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Create an In-Memory SQLite Table and Query It in Python
This code creates an in-memory SQLite database, defines an employees table, inserts sample rows, and runs a filtered query with sorted results.
import sqlite3
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
employees = [
(1, "Alice", "Engineering", 95000),
(2, "Bob", "…
Export SQLite Query Results to CSV in Python
Connects to a SQLite database, runs a query, and writes the result rows and column headers to a CSV file using the standard library.
import sqlite3
import csv
def export_query_to_csv(db_path, query, csv_path):
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
cursor.execute(query)
rows = cursor.fetchall()
column_names = [description[0] for description in cursor.description]
with open(csv_path, 'w', newline='', encodi…
How to Bulk Insert Rows into SQLite in Python
Insert many rows into an SQLite table in one call with cursor.executemany, then verify them with a SELECT query.
import sqlite3
# Create an in-memory database and a table
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("CREATE TABLE products (name TEXT, price REAL, quantity INTEGER)")
# Data to insert in bulk
products = [
("Laptop", 999.99, 5),
("Mouse", 19.99, 50),
("Keyboard", 49.99, 30),…
Parameterize SQL queries in Python to prevent SQL injection
Safely fetch users from a SQLite database using parameterized queries to prevent SQL injection attacks.
import sqlite3
def get_users_by_name(name):
"""Fetch users safely using parameterized query."""
conn = sqlite3.connect(':memory:')
cursor = conn.cursor()
# Create sample table and data
cursor.execute('CREATE TABLE users (id INTEGER, name TEXT)')
cursor.executemany('INSERT INTO users (name…
Read SQLite database with sqlite3 module in Python
Connect to a SQLite database and query rows with the standard library sqlite3 module, returning results as dictionaries.
import sqlite3
from pathlib import Path
# Create an in-memory database and a sample table
connection = sqlite3.connect(":memory:")
cursor = connection.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
department TEXT NOT NULL,
salary REAL
)
""")
# Inser…
How to Parse Query String to Dict with Duplicate Keys in Python
Convert a URL query string into a Python dictionary, merging duplicate keys into lists while keeping single values as scalars.
from urllib.parse import parse_qs
def parse_query_to_dict(query_string):
parsed = parse_qs(query_string, keep_blank_values=True)
return {key: values if len(values) > 1 else values[0] for key, values in parsed.items()}
if __name__ == "__main__":
query = "name=John&name=Jane&age=30&city=&city=Paris&empty…
How to Serialize a Dictionary to a Query String in Python
Convert a Python dictionary into a URL-encoded query string using the standard library's urllib.parse.urlencode function.
import urllib.parse
def dict_to_query_string(params):
"""Serialize a dictionary to a URL query string."""
return urllib.parse.urlencode(params)
if __name__ == "__main__":
data = {
"name": "Alice Johnson",
"age": 30,
"city": "New York",
"interests": ["coding", "hiking"]
…
Graph Class with Adjacency Dict in Python
Build an undirected graph class using a dictionary of adjacency lists with methods to add vertices, edges, remove edges, and query neighbors.
class Graph:
def __init__(self):
self.adjacency = {}
def add_vertex(self, vertex):
if vertex not in self.adjacency:
self.adjacency[vertex] = []
def add_edge(self, u, v):
self.add_vertex(u)
self.add_vertex(v)
self.adjacency[u].append(v)
self.adja…
Cosine Similarity to Retrieve Top K Chunks in Python
Compute cosine similarity between a query vector and a list of chunk vectors, then return the indices and scores of the top k most similar chunks.
import numpy as np
from numpy.linalg import norm
def cosine_similarity(vec1, vec2):
return np.dot(vec1, vec2) / (norm(vec1) * norm(vec2))
def retrieve_top_k(query_vec, chunk_vectors, k=3):
similarities = [cosine_similarity(query_vec, vec) for vec in chunk_vectors]
top_indices = sorted(range(len(similarit…
How to Mock DynamoDB with a Simple Dict Store in Python
A lightweight in-memory DynamoDB mock that stores items in a dict and supports put, get, and query-by-value operations for local testing.
import json
from typing import Any, Dict, Optional
class MockDynamoDB:
def __init__(self) -> None:
self._store: Dict[str, Dict[str, Any]] = {}
def put_item(self, table_name: str, item: Dict[str, Any]) -> None:
key = str(item.get("id"))
if table_name not in self._store:
se…
How to Implement CQRS with Separate Read and Write Models in Python
Implements Command Query Responsibility Segregation (CQRS) by splitting data into separate write and read models with dedicated repositories, using dataclasses for structure.
from dataclasses import dataclass, field
from typing import List, Dict, Optional
@dataclass
class OrderWriteModel:
order_id: int
customer: str
items: List[str] = field(default_factory=list)
def add_item(self, item: str) -> None:
self.items.append(item)
@dataclass
class OrderReadModel:
…
How to Filter Query Parameters by Operator in Python
Parse a URL query string and keep only parameters with allowed comparison operators like eq, gt, and lt.
from urllib.parse import urlparse, parse_qs
def filter_operators(query_string, allowed=("eq", "gt", "lt")):
parsed = urlparse(query_string)
params = parse_qs(parsed.query)
filtered = {}
for key, values in params.items():
if "__" in key:
field, op = key.rsplit("__", 1)
i…
How to Implement Pagination with Offset and Limit in Python
A mock API pagination pattern that parses page and per_page query parameters, computes offset and limit, and slices a list of items for a specific page.
