CSV to DB Table#
This page explains how to translate a CSV File into a DataBase Table using Dynamic Django tool.
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Download Dynamic Django#
For newcomers, Dynamic Django is a commercial tool that aims to simplify the data processing and consolidation via generated APIs, DataTables, Charts and CLI tools.
To get the product navigate to the payment page and complete the purchase. Unpack the ZIP archive and folow these steps:
unzip dynamic-django.zip
cd dynamic-django
The project set up is the usual one for any Django project:
virtualenv env # create a virtual environment
source env/bin/activate # activate VENV
pip install -r requirements.txt # install modules
python manage.py makemigrations # migrate DB
python manage.py migrate # apply changes
python manage.py runserver # start Dynamic Django tool
At this point, we can visit the tool in the browser at localhost:8000.
Convert CVS into a Table#
Once the tool is properly installed, the next step is to execute csv-to-model custom command to process the CSV file. Here are the steps for Titanic.csv file, shipped with the tool.
python manage.py csv-to-model -i # STEP #1: Print the help
python manage.py csv-to-model -f Titanic.csv -c # STEP #2: Check File integrity
python manage.py csv-to-model -f Titanic.csv # STEP #3: Generate the model definition
python manage.py makemigrations # STEP #4: Generate Migration SQL
python manage.py migrate # STEP #5: Apply Changes in DataBase
At this point, we have the CSV file translated into a DataBase Model/Table ready to be used.
Explanation of the steps#
STEP #1: Print the tool help using -i argument
STEP #2: Check the integrity of the CSV file using -c argument
STEP #3: Translate the CSV file to a Django model. The definition is also printed in the terminal
STEP #4: Execute makemigrations command that generates the SQL code for DB migration
STEP #5: Apply the Database migration
Invoke the Model (Django Shell)#
The model can be used and provisioned with information using python manage.py csv-to-model -f Titanic.csv -l command. Please note the -l argument that enables the data load.
python manage.py shell
>>> from home.models import *
>>> Titanic.objects.all()
<QuerySet []>
Video Resources#
This video material explains how to process CSV files and convert them into secure APIs and server-side data tables using Dynamic Django tool.
Links#
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