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https://github.com/herrfeder/udacity-project-disaster-response-pipelines-webapp
The Repository for the Disaster Response Pipelines Webapp for easy deploying in Docker Container
https://github.com/herrfeder/udacity-project-disaster-response-pipelines-webapp
Last synced: 27 days ago
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The Repository for the Disaster Response Pipelines Webapp for easy deploying in Docker Container
- Host: GitHub
- URL: https://github.com/herrfeder/udacity-project-disaster-response-pipelines-webapp
- Owner: herrfeder
- Created: 2020-02-10T11:11:28.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-02-13T13:12:08.000Z (almost 5 years ago)
- Last Synced: 2024-10-15T19:13:14.554Z (2 months ago)
- Language: HTML
- Homepage:
- Size: 4.29 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Disaster Response Pipeline Project
## Screenshots
| Landing Page with first Plotly Visualisation | Second Graph Visualisation on Landing Page | Zoom into Second Graph Visualisation | Classification of Example Message "Help me. I need water." |
|--------------------------------------|--------------------------------------|--------------------------------------|--------------------------------------|
|  |  |  |  |
## Included Files
* __Dockerfile and docker-entrypoint.sh__: Files for setting up Docker container
* __app/data/process_data__: Script for ETL-Pipeline
* __app/data/disaster_categories.csv__: Source data categories
* __app/data/disaster_messages.csv__: Source data messages
* __app/data/DisasterResponse.db__: Resulting SQLite Database
* __app/models/train_classifier.py__: Script for ML-Pipeline (Training and Storing)
* __templates/__: HTML templates for Web app representation
* __static_disasterresponse/__: Standalone Graph Plot
* __run.py__: Flask routes.py
* __wsgi.py__: Gunicorn Wrapper
## Webapp
An example of this web app is temporary accessible on https://federland.dnshome.de/disasterresponse .
Please be gentle, the resources are restricted. This app __isn't responsive__.
### Docker Instructions:
1. Create directory and download Dockerfile:
```
mkdir pipeline_docker && cd pipeline_docker
wget https://raw.githubusercontent.com/herrfeder/Udacity-Project-Disaster-Response-Pipelines-Webapp/master/Dockerfile
```
2. Build Docker Container:
```
docker build . -t pipeline_docker
```
As the model will be trained during Build, this will take a while.
3. Run Docker Container:
```
docker run -p 5000:5000 pipeline_docker:latest
```
4. Go to http://0.0.0.0:5000/disasterresponse
### Manual Instructions:
1. Clone this Repository and move into it:
```
git clone https://github.com/herrfeder/Udacity-Project-Disaster-Response-Pipelines-Webapp
cd Udacity-Project-Disaster-Response-Pipelines-Webapp
```
2. Resolve all required Python Packages:
```bash
pip install numpy==1.17
pip install scipy
pip install Flask==1.0.0
pip install pandas==1.0.0
pip install matplotlib
pip install scikit_learn
pip install nltk
pip install sqlalchemy
pip install plotly
pip install pyvis
pip install gunicorn
```
3. Run the following commands in the project's `app` 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 run.py`
* (this will take approximately 30 minutes)
* (I had to modify this, because of this issue: https://www.stefaanlippens.net/python-pickling-and-dealing-with-attributeerror-module-object-has-no-attribute-thing.html)
4. Run the following command in the app's directory to run your web app.
`gunicorn --bind 0.0.0.0:5000 wsgi:app`
5. Go to http://0.0.0.0:5000/disasterresponse