DEV Community: saba diasamidze

Finite sets from Python SymPy

saba diasamidze — Fri, 11 Jul 2025 17:38:57 +0000

Finite sets from Python SymPy

FiniteSet is a data structure from the Python sympy package. Today, we’ll talk about its unique functionality and use cases.

FiniteSet(n_1, n_2, n_3, ...) – function –

is_subset(x) – method –

is_superset(x) – method –

powerset() – method –

union(x) – method –

intersect(x) – method –

Cartesian product (*) – operator –

Use

Package
Before using any of the features, we need to import the sympy package. It’s a third-party library, so install it first using pip if you haven’t:

import sympy as sy

FiniteSet

To create a set:

a = sy.FiniteSet(1, 5.3, "hello", False)

FiniteSet works like a Python set, not a list. Unlike lists, it does not store duplicates:

# Normal list
a = [2, 2]
# SymPy set
b = sy.FiniteSet(2, 2)
print(a, b)  # Output: [2, 2] {2}

Subsets

a = sy.FiniteSet(1, 2, 3, 4, 5)
b = sy.FiniteSet(2, 3)
a.is_subset(b)  # False
b.is_subset(a)  # True

Returns True if all elements of one set are in the other.

Supersets

a = sy.FiniteSet(1, 2, 3, 4, 5)
b = sy.FiniteSet(2, 3)
a.is_superset(b)  # True
b.is_superset(a)  # False

The reverse of is_subset.

Powerset

a = sy.FiniteSet(1, 2, 3)
a.powerset()
# Returns: {∅, {1}, {2}, {3}, {1, 2}, {1, 3}, {2, 3}, {1, 2, 3}}

Gives all possible subsets of the set.

Union

a = sy.FiniteSet(1, 2, 3)
b = sy.FiniteSet(3, 4)
c = a.union(b)
# c = {1, 2, 3, 4}

You can chain unions:

d = a.union(b).union(c)

Intersect

a = sy.FiniteSet(1, 2, 3)
b = sy.FiniteSet(3, 4)
c = a.intersect(b)
# c = {3}

Chaining also works:

d = a.intersect(b).intersect(c)

Cartesian Product (Multiplication)

a = sy.FiniteSet(1, 2)
b = sy.FiniteSet(3)
c = a * b
# c = {(1, 3), (2, 3)}

Returns all ordered pairs from set a and b.

Summary

A set is a powerful structure for storing unique elements. FiniteSet integrates well with SymPy and supports rich set operations like union, intersection, subsets, powersets, and cartesian products—all helpful in symbolic math and logic operations.

Sqlite3 module in python

saba diasamidze — Fri, 11 Jul 2025 04:50:28 +0000

sqlite3 Python Module Guide

SQLite3 is a Python module written in C that allows interaction with lightweight, local SQL databases. It’s part of Python’s standard library, no installation needed. This article assumes you know basic Python and SQL.

Setting Up
SQL Query Types
- DDL Example: Creating and Dropping Tables
- DML Example: Inserting and Selecting Data
Fetching Data
Summary
Critique

Setting Up

To begin:

import sqlite3 as sql

Then establish a connection and cursor:

connection = sql.connect("my_database.db")
cursor = connection.cursor()

connection links your Python program to the database.
cursor sends SQL commands and fetches results.

SQL Query Types

There are two main types of SQL commands you'll use:

DDL (Data Definition Language): CREATE, DROP, ALTER
DML (Data Manipulation Language): INSERT, SELECT, UPDATE, DELETE

DDL Example: Creating and Dropping Tables

connection = sql.connect("my_database.db")
cursor = connection.cursor()

cursor.execute("""
CREATE TABLE IF NOT EXISTS users (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL,
    age INTEGER
);
""")

# Example DROP
cursor.execute("DROP TABLE IF EXISTS old_users;")

connection.commit()
connection.close()

All DDL commands must be followed by connection.commit() else your changes will not be saved.

DML Example: Inserting and Selecting Data

Insert Example

connection = sql.connect("my_database.db")
cursor = connection.cursor()

cursor.execute("INSERT INTO users (name, age) VALUES (?, ?)", ("Alice", 25))
cursor.execute("INSERT INTO users (name, age) VALUES (?, ?)", ("Bob", 30))

connection.commit()
connection.close()

Select Example

connection = sql.connect("my_database.db")
cursor = connection.cursor()

cursor.execute("SELECT * FROM users")
data = cursor.fetchall()

connection.close()

print(data)

All SELECT commands must be followed by appropriate fetch command.

Use these methods to retrieve data:

Method	Returns
`fetchone()`	One row as a tuple
`fetchmany(n)`	Next `n` rows as a list of tuples
`fetchall()`	All rows as a list of tuples

Example:

cursor.execute("SELECT * FROM users")
rows = cursor.fetchall()
for row in rows:
     print(row)

output:

[(1, 'Alice', 25), (2, 'Bob', 30)]

Next Steps

Now that you understand the basics of the sqlite3 module and how to interact with a database, here are some important topics we should probably also cover:

Using the `with` Statement

Using with ensures your database connection closes automatically, even if errors occur:

import sqlite3 as sql

with sql.connect("my_database.db") as connection:
    cursor = connection.cursor()
    cursor.execute("SELECT * FROM users")
    data = cursor.fetchall()
    print(data)

Basic Error Handling

Wrap your database operations in try-except blocks to catch DatabaseError:

try:
    connection = sql.connect("my_database.db")
    cursor = connection.cursor()
    cursor.execute("SELECT * FROM users")
    data = cursor.fetchall()
except sql.DatabaseError as e:
    print(f"Database error occurred: {e}")
finally:
    connection.close()

Exception	Description
`sqlite3.DatabaseError`	Generic database error
`sqlite3.IntegrityError`	Constraint violations (e.g., unique, foreign key)
`sqlite3.OperationalError`	Operational issues (e.g., missing tables, syntax)
`sqlite3.ProgrammingError`	API misuse (e.g., wrong parameters)
`sqlite3.InterfaceError`	Database interface-related errors

Preventing SQL Injection

Always use parameterized queries (with ? placeholders) to safely insert user input and avoid SQL injection risks:

name = "Alice"
age = 25
cursor.execute("INSERT INTO users (name, age) VALUES (?, ?)", (name, age))

DEV Community: saba diasamidze

Finite sets from Python SymPy

Finite sets from Python SymPy

Table of Contents

Use

FiniteSet

Subsets

Supersets

Powerset

Union

Intersect

Cartesian Product (Multiplication)

Summary

Sqlite3 module in python

sqlite3 Python Module Guide

Table of Contents

Setting Up

SQL Query Types

DDL Example: Creating and Dropping Tables

DML Example: Inserting and Selecting Data

Insert Example

Select Example

Next Steps

Using the `with` Statement

Basic Error Handling

Preventing SQL Injection

DEV Community: saba diasamidze

Finite sets from Python SymPy

Finite sets from Python SymPy

Table of Contents

Use

FiniteSet

Subsets

Supersets

Powerset

Union

Intersect

Cartesian Product (Multiplication)

Summary

Sqlite3 module in python

sqlite3 Python Module Guide

Table of Contents

Setting Up

SQL Query Types

DDL Example: Creating and Dropping Tables

DML Example: Inserting and Selecting Data

Insert Example

Select Example

Next Steps

Using the with Statement

Basic Error Handling

Preventing SQL Injection

Using the `with` Statement