Hi everyone,
I’m new to Julia and currently using it in Google Colab for some modeling work. I’ve noticed that package installation is quite slow — it takes several minutes. Is this expected behavior, or am I missing something?
I’d appreciate any tips on how to speed things up or set up Colab more efficiently for Julia workflows. Thanks in advance!
Really depends on the sizes and precompilation workloads of the package and its dependencies, though cached versions of packages are reused to cut down on installation times. I never used Google Colab so I don’t know how it affects package installation. Locally, a package installation varies from seconds to minutes for me, and it may increase with slower internet access or lowered power consumption. What packages are you trying to install and when?
Hi Benny, thanks for your answer. Here are some packages, which I want to install: OrdinaryDiffEq, ModelingToolkit, DataDrivenDiffEq, SciMLSensitivity, DataDrivenSparse
Optimization, OptimizationOptimisers, OptimizationOptimJL, LineSearches.
I installed these packages on my local machine. The problem with Colab is that even if you install them once, you have to reinstall them every time you start a new session. Is there a way to use Google Drive to avoid reinstalling them each time?
There was some discussion about package precompilation being slow in Julia in Colab - #25 by vchuravy. The problem should be the filesystem where the precompile cache is saved, I think someone had some luck by choosing a faster partition.