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Python Code Samples

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17 matches
Strings & text easy

How to Merge Strings in Python

Merge multiple strings or a list of text lines into one string with a custom separator

strings join merging
Python
def merge_strings(*parts, separator=" "):
    """Merge multiple string parts into one string with a separator."""
    return separator.join(parts)


def merge_text_lines(lines, separator="\n"):
    """Merge a list of text lines into a single string."""
    return separator.join(lines)


if __name__ == "__main__":
    …
15 0 Open
Strings & text easy

How to Parse and Clean Text in Python

This code defines three helper functions to parse text into lowercase words, count unique word frequencies, and clean text by removing punctuation and extra whitespace.

text parsing string cleaning word frequency
Python
def extract_words(text: str) -> list[str]:
    """Return a list of lowercase words from the given text."""
    return [word.lower() for word in text.split() if word.isalpha()]


def count_unique_words(text: str) -> dict[str, int]:
    """Return a dictionary with unique words and their frequencies."""
    words = extra…
11 0 Open
Strings & text easy

String helpers in Python: stats, reverse, and remove vowels

Three beginner-friendly Python functions compute text statistics, reverse word order, and strip vowels from a string.

string-manipulation text-stats vowel-removal
Python
def text_stats(text: str) -> dict:
    """Return basic statistics for a given text string."""
    words = text.split()
    return {
        "characters": len(text),
        "words": len(words),
        "sentences": text.count(".") + text.count("!") + text.count("?"),
        "uppercase": sum(1 for c in text if c.isupp…
14 0 Open
Files & data easy

File Data Helper Functions in Python

Read and write text and JSON files, and list files in a directory, using pathlib-based helper functions.

file-io pathlib json
Python
from pathlib import Path

def load_text_file(filepath):
    """Read a text file and return its contents as a string."""
    path = Path(filepath)
    if not path.exists():
        raise FileNotFoundError(f"File not found: {filepath}")
    return path.read_text(encoding="utf-8")

def save_text_file(filepath, content):
…
14 0 Open
Files & data easy

How to Read and Write Files in Python (JSON + Text)

A beginner-friendly helper module to read and write JSON and text files using Python's pathlib and json standard library modules.

json file-io pathlib
Python
import json
from pathlib import Path


def load_json_file(filepath):
    """Load data from a JSON file and return as dict/list."""
    path = Path(filepath)
    with path.open("r", encoding="utf-8") as f:
        return json.load(f)


def save_json_file(filepath, data):
    """Save data to a JSON file."""
    path = P…
14 0 Open
Dictionaries & sets easy

Convert Lists and Dictionaries to Sets in Python

Convert lists of pairs into dictionaries and lists or dictionaries into sets using simple helper functions.

dict set conversion
Python
def convert_to_dict(data):
    """Convert list of tuples or lists into a dictionary."""
    return dict(data)


def convert_to_set(data):
    """Convert list or dictionary into a set of its keys/values."""
    if isinstance(data, dict):
        return set(data.keys())
    return set(data)


def convert_collection(data…
14 0 Open
Comprehensions & generators easy

How to Filter Data with Predicates in Python

This helper filters a list with a predicate using a list comprehension, plus a lazy generator version that yields matches one by one.

filtering comprehensions generators
Python
def filter_data(data, predicate):
    """Return a list containing only items that pass the predicate."""
    return [item for item in data if predicate(item)]


def filter_data_lazy(data, predicate):
    """Generator version: yields items that pass the predicate one by one."""
    for item in data:
        if predicat…
16 0 Open
Comprehensions & generators easy

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.

comprehensions generators data-helpers
Python
# 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…
10 0 Open
Data pipelines & processing easy

Create Data Helper Functions in Python for Beginners

Build reusable Python helper functions to load, filter, sort, summarize, and save JSON data — a beginner-friendly starting point for small data pipelines.

json pipeline helpers
Python
import json
from pathlib import Path
from typing import Any, Dict, List


def load_json_file(filepath: str) -> Dict[str, Any]:
    """Load JSON data from a file."""
    with Path(filepath).open("r", encoding="utf-8") as file:
        return json.load(file)


def filter_by_key(
    data: List[Dict[str, Any]], key: str,…
14 0 Open
Cloud + Python easy

