Libraries and Dependencies Used in Our Application
Last updated
Last updated
Libraries and dependencies details regarding purpose and version are as follow
| Library Name | Purpose | Version |
|---|---|---|
Below are the libraries which is used by our UI.
Info: For lyftrondata installation on the environment follow the document
| Library | 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
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