def paginate(items, page, per_page):
offset = (page - 1) * per_page
return items[offset:offset + per_page]
def parse_query_params(query_string):
params = {}
if query_string:
for pair in query_string.split("&"):
key, value = pair.split("=")
params[key] = value
page …
How to Mock a GraphQL Query Type in Python
Create a lightweight mock of a GraphQL Query type to simulate repository lookups without a server.
import json
class Query:
def __init__(self):
self.starred_repos = [
{"id": 1, "name": "graphql", "owner": "graphql"}
]
def repository(self, name):
if name == "graphql":
return {"id": 1, "name": "graphql", "stargazerCount": 85000}
return None
if __name…
Sort Python list by query param order_by
Sort a list of dataclass objects dynamically by a field name passed as a query param, with asc/desc direction support.
from dataclasses import dataclass
@dataclass
class Item:
name: str
price: int
def sort_items(items, order_by, direction="asc"):
if order_by not in ("name", "price"):
raise ValueError(f"Unsupported sort field: {order_by}")
reverse = direction.lower() == "desc"
return sorted(items, key=l…
How to Mock Database Query Duration in Python
Simulate realistic database query durations with random jitter for testing dashboards, alerts, and SLO calculations.
import random
import time
def mock_query_duration(db_name, avg_ms, jitter_ms=5, runs=3):
"""Simulate database query durations with realistic variation."""
durations = []
for _ in range(runs):
# Base duration plus random jitter (can be negative)
duration = avg_ms + random.uniform(-jitter_m…
How to Mock a Catalyst Logical Plan in Python
Build a small Python class that mimics Spark Catalyst's logical plan tree for teaching or testing query optimizations.
from typing import Any, Dict, List, Optional
class CatalystLogicalPlan:
"""A minimal mock of Catalyst's logical plan for teaching purposes."""
def __init__(self, node_type: str, **kwargs: Any) -> None:
self.node_type = node_type
self.attributes: Dict[str, Any] = kwargs
self.child…
Mock Predicate Pushdown in Python for Big Data Queries
Simulate predicate pushdown by applying filters at the storage layer before materializing rows, showing how big data engines optimize queries.
class Query:
def __init__(self, table, rows):
self.table = table
self.rows = rows
def filter(self, predicate):
return Query(
self.table,
[row for row in self.rows if all(predicate(row) for predicate in predicate)]
)
def filter_pushdown(self, predica…
Composite index leftmost prefix in Python
Simulate a composite index in SQLite and check whether query columns match the leftmost prefix rule for index usage.
import sqlite3
def get_indexed_columns(table_name):
"""Simulate a composite index by reading column names that start with 'idx_'."""
conn = sqlite3.connect(":memory:")
conn.execute(f"CREATE TABLE {table_name} (id INTEGER, idx_col1 TEXT, idx_col2 INTEGER, other TEXT)")
conn.execute(f"CREATE INDEX idx_…
Cross Shard Query Scatter Gather Mock in Python
Simulate a distributed database cross-shard query using a scatter-gather pattern with a mock Python implementation.
from dataclasses import dataclass
from typing import List, Dict
@dataclass
class NodeResponse:
node_id: int
data: Dict[str, float]
def mock_query_shard(shard_id: int, shard_data: Dict[str, float], query: str) -> NodeResponse:
"""Simulate querying a single shard, returning matches whose value > 50."""
…
Database indexing and query timing optimization in Python
Create SQLite indexes and time query performance to measure speedup for large table lookups in Python.
import sqlite3
import time
def time_query(db_path, query, params=()):
conn = sqlite3.connect(db_path)
conn.execute("PRAGMA journal_mode = WAL")
start = time.perf_counter()
result = conn.execute(query, params).fetchall()
elapsed = time.perf_counter() - start
conn.close()
return result, ela…
How to Create a Covering Index with INCLUDE Columns in Python
Create a covering index with INCLUDE columns in SQLite from Python and inspect the query plan to confirm the index covers the query.
import sqlite3
def create_covering_index_mock():
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE employees (
id INTEGER PRIMARY KEY,
name TEXT,
department TEXT,
salary INTEGER
)
""")
employe…
How to Eager Load with JOIN to Reduce N+1 Queries in Python
Demonstrates eager loading with a SQL JOIN to reduce N+1 query patterns down to a single database call when fetching related data.
import sqlite3
def eager_load_join_reduce(mock_db_path=":memory:"):
"""Demonstrate eager loading where joins reduce query count from N+1 to 1."""
conn = sqlite3.connect(mock_db_path)
cursor = conn.cursor()
cursor.executescript(
"""
CREATE TABLE authors (id INTEGER PRIMARY KEY, name TE…
How to Explain SQLite Query Plans in Python
Build a Python function that runs EXPLAIN QUERY PLAN on SQLite in-memory tables and prints the optimizer's execution plan for any SELECT statement.
import sqlite3
def explain_query(sql: str) -> str:
"""Return the SQLite query plan for the given SQL statement."""
conn = sqlite3.connect(":memory:")
cursor = conn.cursor()
# Create sample data for a realistic plan
cursor.execute("CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)")
c…
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