THE COLLABORATION OF PYTHON AND DATABASES: A MODERN APPROACH TO DATA-DRIVEN APPLICATIONS

In the era of data-driven decision-making, the synergy between programming languages and database systems has become paramount. This study explores the integration of Python—a versatile and widely-used programming language—with relational databases such as SQLite, MySQL, and PostgreSQL. Employing libraries like sqlite3, psycopg2, and Object-Relational Mapping (ORM) tools such as SQLAlchemy and Django ORM, the research demonstrates how Python facilitates efficient database interactions. Through practical implementations and performance benchmarks, the study highlights Python's strengths in simplicity, scalability, and a rich ecosystem, while also addressing limitations like concurrency handling and performance constraints in high-load scenarios. The findings underscore Python's efficacy as a tool for students and researchers in developing robust, data-centric applications.

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Publication Details

Journal
INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY
Published
2025-05-01
DOI
https://doi.org/10.70728/tech.v2.i06.032
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

THE COLLABORATION OF PYTHON AND DATABASES: A MODERN APPROACH TO DATA-DRIVEN APPLICATIONS

Abrorjon Satvoldiev
INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY
Computational Physics and Python Applications
article

THE COLLABORATION OF PYTHON AND DATABASES: A MODERN APPROACH TO DATA-DRIVEN APPLICATIONS

Abrorjon Satvoldiev
article en

Abstract

In the era of data-driven decision-making, the synergy between programming languages and database systems has become paramount. This study explores the integration of Python—a versatile and widely-used programming language—with relational databases such as SQLite, MySQL, and PostgreSQL. Employing libraries like sqlite3, psycopg2, and Object-Relational Mapping (ORM) tools such as SQLAlchemy and Django ORM, the research demonstrates how Python facilitates efficient database interactions. Through practical implementations and performance benchmarks, the study highlights Python's strengths in simplicity, scalability, and a rich ecosystem, while also addressing limitations like concurrency handling and performance constraints in high-load scenarios. The findings underscore Python's efficacy as a tool for students and researchers in developing robust, data-centric applications.

INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGYVol. 2(06)
Openalex Percentile: Top 96%
Computational Physics and Python Applications
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