- Following the Corva Dev Center Backend Getting Started and Python SDK documentation:
- Create, develop, locally test and deploy a Python backend scheduled depth app:
- +App: Backend→ Scheduler → App Name: Lab Scheduled Depth App → Segment: Drilling → Log Type: Depth → Scheduler Type: Data Depth → Follow: Drilling Enhanced Real-Time Depth→ Category: Analytics
- Create a dataset:
- Dataset Type: Depth-Based
- Name: {provider}#lab-scheduled-depth-app
- In the manifest.json file, set “read”,”write” permissions for {provider}#lab-scheduled-depth-app.
- In the manifest.json file, set the
“app.depth_milestone”: 5 - Perform a GET request to
corva#drilling.wits.depthfor the following value:“data.dep - Import the Python statistics library into the app:
import statistics - Calculate the mean value of the 5 minutes of the "data.dep" data e.g.
mean_dep = statistics.mean(record.get("data", {}).get("dep", 0) - POST the calculated
"data.mean_dep"value to {provider}#lab-scheduled-depth-app. - Test the GET and POST request in the Corva Data API Swagger document or in Postman utilizing your company's API key or your Bearer Token
- Locally test the lambda function using the Pytest template within the app directory
- Zip up the app and deploy to the Dev Center
- Utilizing the App Runner feature, test the app on Production
- Confirm no errors in Log Files and that the data is being populated in the {provider}#lab-scheduled-depth-app dataset
- Create, develop, locally test and deploy a Python backend scheduled depth app:
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