Data Setup

CSR Data Loader – Technical Implementation & Usage Guide

Overview

This section describes the post-deployment data setup process for the DIGIT CRS module using Jupyter Notebook. It serves as a comprehensive guide to help implementation teams prepare and configure the required master data after the CRS module deployment.

The section :

• An overview of all master data that must be collected as part of CRS implementation

• Standard data collection templates, including sample/default values for reference

• A detailed list of attributes for each master, along with the expected data types and formats

• Detailed, step-by-step instructions to ingest the collected master data into the DIGIT CRS system, following the required order of execution.

This setup is designed to improve usability and make the system configuration process straightforward and intuitive.

Note: The data setup process should be performed from the user’s local machine or VM.

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Pre-requisites

• Ensure that a registered domain name is available for the CRS application.

• Ensure you have the admin user credentials with the root tenant ID mapped. This will be created as part of the deployment.

• Python needs to be installed.

• Jupyter Notebook should be installed on Linux, macOS, and Windows.

• Ensure that Jupyter Notebook is up and running.

Steps

The data-loading process is divided into four major phases:

How the templates are phased out, based on the order data needed to be pushed and later the master data required in the other master.

• Load Tenant and Branding Information – Creates city/ULB records and configures header logo, footer logo, login page background image, and state emblem

• Upload Boundary Master – Defines administrative hierarchy (City → Zone → Ward → Block → Locality)

• Upload Common Master – Creates departments, designations, and complaint types with SLA definitions

• Upload Employee Master – Creates employee accounts with role assignments and jurisdiction mappings

Each phase implements three layers of validation to ensure data accuracy, consistency, and schema compliance.

Setup CRS Notebooks

This section explains how to clone the Citizen Complaint Resolution System repository and run the DataLoader.ipynb notebook locally.

1

Clone the Repository

Run the following command in Terminal (macOS/Linux) or PowerShell/Command Prompt (Windows):

git clone https://github.com/egovernments/Citizen-Complaint-Resolution-System.git

After cloning, navigate to the Data Loader directory:

cd Citizen-Complaint-Resolution-System/utilities/crs_dataloader
git checkout  pgr-data-loader 

2

Verify Jupyter Installation

Ensure Jupyter is installed:

jupyter --version

If not installed, refer to the Before You Begin section for installation instructions.

3

Launch Jupyter Notebook

Start Jupyter Notebook:

jupyter notebook (or) jupyter labs

A browser window will open at:

http://localhost:8888/tree

Navigate to Citizen-Complaint-Resolution-System/utilities/crs_dataloader and open DataLoader.ipynb

4

Run the Data Loader Notebook

• Open the notebook.

• Review the notebook sections.

• Read the instructions

• Execute each cell in sequence using Shift + Enter.

• Provide any required inputs (tenant, file paths, etc.).

• Validate output logs as the loader processes data.

Next Steps

This section completes the setup, execution, and maintenance workflow for running the Data Loader notebook locally.

Once setup is complete, proceed based on your chosen approach:

Your Approach	Next Section
Unified (DataLoader.ipynb)	User Guide → Step 1: Login CRS Data Loader – Technical Implementation & Usage Guide
Notebook-wise (3 notebooks)	Alternative Method → Notebook 1: Tenant and Common Masters CRS Data Loader – Technical Implementation & Usage Guide