# Using specific (conda) environment when running functions on the server-side

**URL:** <https://datashield.discourse.group/t/using-specific-conda-environment-when-running-functions-on-the-server-side/258>\
**Category:** Analyst Support\
**Created:** [21 July 2020 09:55 UTC](https://datashield.discourse.group/t/using-specific-conda-environment-when-running-functions-on-the-server-side/258 "2020-07-21T09:55:13Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![yannick](https://yyz2.discourse-cdn.com/free1/user_avatar/datashield.discourse.group/yannick/32/19_2.png) [@yannick](https://datashield.discourse.group/u/yannick)\
**Post date:** [21 July 2020 20:42 UTC](https://datashield.discourse.group/t/using-specific-conda-environment-when-running-functions-on-the-server-side/258/3 "2020-07-21T20:42:07Z")

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Hi,

Looks like a good candidate for using [resources](https://datashield.discourse.group/t/opal-3-0-released/237) 🙂 How will you handle the datasets ? Are these stored in CSV files or TFRecords ones ?

I have made a bit of technology review and there is a good integration with R that is supported by Rstudio: [https://tensorflow.rstudio.com/](https://tensorflow.rstudio.com/) (it uses the [reticulate](https://rstudio.github.io/reticulate/) package that is a bridge between the R and Python worlds). Will you use this tensorflow R package ?

As there seems to be quite a lot of dependencies, I think that building a specific R server docker image, including all the Tensorflow related stuff, would help. You can use the [obiba/opal-rserver](https://github.com/obiba/docker-opal-rserver/blob/master/Dockerfile) as the base image.

Regards  
Yannick

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