ferenc-hechler / disaster-response-project

Submission for Udacity Nanodegree Data Scientist

Disaster Response Pipeline Project

Setup Environment

The packages listed in requirements.txt have to be installed:

pip install -r requirements.txt

The program was tested with Python 3.10 but it should also run with earlier versions too.

Instructions:

1. Run the following commands in the project's root directory to set up your database and model.

   • To run ETL pipeline that cleans data and stores in database python data/process_data.py data/disaster_messages.csv data/disaster_categories.csv data/DisasterResponse.db
   • To run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl the training takes some time (about 10 minutes)

2. Go to app directory: cd app

3. Run your web app: python run.py

4. Start a local browser and enter the url http://localhost:3000/. Initially the top 10 categories with their percetage occurrences and the distribution of the genres is shown. When entering an example sentence, like "we need fresh water" is entred in the input field and the button "Classify Message" is clicked a screen showing all identified categories in green is shown.

Running Unittests

For running the unit tests the package "pytest" is needed.

cd models
pytest

Sources

The source code is available in GitHub: Disaster-Response-Project.