-size overlapping slices of a sequence, useful for efficient windowed iteration.
def sliding_window(sequence, size):
for i in range(len(sequence) - size + 1):
yield sequence[i:i + size]
if __name__ == "__main__":
data = [1, 2, 3, 4, 5]
n = 3
for window in sliding_window(data, n):
print(window)How to Create a Pairwise Generator with zip and tee in Python
Build a memory-efficient generator that yields successive overlapping pairs from any iterable using zip and tee.
from itertools import tee
def pairwise(iterable):
"""Yield successive overlapping pairs from iterable."""
a, b = tee(iterable)
next(b, None)
return zip(a, b)
if __name__ == "__main__":
values = [1, 2, 3, 4, 5]
print(list(pairwise(values)))
print(list(pairwise("hello")))How to Create an Infinite Arithmetic Sequence Generator in Python
Build a memory-efficient generator that yields an infinite arithmetic progression and extract the first N values with list comprehension.
"""Count generator infinite arithmetic progression"""
def arithmetic_counter(start=0, step=1):
"""Generate an infinite arithmetic sequence."""
current = start
while True:
yield current
current += step
if __name__ == "__main__":
counter = arithmetic_counter(1, 3)
result = [next(c…How to Generate Fibonacci Numbers in Python Without Recursion
Build an efficient infinite Fibonacci sequence using a generator function with O(1) memory and no recursion overhead.
def fib(n):
a, b = 0, 1
for _ in range(n):
yield a
a, b = b, a + b
if __name__ == "__main__":
count = 10
result = list(fib(count))
print(result)How to Repeat a Generator Cycle Single Value in Python
Build a generator that repeats a single value across multiple cycles, each cycle adding an extra repetition to mark its completion.
def repeat_with_cycle(value, cycle_limit, repetitions):
"""
Repeats a single value until reaching a cycle limit,
then yields the value one more time to demonstrate a full cycle.
Args:
value: The single value to repeat.
cycle_limit: Number of repetitions per cycle.
repetitio…How to filter even numbers with a Python list comprehension
Build a new list of only the even numbers from 1 to 20 using a single list comprehension with a filter condition.
even_numbers = [num for num in range(1, 21) if num % 2 == 0]
print(even_numbers)Write Data Helpers with Comprehensions and Generators in Python
Demonstrates list, dict, and set comprehensions plus generator expressions and generator functions for building concise data helpers.
# Basic comprehensions and generators demo
# List comprehension: squares of evens
squares = [x * x for x in range(10) if x % 2 == 0]
print("List comp:", squares)
# Dictionary comprehension: char -> count
text = "hello"
char_counts = {c: text.count(c) for c in set(text)}
print("Dict comp:", char_counts)
# Set compre…How to Append Few-Shot Examples to a Prompt in Python
This code builds a complete LLM prompt by appending few-shot examples in alternating user/assistant format using a simple loop.
def append_few_shot_examples(prompt: str, examples: list[tuple[str, str]], separator: str = "\n\n") -> str:
"""Append few-shot examples to a prompt in alternating user/assistant format."""
full_prompt = prompt
for user_input, assistant_output in examples:
full_prompt = f"{full_prompt}{separator}Use…How to Build a Data Helper for LLM Prompts in Python
A beginner-friendly helper class that flattens nested dictionaries, formats prompt templates, and safely parses JSON for AI/LLM pipelines.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Simple helper class for working with data in AI/LLM pipelines."""
def __init__(self, data: Optional[Dict[str, Any]] = None) -> None:
self.data = data or {}
def flatten(self, prefix: str = "") -> Dict[str, Any]…How to Build a Prompt Template with Variable Slots in Python
Create a reusable LLM prompt template with named variable slots using Python's string.Template class and fill them with render() calls.
from string import Template
class PromptTemplate:
def __init__(self, template_text):
self.template = Template(template_text)
def render(self, **kwargs):
return self.template.substitute(**kwargs)
if __name__ == "__main__":
template = PromptTemplate(
"You are a helpful assistant …How to Build a Simple Semantic Cache for Similar Prompts in Python
Mock a semantic cache that finds the closest matching prompt using word-overlap similarity and returns cached results above a threshold.
prompt_cache = [
"What is the capital of France?",
"How does recursion work?",
"Best practices for Python logging?",
"Explain binary search in one line.",
"How to reverse a string in Python?"
