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Python Code Samples

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42 matches
Comprehensions & generators easy

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.

list comprehension filtering even numbers
Python
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}")
13 0 Open
Comprehensions & generators easy

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.

dictionary-comprehension generator-expression data-merging
Python
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
    …
14 0 Open
AI & LLM integration patterns easy

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.

guardrails text-filtering llm-safety
Python
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.

…
12 0 Open
Automation & scripting easy

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.

csv logs report
Python
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_…
14 0 Open
Automation & scripting easy

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.

docker json datetime
Python
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…
13 0 Open
Automation & scripting easy

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.

github issues automation
Python
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…
35 0 Open
Data pipelines & processing easy

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.

pipeline json aggregation
Python
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…
10 0 Open
Data pipelines & processing easy

How to Filter Data in Python

Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.

filtering list-comprehension dictionaries
Python
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…
12 0 Open
Data pipelines & processing easy

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.

merge pipelines dicts
Python
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:
    …
14 0 Open
Cloud + Python easy

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.

ec2 mock aws
Python
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…
15 0 Open
Testing & modern typing easy

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.

filtering type-hints generics
Python
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…
11 0 Open
API design & gRPC easy

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.

dataclasses data-handling beginner
Python
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…
14 0 Open
API design & gRPC easy

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.

filtering dataclasses grpc
Python
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…
13 0 Open
API design & gRPC easy

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.

api jsonapi sparse-fieldsets
Python
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…
12 0 Open
Caching & Redis easy

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.

redis caching filtering
Python
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…
13 0 Open
Observability & SRE easy

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.

logging log-levels observability
Python
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…
13 0 Open
Big data & Spark easy

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.

spark partition dataclass
Python
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…
15 0 Open
Database scaling & optimization easy

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.

partial-index database mock
Python
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…
12 0 Open

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