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Description
Current Behavior
{
  name,
  availableKernels,
  extraArgs,
}:
availableKernels.python {
  name = "jupyterWith-testing"; # must be unique
  displayName = "jupyterWith-testing";
  extraPackages = ps: [ ps.numpy ps.matplotlib ];
}adding matplotlib to the example in the tutorial
leads to
$ nix run
warning: Using saved setting for 'extra-substituters = https://tweag-jupyter.cachix.org' from ~/.local/share/nix/trusted-settings.json.
warning: Using saved setting for 'extra-trusted-public-keys = tweag-jupyter.cachix.org-1:UtNH4Zs6hVUFpFBTLaA4ejYavPo5EFFqgd7G7FxGW9g=' from ~/.local/share/nix/trusted-settings.json.
warning: creating lock file '/home/collin/projects/jupyterWith-test/flake.lock'
error: infinite recursion encountered
       at /nix/store/fr68dr66gmggn62jir7vp1bcnignwxp9-source/pkgs/stdenv/generic/make-derivation.nix:311:7:
          310|       depsBuildBuild              = lib.elemAt (lib.elemAt dependencies 0) 0;
          311|       nativeBuildInputs           = lib.elemAt (lib.elemAt dependencies 0) 1;
             |       ^
          312|       depsBuildTarget             = lib.elemAt (lib.elemAt dependencies 0) 2;
(use '--show-trace' to show detailed location information)Expected Behavior
Jupyter notebook with matplotlib and numpy available.
Steps To Reproduce
Add ps.matplotlib to extraPackages
Version
$ nix-shell -p nix-info --run "nix-info -m
"
 - system: `"x86_64-linux"`
 - host os: `Linux 5.15.59, NixOS, 22.11 (Raccoon), 22.11.20221024.afd4752`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.11.0`
 - channels(collin): `""`
 - channels(root): `"nixos-21.11.335130.386234e2a61"`
 - nixpkgs: `/nix/store/msv8qjxnga8h81biz33gpa4pyw9kg0j1-sourceAdditional Context
This is probably related to nix-community/poetry2nix#750. I'm not sure how I feel about having poetry2nix under jupyterWith. In the past I've had many issues using poetry2nix. Trying to diagnose nix issues + poetry issues is a real headache with nix's non-descriptive error messages. The previous jupyterWith was convenient because I could just specify what packages I wanted without caring about what versions I wanted. I understand the documentation is still under construction so maybe there's a simple method to use jupyterWith like I did previously.
Relevant log output
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