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Heat Sink Design Project

This is a sample project that aims to demonstrate various possible Onshape integrations with the REST API. Speicifically, this project demonstrates two alternatives that API calls can be made: (1) simple coding in a Jupyter notebook, and (2) integration to the Onshape user interface with a Python Flask application.

Correspondingly, more detailed guides to these two integration methods can be found in this repository. To really get started and learn about these methods, it is highly recommended to first go through the integration guides for the basics and then return to this project to see its capability.

In this project, we first build an Onshape model of a simple heat sink with fins on top for heat dissipation. By varying the width and the spacing of the fins, we use a series of REST API calls to obtain measurements of the heat sink from Onshape. Then, we can algorithmically calculate the varying amount of heat transfer from the heat sink with variables mentioned above.

snapshot

Note: Due to the difference in the two integration methods, the same Onshape CAD model was built with two different approach: one with configurations here, and the other one with variables here.

1. Jupyter Notebook

The Jupyter notebook contains detailed descriptions and instructions of the project. The notebook was designed in a way that allows both students with no programming experience to interact with the engineering concepts through forms and students who would like to further explore the REST API calls in Onshape.

Simply locate and open the document named Heat_Sink_Demo.ipynb in this repository. It is recommended to click the badge at the top of the page to "Open in Colab", or you can also upload and open the Jupyter notebook in your Google Drive with Google Colab.

Without re-running the code, you should be able to see the saved results of the code blocks and get a sense of some of the capabilities of the REST API calls in Onshape. To play around with the parameters and make changes to the code for further exploration, you will need to do the following:

  1. Make a copy to this Onshape document in your own Onshape account.
  2. Follow the instructions of section 2 of this guide to create your API keys. Such that you can configure your client to access your copied Onshape document.
  3. Follow the instructions on the Jupyter notebook to configure your client with the API keys you created and copy the URL of your copied Onshape document. Then, you are good to go!

By making API calls to the model, we can vary its parameters and conduct scientific analysis that may result in a heat map like this as an example:

heatmap

2. Flask application

The Flask app was built to demonstrate the capability of integrating a self-built web application to the native Onshape interface. Such that, you can simply launch the app locally in your computer but interact with it in an Onshape document.

To integrate and use the Flask app in this project, please follow the following steps:

  1. Make a copy to this Onshape document. Note that this is a different document from the one used for the Jupyter notebook.
  2. Clone this repository to your local computer like you would do for any other GitHub repository.
  3. If you are using an Onshape Enterprise account, open HeatSinkApp.py and change the base URL on line 20 to the URL of your Enterprise account (e.g., 'https://ptc.onshape.com').
  4. Follow the instructions of section 2 of this guide to create your API keys if you have not done so.
  5. Optional: rename the file that stores your API key to OnshapeAPIKey.py and put it into the folder that host this project. This file name has been added to .gitignore, so it won't be shared through any git commands. If you choose not to do so, you can also manually enter your API keys when you launch the app.
  6. This repository already contains a set of HTTPS certificates. You can simply use the ones we provide, or you can also create your own, following section 3 of this guide. Either way, you should still follow the steps of that section to add the certificates to be a trusted certificate for your computer and launch the app in your browser for testing.
  7. Follow section 4.1 of this guide to integrate this app to Onshape through OAuth.

For the "Action URL" of your OAuth application extension, use the following:

https://127.0.0.1:5000/login?documentId={$documentId}&workspaceId={$workspaceId}&elementId={$elementId}

Then, you can simply launch the Flask app in your local computer environment with the following command lines and use it in your Onshape document:

$ export FLASK_APP=HeatSinkApp
$ export FLASK_ENV=development 
$ flask run --cert=cert.pem --key=key.pem

Below shows how the Flask app should be running:

FlaskGIF