4300-Flask-Template-JSON

Contents

• Summary
• Deploying on the server
• Running Locally
• Uploading Large Files
• Debugging Some Basic Errors
• General comments from the author

Summary

This is a template for "CS/INFO 4300 class at Cornell University"

You will use this template to directly deploy your Flask code on the project server.

After you follow the steps below, you should have set up a public address dedicated to your team's project at (for the moment) a template app will be running. In future milestones you will be updating the code to replace that template with your very own app.

Deploying on the server

For the initial deployment, only one member of your team needs to follow the steps below.

Step 0: Forking or Cloning this template

• You should make a FORK or CLONE of this repository on (regular/your public) GitHub, make sure that your repository is PUBLIC. Keep in mind that other students will be able to see your repository.

Step 1: Login to the deployment dashboard

• Login to the dashboard at http://4300showcase.infosci.cornell.edu:9090/#/login using your provided account name and password. Each team was provided with joint account in CMS comments to assignment P01; since you are sharing an account, any changes made by one teammate will reflect for everyone in the team.
• When you login, ensure your dashboard has the following data filled from the image below (check the black arrows only)
  • The GitHub URL field will not be filled in for you, so you should add in the URL of your forked repository.

Step 2: Understanding the interface

• CLONE: First time clone from GitHub onto the server, this is to load your files on the server. In future, when you push updates, clone will re-downloaded your new files onto the server. It is imperative that you re-clone before building.
• BUILD: Will re-clone and build everything from your GitHub repo, and only from the master/main branch. This is a hard reset, however, your data will be preserved. This includes all data from your database and tables.
• DESTROY: Will destroy all your containers as well as remove any data associated with them. Useful for fresh boot from scratch
• Container Information Table: Will show you the status of all your containers. This should tell you if they are on/off. Generally, this information is just useful for debugging and for checking any port errors or mismatches, although mostly just useful for TAs.
• Logs: Should give you an idea of what went wrong during deployment. This of course will not tell you if something is broken during build time, but only what happened when your code was deployed.

Step 3: Test deployment

• On the dashboard, in the provided search bar, add the URL of your forked repository
• Click the clone button and wait for a bit till you get a confirmation
• Click build, and wait for a minute. If all goes successfully, hitting the refresh button on the Container Information table and the logs tab will show the created data from the service. If this doesn't work, logout and log back in.
• Now, clicking on the URL button should lead you to a simple episode-searching app
• If it doesn't load initially, give it a few seconds and reload.
• This should be the screen you see. Test it out

Running locally

This is not formally a requirement of P01. This is to help you test and develop your app locally; we recommend each member of the team to try this out.

Step 1: Set up a virtual environment

Create a virtual environment in Python. You may continue using the one you setup for assignment if necessary. To review how to set up a virtual environment and activate it, refer to A0 assignment writeup.

Run python -m venv <virtual_env_name> in your project directory to create a new virtual environment, remember to change <virtual_env_name> to your preferred environment name.

Step 2: Install dependencies

You need to install dependencies by running python -m pip install -r requirements.txt in the backend folder.

Step 3: Modify init.json file

This project gives you an init.json file with dummy data to see how app.py file reads data from the json file. You can change data in this file to your project's json data, but do not delete or change the name of the file. However, you are allowed to create more json files for your project.

Command to run project locally:

flask run --host=0.0.0.0 --port=5000

Uploading Large Files

• Note: This feature is correctly under testing
• When your dataset is ready, it should be of the form of a JSON file of 128MB or less.
  • 128MB is negotiable, based on your dataset requirements
• Click "Upload JSON file" button, choose your file and hit the upload button to send it to your project
• The files are chunked. Any interruption either on the network or client end will require a full file re-upload so be careful
  • In the event your file does not get consistently uploaded due to network issues or takes too long (it really shouldn't) you may request a manual upload
• This JSON file that you upload will always replace your init.json file. This means that when you build your project, this file will be automatically imported into your Database and be available to use.

Debugging Some Basic Errors

• After the build, wait a few seconds as the server will still be loading, especially for larger applications with a lot of setup
• Do not change the Dockerfiles without permission
• Sometimes, if a deployment doesn't work, you can try logging out and back in to see if it works
• Alternatively, checking the console will tell you what error it is. If it's a 401, then logging in and out should fix it.
• If it isn't a 401, first try checking the logs or container status. Check if the containers are alive or not, which could cause issues. If the containers are down, try stopping and starting them. If that does not work, you can report it on ED.
• If data isn't important, destroying and then cloning and re-building containers will usually fix the issue (assuming there's no logical error)

General comments from the author

• Ensure that you have Python version 3.10 or above installed on your machine (ideally in a virtual environment). Some of the libraries and code used in the template, as well as on the server end, are only compatible with Python versions 3.10 and above.
• Since this project was made in the span of a few weeks, it is very likely things will break from time to time. If things break, you can send an email through the course email or post to ED first.
• If you would like to see stuff added to the dashboard you can send an email through the course email and prefix the title with FEATURE REQUEST
• If you REALLY want to go above and beyond, you can make a request for a special Docker template. These will likely be turned down unless there is an exceptional reason to do so, and you will have to be able to debug it yourself to ensure it works.
• You can ask for the allocation of extra port numbers which will be approved or denied on a case-by-case basis.
• You can also email regarding any questions relating to the service itself. If you think things can be improved or some better logic can be implemented for certain portions, or even just want to know more about the project then feel free to do so.