Libraries and Dependencies Used in Our Application

Libraries and dependencies details regarding purpose and version are as follow

Library Name Purpose Version

Library Name	Purpose	Version
Python3-pip	Python package installer for Python 3.x.	21.3.1
Python3-dev	Development files for building Python modules in Python 3.x.	21.3.1
Python3-tk	Tkinter module for Python 3.x, used for GUI applications.	-21.3.1
Python3-venv	Python virtual environment support for Python 3.x.	21.3.1
Redis-server	The `image: redis:7.2.4` line in the Dockerfile specifies the Redis image version 7.2.4 to be used. Redis serves as a fast, in-memory data store for caching and messaging within the application's Docker environment, enhancing performance and scalability while ensuring compatibility and consistency across deployments.	7.2.4
Pymssql	MSSQL database adapter for Python version	2.2.5.
Pyyaml	YAML parser and emitter for Python version	5.4.1
Apache-airflow	This command installs Apache Airflow version 2.2.0, a platform for orchestrating workflows. Ensure that pip is installed on your system before running this command.	2.2.0
Java	OpenJDK is a free and open-source implementation of the Java Platform. This command installs OpenJDK version 11, which is required by Apache Airflow for execution.	11
Node.js v	JavaScript runtime environment for executing JavaScript code server-side.	16.15.1
Yarn	Dependency management tool for JavaScript projects.	1.22.21
Spark & Hadoop	Spark 3.2.2 with Hadoop 3.2 support is a distributed computing system for large-scale data processing. It offers high performance, fault tolerance, and diverse data processing capabilities like batch processing and real-time streaming. Spark simplifies complex data workflows, making it suitable for big data analytics and computation tasks.	spark-3.2.2-bin-hadoop3.2
Python 3.9	Python 3.9 is a major release with enhanced features and performance improvements. It offers new syntax, built-in types, and additional library modules. Python 3.9 improves developer productivity, code readability, and application efficiency	Python 3.9
PostgreSQL	Relational database management system	14
Docker	Used to run and manage containers	26.0.0
Docker Compose	Used to run and manage the multiple containers compose files	v2.25.0

Python3-pip

Python package installer for Python 3.x.

21.3.1

Python3-dev

Development files for building Python modules in Python 3.x.

21.3.1

Python3-tk

Tkinter module for Python 3.x, used for GUI applications.

-21.3.1

Python3-venv

Python virtual environment support for Python 3.x.

21.3.1

Redis-server

The image: redis:7.2.4 line in the Dockerfile specifies the Redis image version 7.2.4 to be used. Redis serves as a fast, in-memory data store for caching and messaging within the application's Docker environment, enhancing performance and scalability while ensuring compatibility and consistency across deployments.

7.2.4

Pymssql

MSSQL database adapter for Python version

2.2.5.

Pyyaml

YAML parser and emitter for Python version

5.4.1

Apache-airflow

This command installs Apache Airflow version 2.2.0, a platform for orchestrating workflows.
Ensure that pip is installed on your system before running this command.

2.2.0

Java

OpenJDK is a free and open-source implementation of the Java Platform.
This command installs OpenJDK version 11, which is required by Apache Airflow for execution.

Node.js v

JavaScript runtime environment for executing JavaScript code server-side.

16.15.1

Yarn

Dependency management tool for JavaScript projects.

1.22.21

Spark & Hadoop

Spark 3.2.2 with Hadoop 3.2 support is a distributed computing system for large-scale data processing. It offers high performance, fault tolerance, and diverse data processing capabilities like batch processing and real-time streaming. Spark simplifies complex data workflows, making it suitable for big data analytics and computation tasks.

spark-3.2.2-bin-hadoop3.2

Python 3.9

Python 3.9 is a major release with enhanced features and performance improvements. It offers new syntax, built-in types, and additional library modules. Python 3.9 improves developer productivity, code readability, and application efficiency

Python 3.9

PostgreSQL

Relational database management system

Docker

Used to run and manage containers

26.0.0

Docker Compose

Used to run and manage the multiple containers compose files

v2.25.0

Libraries

Below are the libraries which is used by our UI.

Library	Version
django	3.1.7
django-filter	2.4.0
djangorestframework	3.12.4
django-cors-headers	3.7.0
python-dateutil	2.8.1
python-dotenv	1.0.1
pandas	1.4.1
SQLAlchemy	1.4.17
django-countries	7.2.1
boto3	1.17.79
schedule	1.1.0
requests	2.25.1
psycopg2-binary	2.9.1
getmac	0.8.2
sendgrid	6.7.1
redis	3.5.3
xlrd	2.0.1
openpyxl	3.0.7
selenium	3.141.0
apscheduler	3.7.0
jaydebeapi	1.2.3
Jinja2	3.0.1
django-q	1.0.2
sentry-sdk	1.3.1
pyspark	3.1.2
google-cloud-bigquery	2.34.0
google-auth	1.35.0
django-allauth	0.45.0
drf-yasg	1.20.0
rncryptor	3.3.0
gunicorn	20.1.0
simplejson	3.17.6
psutil	5.9.1
flower	1.2.0
stripe	5.0.0
pdfkit	-
django_otp	1.0.2
dj_rest_auth	2.2.4
dropbox	11.36.2
celery	5.2.7
snowflake-connector-python	3.6.0
django-guardian	2.4.0

Info: For lyftrondata installation on the environment follow the document

PreviousLyftrondata Architecture NextServices used by Lyftrondata

Last updated 6 months ago