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List Comprehension to Filter Even Numbers in Python
Creates a new list containing only the even numbers from an existing list using a list comprehension with a condition.
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = [n for n in numbers if n % 2 == 0]
print(f"Original: {numbers}")
print(f"Even numbers: {even_numbers}")
Merge Data with Comprehension and Generator in Python
Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.
def merge_data(users, orders):
"""
Merge user and order data using a dictionary comprehension
and a generator expression for filtering.
"""
# Build a lookup: user_id -> user name
user_map = {user["id"]: user["name"] for user in users}
# Generator: yield orders with user names attached
…
How to Filter Toxic Keywords in Python
Filter toxic keywords from text by replacing each occurrence with asterisks, useful as a basic guardrail for LLM inputs.
TOXIC_KEYWORDS = ["insult", "threat", "hate", "violence", "spam"]
def guardrails_filter(text: str, keywords: list[str] | None = None) -> str:
"""Filter out toxic keywords from the given text.
Args:
text: The input text to filter.
keywords: Optional keyword list. Defaults to TOXIC_KEYWORDS.
…
Generate a Monthly Report CSV from Log Files in Python
Reads a CSV log file, filters events by a given month, aggregates daily event counts and revenue, and writes a summarized monthly report to a new CSV.
import csv
from collections import defaultdict
from datetime import datetime
def generate_monthly_report(log_file: str, month: str, output_file: str) -> None:
events_by_date = defaultdict(int)
revenue_by_date = defaultdict(float)
with open(log_file, 'r') as f:
for line in f:
date_…
How to Filter Docker Containers for Pruning in Python
Simulate Docker's container prune by filtering a JSON list for exited containers older than a cutoff, returning pruned IDs and space freed.
import json
from datetime import datetime, timedelta
def parse_docker_ps(json_output: str, older_than_hours: int = 24) -> list:
containers = json.loads(json_output)
cutoff = datetime.now() - timedelta(hours=older_than_hours)
return [
c for c in containers
if datetime.fromisoformat(c["crea…
How to Find Stale GitHub Issues in Python
Filter a list of GitHub issues to find those not updated within a configurable number of days using Python datetime arithmetic.
import os
from datetime import datetime, timezone, timedelta
import re
# Simulated GitHub issue data structure
SAMPLE_ISSUES = [
{"number": 101, "title": "Login button not working", "updated_at": "2025-06-01T12:00:00Z", "assignee": "alice"},
{"number": 102, "title": "Fix database migration error", "updated_at…
How to Build a Simple Data Pipeline in Python
A beginner-friendly data pipeline that loads JSON, filters records by a field value, and aggregates counts per category.
import json
from pathlib import Path
def load_json(filepath: str | Path) -> list[dict]:
"""Load a JSON file containing a list of records."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def filter_records(records: list[dict], field: str, value) -> list[dict]:
"""Kee…
How to Filter Data in Python
Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.
from typing import List, Dict, Any
def filter_data(
data: List[Dict[str, Any]], key: str, value: Any
) -> List[Dict[str, Any]]:
"""Return records where data[key] equals value."""
return [record for record in data if record.get(key) == value]
def filter_by_range(
data: List[Dict[str, Any]], key: str…
How to Merge Multiple Data Sources in Python
A beginner-friendly helper that merges lists of dictionaries from multiple sources into one combined list using key filtering.
import json
def merge_pipeline_data(*data_sources, keys=()):
"""Merge multiple data sources (list of dicts) into a single list of merged dicts.
Args:
*data_sources: One or more lists of dictionaries.
keys: Tuple of keys to include from each source (empty means all keys).
Returns:
…
How to mock EC2 describe-instances tag filtering in Python
Simulate AWS EC2 describe-instances with tag-based filtering using a mock dataset and conditional list comprehension.
import json
from datetime import datetime, timezone
def mock_describe_instances(tag_key: str, tag_value: str) -> list[dict]:
"""Simulate EC2 describe-instances with tag filtering."""
all_instances = [
{"InstanceId": "i-0abc123", "State": "running", "Tags": [{"Key": "Name", "Value": "web-server"}, {"K…
How to Filter Data in Python with Type Hints
A reusable filter_data helper uses optional predicates and numeric bounds with modern Python type hints.
from typing import Iterable, TypeVar, Callable, Any
T = TypeVar("T")
def filter_data(
items: Iterable[T],
predicate: Callable[[T], bool] | None = None,
*,
min_value: float | None = None,
max_value: float | None = None,
) -> list[T]:
"""Filter items by predicate and/or numeric bounds."""
r…
How to Build a Data Helper Class in Python for Beginners
Create a beginner-friendly DataHelper class that stores, retrieves, filters, and summarizes records in a list of dictionaries.
from __future__ import annotations
import json
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
@dataclass
class DataHelper:
"""A beginner-friendly helper for common data tasks."""
data: List[Dict[str, Any]] = field(default_factory=list)
def add_record(self, record…
How to Build a Simple Filter Helper in Python for API Design
Create a reusable data filter service with dataclasses that mimics gRPC request/response patterns for filtering dataset records.
from dataclasses import dataclass, field
from typing import List, Optional, Dict, Any
@dataclass
class FilterRequest:
"""A simple filter request mirroring a gRPC message structure."""
field_name: str
operator: str # eq, ne, gt, lt, contains
value: Any
page_size: int = 10
page_token: Optional…
How to Implement Sparse Fieldsets in Python
A function that filters API responses by resource type, returning only requested fields plus IDs, as a sparse fieldset mock.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class MockResponse:
data: Dict[str, object] = field(default_factory=dict)
included: List[Dict[str, object]] = field(default_factory=list)
def select_fields(
data: Dict[str, object],
sparse_fields: Optional[D…
How to cache filtered data in Redis with Python
This code caches filtered list results in Redis using an MD5 hash key, returning cached results when available.
import redis
import json
import hashlib
import time
cache = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
def filter_data(data, predicate_key, predicate_value):
"""Filter a list of dicts by key-value pair, with Redis caching."""
cache_key = hashlib.md5(
f"{predicate_key}:{pred…
How to Use Log Levels DEBUG INFO WARNING ERROR in Python
Demonstrates Python's logging levels (DEBUG, INFO, WARNING, ERROR) with basicConfig and a logger, showing how severity filtering controls output.
import logging
# Configure a mock logger to demonstrate log levels
logging.basicConfig(level=logging.DEBUG, format="%(levelname)s: %(message)s")
logger = logging.getLogger("mock_logger")
# Simulate events at each severity level
logger.debug("Detailed diagnostic info")
logger.info("General system operation")
logger.w…
How to Mock Partition Pruning in Python
A dataclass-based mock that filters partitions by year and month to emulate Spark's partition pruning logic.
from dataclasses import dataclass
from typing import List
@dataclass(frozen=True)
class Partition:
id: int
year: int
month: int
class PartitionPruner:
"""Mock partition pruning: only keep partitions that match the filter."""
def __init__(self, partitions: List[Partition]):
self._partiti…
Build a Partial Index Mock in Python for Database Filtering
Simulate a partial database index by filtering keys with a predicate, then return a limited mock lookup dictionary.
data = [
"alpha", "beta", "gamma", "delta", "epsilon",
"zeta", "eta", "theta", "iota", "kappa"
]
filtered_keys = [item for item in data if len(item) >= 5]
def mock_partial_index(keys, filter_func, limit=3):
result = {}
for key in keys:
if not filter_func(key):
continue
res…
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