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Alteryx Promote Knowledge Base

Definitive answers from Promote experts. - Adding Layers to R or Python Images

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Often, when deploying a model up to Promote, the model requires certain dependencies to run. These dependencies can be certain functions, files, etc. If your model requires them, you’ll need to create a, which contains commands to import these dependencies. This will be one of the factors needed to ensure your model will be set up for success on Promote, because sometimes a model needs a little help.




If we go to we can go into the article-summarizer example, which contains one of these files. You’ll notice that if you open the file, you’ll see this command:


python -c "import nltk;'punkt')"

This is required because the newspaper package in the model ( requires an NLP dataset. Now, when we deploy the model, the file will run at the same time, which will ensure the dependencies live inside the model environment (docker model image). We can now properly test the model in Promote!


If we're looking at an R example (there is one on the Promote GitHub), you will have the same folder structure, except the file will look something like this:

curl | apt-key add -
curl > /etc/apt/sources.list.d/mssql-release.list
apt-get update
ACCEPT_EULA=Y apt-get -y install msodbcsql17
apt-get -y install unixodbc-dev

apt-get -y install r-cran-rodbc
apt-get -y install libiodbc2-dev

In this case, our model requires an ODBC driver, therefore our model container will also need it in order to run on Promote. Just as in the above Python example, when we deploy this model, the file will run and the proper driver will be installed, enabling us to work and test this model on Promote!


Once you get these all set, you'll be good to venture on and make your model the best it can be!