The MyGMR project consists of a backend running on Google Cloud App Engine and a mobile app built with Flutter for Android. This project allows users to manage GMR devices and their associated tasks.
- flutter_app: Contains the Flutter mobile application.
- server: Contains the backend server code for Google Cloud App Engine.
- test: Contains testing scripts and data for the server.
- Flutter: To run the mobile app, install Flutter from here.
- Python: Required for the backend server. Install Python 3.9 or higher.
- Google Cloud SDK: To deploy the backend server on Google Cloud. Install from here.
In this case, there are two ways to utilize our app, either by installing our APK or through Android Studio using a virtual machine of an Android Phone:
The easiest way to run our app is to install our APK on your phone device. In this case, this APK is only compatible with Android phones. You can find our APK in the following location:
./APKs/app-realese.apk
This will be the steps to run your own server:
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Having a google cloud project with the necessary cloud storage, cloudSQL and app engine setted up. Also you will need your service account json
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Having a firebase linked to that gcloud project with the following settings:
- Authentication system with (at least) a google provider
- Add the flutter app package to the project along with the SHA1 key
You need the following secret files in order to run the app completly (if you don't have them already):
- server/your-project-random-string.json this is your service account json
- server/.env add the following environment environment variables
- GOOGLE_APPLICATION_CREDENTIALS: your google service account json
- INSTANCE_CONNECTION_NAME: project-name:timezone:cloudsql-instance-id
- DB_USER: username of your database user
- DB_PASS: password of your database user
- DB_NAME: name of your databas
- FLASK_SECRET_KEY: random string to handle flask sessions
- CLOUD_IMAGE_FOLDER: the cloud bucket name for your files
- CLOUD_BUCKET_BASE_URL: generally https://storage.googleapis.com
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Create a virtual environment with the requisite:
python -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate`
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Install the dependencies:
pip install -r requirements.txt
Alternatively, you can use our enviroment.yml
conda env create --name my_gmr -f environment.yml conda activate my_gmr
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Run the server:
python run.py
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Authenticate with Google Cloud:
gcloud auth login
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Set your Google Cloud project:
gcloud config set project YOUR_PROJECT_ID -
Deploy the application:
gcloud app deploy
The same as the server, you need a running server on the cloud along with the following secret files:
-
server/test/your-project-random-string.json this is your service account json
-
server/test/.env add the following environment environment variables
- SERVER_URL: your app engine server URL
- BUCKET_NAME: your buckent name
- GOOGLE_APPLICATION_CREDENTIALS: to your google service account json
To run a test client robot you have to use the same environment as said before. In this case, before running any client, you have to add and ID of 8 digits, which simulates the plate/ID of the GMR device.
To add this ID of 8 digits you have to access to a json file, the path is the following one:
python server/test/robot_data.jsonIn this file you have to write yourself the ID of the GMR device, modifying the "matricula" entry:
{
"matricula": 87654321,
"model_id": 1
}Once you have done it, you can run your test server without problem running the following command in your console:
python ./server/test/test_robot_client.py-
Navigate to the
flutter_appdirectory:cd flutter_app -
Ensure all Flutter dependencies are installed:
flutter pub get
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Connect an Android device or start an Android emulator.
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Run the app in debug mode:
flutter run
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Build the APK:
flutter build apk --release
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The release APK can be found in
build/app/outputs/flutter-apk/app-release.apk.
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Modify the
matriculafield inrobot_data.jsonin theserver/testdirectory as needed. -
Run the test client to verify functionalities:
python test_robot_client.py
- Fork the repository.
- Create a new branch.
- Make your changes.
- Submit a pull request.
This project is licensed under the MIT License.
For any issues or questions, please open an issue on the project's GitHub page.