How to Validate Data Fields and Types in Python

Validate required fields and type correctness in a Python dictionary with small helper functions, returning a list of clear error messages.

validation data dict
Python
import json
from typing import Any, Dict, List


def validate_data(data: Dict[str, Any], required_fields: List[str]) -> List[str]:
    """Check required fields exist and are non-empty. Return list of errors."""
    errors = []
    for field in required_fields:
        value = data.get(field)
        if value is None o…
13 0 Open
Modern tooling easy

Data Conversion Helper Functions in Python

A set of beginner-friendly helper functions to convert between JSON strings and Python data, parse dates, and read/write files using pathlib.

json datetime pathlib
Python
from datetime import datetime
from pathlib import Path
import json

def to_json(data, indent=2):
    """Convert Python data to pretty-printed JSON string."""
    return json.dumps(data, indent=indent, default=str)

def from_json(json_string):
    """Parse JSON string back into Python data."""
    return json.loads(jso…
12 0 Open
Modern tooling easy

How to Format Data with Python's datetime and JSON Helpers

A beginner-friendly set of helper functions to format dates and safely read/write JSON files in Python.

datetime json files
Python
from datetime import datetime
from pathlib import Path
import json


def format_today(pattern: str = "%Y-%m-%d") -> str:
    """Return today's date formatted with the given pattern."""
    return datetime.now().strftime(pattern)


def load_json(file_path: str) -> dict:
    """Read and parse a JSON file safely."""
    …
12 0 Open
Modern tooling easy

How to Load and Inspect Data Files in Python

A beginner-friendly DataLoader dataclass that loads JSON or text files and provides methods to preview and inspect the data.

dataclasses file-io json
Python
from dataclasses import dataclass, field
from pathlib import Path
import json
from typing import Any, Dict, List


@dataclass
class DataLoader:
    """Simple helper to load and inspect data files for beginners."""
    path: Path
    data: Any = field(init=False, default=None)

    def __post_init__(self) -> None:
    …
15 0 Open
Testing & modern typing easy

Design Data Helpers with Python TypedDict and Literal

Use TypedDict, Literal, and Union to define typed data shapes and parse values in Python.

typeddict literal union
Python
from typing import TypedDict, Literal, Optional, Union, List

class User(TypedDict):
    name: str
    age: int
    role: Literal["admin", "user", "guest"]

def describeUser(data: User) -> str:
    return f"{data['name']} ({data['age']}) — {data['role']}"

def parse_value(item: Union[int, str, None]) -> str:
    if it…
12 0 Open
Testing & modern typing easy

How to Sort Data in Python

Sort sequences with type-safe helpers that handle mixed data with a string fallback.

sorting typing protocol
Python
from typing import Any, TypeVar, Protocol, Sequence, Iterable

T = TypeVar("T")
Comparable = TypeVar("Comparable", bound="Comparable")

class Sortable(Protocol):
    def __lt__(self, other: Any) -> bool: ...

S = TypeVar("S", bound=Sortable)

def sort_data(data: Sequence[S], *, reverse: bool = False) -> list[S]:
    "…
14 0 Open
ML engineering pipelines easy

How to Load, Save, and Split JSON Data in Python

Provides helper functions to load, save, and split JSON dictionary data for simple ML pipeline preprocessing.

json data-splitting ml-pipeline
Python
import json
from pathlib import Path


def load_json_data(file_path):
    """Load JSON data from a file, returning an empty dict if missing."""
    path = Path(file_path)
    if path.exists():
        with path.open("r", encoding="utf-8") as f:
            return json.load(f)
    return {}


def save_json_data(data, f…
13 0 Open
Production deployment patterns easy

How to Build a Simple Data Helper Class in Python

A beginner-friendly DataHelper class that stores Python dataclass objects as JSON records to disk, with load, add, and save methods.

dataclass json file-io
Python
import json
from dataclasses import dataclass, asdict
from pathlib import Path

@dataclass
class User:
    name: str
    age: int
    email: str

class DataHelper:
    def __init__(self, filepath: str = "data.json"):
        self.filepath = Path(filepath)
        self._data = self._load()
    
    def _load(self) -> l…
12 0 Open

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Guide: free Python code samples library

Copy-ready Python snippets for learners and developers

PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.

How to use this library

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.