Function manager
Overview
Functions are the building blocks of the Function manager feature. It comprises of user-defined python notebooks that perform unique tasks. The user can access the functions under the Lab
icon on the Altergo platform. Following are the predefined guidelines for the user while working with the functions
- Upload function files as python notebooks (.ipynb-format)
- Entail the first cell of the notebook with all mandatory inputs for the function to run
- If you want to give dynamic parameters, make sure to add parameters in a cell tagged
parameters
Create
To create a new function, follow these steps
- Navigate to
Lab > Functions
- Click on
Create function
- Add a function
Name
- Select the
Type
of file as Notebook - Upload notebook file (ipynb-format)
- Click on
Create function
to save
The user is free to choose between Link to file and FIle upload as the source
of function to be integrated. By default, it is selected as File upload
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Link to hosted file
With this option you are able to link a notebook file hosted on a public repository (github, gitlab, bitbucket, etc...) To import notebook from a public repository, follow these steps
- Select
Source
asLink to file
- Add link to the file in
Path
- Click on
Create function
to save
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Limitations
Depending on the configuration of the server where the notebook is executed, there are certain limitations in terms of the memory that a notebook can consume.
Here are the limitations for a server with the following configurations : CPU - 1 RAM - 2GB
Maximum memory consumption - 500 MB Approx total no of datapoints - 500000 (0.5 million) Approx time range of data* - 2 months
'*' - The calculation is based on the assumption that the data is processed for a single sensor of a single asset having roughly a frequency of 1 datapoint every 10 seconds. The limits will vary based on the no of assets, no of sensors and the frequency of the data on Altergo.