I’m experiencing an issue with Autodesk Tandem. I used Postman to upload data spanning 10 days for parameters such as air quality, humidity, and temperature. Despite this, the charts on the Tandem dashboard are not showing any variations.
Autodesk tandem
Yes, for both points:
- I have included a timestamp for each data point, and the timestamp is mapped in the "Configure Connections" settings.
- The dates of the time series data fall within the most recent 14-day window.
Thanks for the clarification. I think the issue may be in how the payload is structured,
Here is a simple example I use to test streams using Postman. The body is an array of objects, which results in many time series data points for a single stream as you would be expecting to see. I can't confirm that this is the only format which works for loading historic data, but this format has worked for me reliably.
[
{
"ts": 1735815600,
"temperature": 20,
"humidity": 60
},
{
"ts": 1735815900,
"temperature": 20.5,
"humidity": 61
},
{
"ts": 1735816200,
"temperature": 20.5,
"humidity": 61
}
]
Below you can see that object is a single payload, and i can cycle between the 3 objects which I posted in the configure connections panel.
I have encountered some challenges regarding historical data, bulk uploads, and Python-based integration with Autodesk Tandem. I would appreciate your guidance on these topics.
Here are my specific questions:
Historical Data Handling:
While I have successfully uploaded real-time data to Tandem and observed proper visualization, my attempts to upload historical data (using accurate epoch timestamps in milliseconds) did not yield the expected variations or updates in the chart. Does Tandem support backdated historical data visualization, and if so, are there any additional steps required to enable this functionality?Bulk Data Upload:
I have been using Postman to upload JSON payloads in bulk. While it works for smaller batches, I am concerned about potential limitations (e.g., payload size or the number of data points per request). Could you provide guidelines or best practices for uploading large datasets efficiently?Python Integration and Authentication:
I am implementing a Python script to automate the data upload process to Tandem. While I have successfully converted historical data (from CSV format) into JSON and formatted the timestamps to epoch time in milliseconds, I am facing issues with:- Authentication Token: I am unsure about the correct method to generate and manage the token required for authentication. Are there any specific Python libraries or best practices for handling the token exchange process?
- Tandem Stream URL: I am unclear on how to correctly configure and authenticate against the stream URL for uploading data. Could you provide a detailed guide or API documentation on setting up and interacting with the Tandem streams using Python?
If possible, I would greatly appreciate arranging a Zoom meeting to discuss these topics in more detail. This would also allow me to share my current approach and receive direct feedback from your team. Please let me know a suitable time, and I will ensure my availability accordingly.
Thank you for your time and support. I look forward to your response.
