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Python Code Samples

Easy snippets you can copy, study, and run in the browser editor.

10 matches
Strings & text easy

How to Align Text in Two Columns with ljust in Python

Format pairs of strings into two aligned columns using ljust padding.

string-formatting ljust alignment
Python
items = [
    ("apple", "red"),
    ("banana", "yellow"),
    ("cherry", "dark red"),
    ("date", "brown")
]

col1_width = max(len(name) for name, _ in items) + 2

for name, color in items:
    print(name.ljust(col1_width) + color)
15 0 Open
Lists & loops easy

How to Transpose a Matrix in Python (List of Lists)

Swap rows and columns of a 2D list using nested loops to produce a transposed matrix.

matrix transpose 2d-list
Python
def transpose(matrix):
    # Number of rows and columns in the original matrix
    rows = len(matrix)
    cols = len(matrix[0]) if rows > 0 else 0
    
    # Create a new matrix with dimensions swapped
    result = []
    for j in range(cols):
        new_row = []
        for i in range(rows):
            new_row.appe…
13 0 Open
Data pipelines & processing easy

How to Unpivot Wide to Long with pandas melt in Python

This code demonstrates how to use pandas.melt to unpivot a wide DataFrame into a tidy long format, converting subject columns into rows.

pandas melt reshape
Python
import pandas as pd

# Sample wide-format data
df_wide = pd.DataFrame({
    'id': [1, 2, 3],
    'name': ['Alice', 'Bob', 'Charlie'],
    'math': [90, 85, 95],
    'science': [80, 92, 88]
})

print("Original wide DataFrame:")
print(df_wide)

# Melt: unpivot subject columns into rows
df_long = pd.melt(
    df_wide,
   …
15 0 Open
Data pipelines & processing easy

Union Multiple DataFrames with Aligned Columns in Python

Concatenate DataFrames with different columns, aligning them and filling missing values with NaN using pandas concat.

pandas dataframes concat
Python
import pandas as pd
from io import StringIO

# Sample dataframes with different columns
df1 = pd.DataFrame({
    'id': [1, 2, 3],
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 30, 35]
})

df2 = pd.DataFrame({
    'id': [4, 5],
    'name': ['Diana', 'Eve'],
    'city': ['NYC', 'LA']
})

df3 = pd.DataFrame({
…
14 0 Open
Big data & Spark easy

How to Filter and Project Spark DataFrames with PySpark SQL

Simulate a SQL SELECT with WHERE using PySpark DataFrame select and filter to project columns and apply conditions.

pyspark dataframe filter
Python
from pyspark.sql import SparkSession
from pyspark.sql.functions import col

spark = SparkSession.builder.appName("QueryFilterMock").master("local[2]").getOrCreate()

data = [
    ("Alice", 28, "Engineering"),
    ("Bob", 35, "Sales"),
    ("Carol", 32, "Engineering"),
    ("David", 25, "Marketing"),
    ("Eve", 29, "E…
14 0 Open
Big data & Spark easy

How to Mock DataFrame Schema Columns in Python

Create an empty pandas DataFrame with only the specified column names to mock a schema before any data is loaded.

pandas dataframe schema
Python
import pandas as pd

def mock_schema(columns):
    return pd.DataFrame(columns=columns)

if __name__ == "__main__":
    cols = ["name", "age", "city"]
    df = mock_schema(cols)
    print(df)
    print(f"Columns: {list(df.columns)}, Shape: {df.shape}")
14 0 Open
Big data & Spark easy

How to select specific columns in Python with SQLite

A reusable function that connects to a SQLite database and returns only the requested columns from a given table.

sqlite sql database
Python
import sqlite3

def select_pruned_columns(db_path, table, columns):
    with sqlite3.connect(db_path) as conn:
        cursor = conn.cursor()
        col_list = ", ".join(columns)
        query = f"SELECT {col_list} FROM {table}"
        return cursor.execute(query).fetchall()

if __name__ == "__main__":
    conn = sq…
15 0 Open
Big data & Spark easy

Modeling a Hive Metastore Table Schema in Python

A dataclass that mimics a Hive metastore table schema—columns, partition keys, storage format, and location—with helper methods for description and mutation.

hive dataclass metastore
Python
from dataclasses import dataclass, field
from typing import Dict, List, Optional


@dataclass
class HiveTable:
    """Simple mock of a Hive metastore table schema."""
    name: str
    database: str = "default"
    columns: List[Dict[str, str]] = field(default_factory=list)
    partition_keys: List[Dict[str, str]] = f…
14 0 Open
Database scaling & optimization easy

How to Avoid SELECT * and Mock SQL Column Queries in Python

Mock a SQLite cursor to verify that queries specify explicit columns instead of using SELECT *.

sqlite mock testing
Python
import sqlite3
from unittest.mock import Mock, patch


def get_user_emails(connection):
    """Fetch only the required columns instead of SELECT *."""
    cursor = connection.cursor()
    cursor.execute("SELECT email FROM users")
    return [row[0] for row in cursor.fetchall()]


def test_get_user_emails_specific_colu…
13 0 Open
Database scaling & optimization easy

How to enforce a unique index constraint in Python

Mock a database unique index in Python that rejects duplicate rows based on one or more columns.

database unique index constraint
Python
class MockIndex:
    def __init__(self, columns):
        self.columns = columns
        self._values = set()

    def insert(self, row):
        key = tuple(row[col] for col in self.columns)
        if key in self._values:
            raise ValueError(f"Duplicate key {key} for columns {self.columns}")
        self._v…
14 0 Open

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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.