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Wear OS DMM data sampling and graphing project for 2020 summer Intern

This is not an officially supported Google product.

This repository is based on a template that can be used to seed a repository for a new Google open source project. See https://opensource.google/docs/releasing/

This template uses the Apache license, as is Google's default. See the documentation for instructions on using alternate license.

Source Code Headers

Every file containing source code must include copyright and license information. This includes any JS/CSS files that you might be serving out to browsers. (This is to help well-intentioned people avoid accidental copying that doesn't comply with the license.)

Apache header:

Copyright 2020 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Commands to checkout the code and push local changes (For admin only).

git init

git remote add origin git@github.com:googleinterns/power-data-graphing-intern-2020.git

git checkout master

git pull

...

make local changes

...

git add your_file_name

git commit -m "Changes description"

git push -u origin master

Adding a new SSH key to your GitHub account for first-time user.

If you encountered "Permission denied (publickey), please set up SSH key following the instruction at: https://help.github.com/en/github/authenticating-to-github/adding-a-new-ssh-key-to-your-github-account

Build rules

Frontend:

  1. Install Angular denpendencies

    • Install Node.js & npm

    • Check Node.js version and npm version by entering

      node -v

      npm -v

  2. Install Angular-cli by running npm install -g @angular/cli

    • Check version by running

      ng version

    • Below are the hello world project's Angular version

      • @angular-devkit/architect 0.901.6
      • @angular-devkit/core 9.1.6
      • @angular-devkit/schematics 9.1.6
      • @schematics/angular 9.1.6
      • @schematics/update 0.901.6
      • rxjs 6.5.4
  3. go to fronend folder, and run following commands to build the frontend

    npm install

    ng serve

Backend

Install pkgs

Make sure you have python3.7+, pip3, python3-venv installed on your machine

  1. To check pip3 version, run pip3 -V, or run sudo apt-get install python3-pip to install it on your machine

  2. Run sudo apt-get install python3-venv to install python3-venv.

Build and run the backend

  1. Make sure you have a python virtual environment on your local machine and install all dependencies in the virtual environment.
    • Create a virtual environment by running python3 -m venv venv. (Recommend to put the environment folder at project's root folder)
    • Activate the environment by running source venv/bin/activate
    • pip3 install wheel
    • install packages in the environment by running pip3 install 'package-name'
  2. go to the backend folder, run the following commands to build the backend server Make sure that you are in a virtual environment before you run this command
    • pip3 install -r requirements.txt (Only need to run this command at the first time)
    • ./build.sh
  3. Leave the virtual environment
    • deactivate

Browser

After finishing set up the frontend and backend, open the browser(recommend chrome) and visit "http://localhost:4200/", you should be able to see the website connected with the backend.

Dev Workflow

One time actions:

  1. Fork the repo
  2. Clone the forked repo locally
    • git clone git@github.com:<YOUR_USERNAME>/power-data-graphing-intern-2020.git
  3. Add upstream remote
    • git remote add upstream git@github.com:googleinterns/power-data-graphing-intern-2020.git
    • Run “git remote -v”, the origin is the fork repo, upstream is the actual repo.
      • origin git@github.com:yaomeng-google/power-data-graphing-intern-2020.git (fetch)
      • origin git@github.com:yaomeng-google/power-data-graphing-intern-2020.git (push)
      • upstream git@github.com:googleinterns/power-data-graphing-intern-2020.git (fetch)
      • upstream git@github.com:googleinterns/power-data-graphing-intern-2020.git (push)

When I am going to work on a new feature:

  1. sync my fork's master branch to upstream's master branch
    • git checkout master; git fetch upstream; git rebase upstream/master
  2. create a new branch from master
    • git checkout -b cool_feature
  3. do my coding
  4. add and commit my changes
    • git add *; git commit -m "New feature"
  5. push my branch to my fork
    • git push origin cool_feature
  6. pull-request my branch from my fork to the upstream repo
    • done in the git hub UI
  7. deal with any code review code changes by making commits and updating the branch in my fork (this updates the open pull-request)
    • git add *; git commit -m "Fixes form review"; git push origin cool_feature
  8. merge the branch into the upstream repo's main branch
    • done in github ui
  9. delete my development branch
    • normally done in github ui

TBD: Deploy the project to Google Cloud Platform

  1. Download gcloud SDK by following this link
  2. Initialze gcloud project by running gcloud init, auenticate with your google acount, and select the option of setting up a new project by entering a new project id, for tank-big-data-plotting, the project id is: google.com:tank-big-data-plotting-285623
  3. Go to the /frontend folder, build the prod version of the frontend by entering ng build --prod. Then go to the generated /dist folder, run gcloud app deploy. Make sure if your gcloud project setup is correctly, and the target service is set as default
  4. Go to the /backend folder, run gcloud app deploy, and make sure the target service is set as api.
  5. Go to the gcp console and make sure the latest frontend and backend have been uploaded.

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  • Python 48.4%
  • TypeScript 39.9%
  • HTML 5.8%
  • CSS 3.1%
  • JavaScript 1.5%
  • Shell 1.3%