]
def normalize(text):
return " ".join(text.lower().split())
def similarity(a, b):
a_words = set(…How to Build a System-User-Assistant Message List in Python
Use dataclasses to model a chat conversation and build the system/user/assistant message list expected by LLM APIs.
from dataclasses import dataclass, field
from typing import List
@dataclass
class Message:
role: str
content: str
@dataclass
class Conversation:
messages: List[Message] = field(default_factory=list)
def add_system(self, content: str) -> None:
self.messages.append(Message(role="system", con…How to Build a Zero-Shot Classification Prompt in Python
Creates a prompt for zero-shot text classification by pairing input text with candidate labels and a hypothesis template.
from typing import Dict, List
def build_zero_shot_prompt(
text: str,
candidate_labels: List[str],
hypothesis_template: str = "This is about {}.",
) -> Dict[str, List[str]]:
"""Build a prompt ready for zero-shot classification."""
return {
"sequences": text,
"candidate_labels": can…How to Build an Agent Loop with Plan, Act, Observe in Python
Implements a simple plan-act-observe loop that an AI agent uses to iteratively complete a task in an environment while storing observations in memory.
class Agent:
def __init__(self, name):
self.name = name
self.memory = {}
def plan(self, task):
return f"Plan for {task}: step 1, step 2, step 3"
def act(self, plan, environment):
return f"Executing {plan} in {environment}"
def observe(self, action_result):
sel…How to Build an Entity Memory Dict to Store Facts in Python
Store and recall facts about entities using nested dictionaries with remember, recall, and forget functions in Python.
facts = {}
def remember(entity, attribute, value):
if entity not in facts:
facts[entity] = {}
facts[entity][attribute] = value
def recall(entity, attribute):
return facts.get(entity, {}).get(attribute, None)
def forget(entity, attribute=None):
if attribute is None:
facts.pop(entity, …How to Build an In-Memory Vector Store in Python
Build a lightweight in-memory vector store using a Python dict and cosine similarity for fast nearest-neighbor searches.
import math
from typing import Dict, List, Optional
class InMemoryVectorStore:
def __init__(self) -> None:
self.vectors: Dict[str, List[float]] = {}
self.index: Dict[str, List[str]] = {} # query -> list of ids sorted by similarity
def add(self, vector_id: str, vector: List[float]) -> None:
…How to build a function calling schema dict in Python
Build an OpenAI-compatible function calling schema dictionary with a helper function that takes name, description, parameters, and required fields.
import json
from typing import Dict, Any, List, Optional
def build_function_schema(
name: str,
description: str,
parameters: Optional[Dict[str, Any]] = None,
required: Optional[List[str]] = None
) -> Dict[str, Any]:
"""Build an OpenAI-compatible function calling schema dictionary."""
schema: …How to build a mock RAG pipeline in Python
Build a minimal Retrieval-Augmented Generation pipeline that retrieves the best-matching document by keyword overlap and generates a template-based answer.
def simple_rag_pipeline(question, documents):
"""
A minimal mock RAG pipeline: retrieve relevant context, then generate an answer.
"""
# Step 1: Retrieve — mock retrieval by simple keyword scoring
scores = []
for doc in documents:
doc_words = set(doc.lower().split())
question_wo…Prepare LLM prompt data with a Python helper class
A beginner-friendly Python class that collects records, converts them to JSON, and produces a quick summary for building LLM prompt context.
import json
from typing import Any, Dict, List
class DataHelper:
"""Simple helper to prepare data for LLM prompts."""
def __init__(self):
self.data = []
def add(self, item: Dict[str, Any]) -> "DataHelper":
self.data.append(item)
return self
def to_json(self) -> s…Build a Command-Line Password Generator in Python
Generate cryptographically strong random passwords using Python's secrets module and print them for command-line use.
import secrets
import string
def generate_password(length=16):
"""Generate a cryptographically strong random password."""
alphabet = string.ascii_letters + string.digits + string.punctuation
password = ''.join(secrets.choice(alphabet) for _ in range(length))
return password
if __name__ == "__main__":…Build a Complete Web Scraper with Requests and BeautifulSoup in Python
Scrape multiple paginated pages from a website using Requests and BeautifulSoup, with retry logic, error handling, and CSV export.
import requests
from bs4 import BeautifulSoup
import csv
import time
from typing import List, Dict, Optional
class WebScraper:
def __init__(self, base_url: str, output_file: str = "scraped_data.csv"):
self.base_url = base_url
self.output_file = output_file
self.session = requests.Session()…Build a Complete Website Sitemap Generator Without External Services
Crawl a website recursively using only Python's standard library to generate a structured sitemap of internal links.
import json
from urllib.parse import urlparse, urljoin
from collections import deque
import urllib.request
import urllib.error
import re
from html.parser import HTMLParser
class SitemapParser(HTMLParser):
def __init__(self, base_url):
super().__init__()
self.base_url = base_url
self.links …Browse by section
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