fix(quickstart): smoother Colab UX (GPU default, conditional install, batch breakdown)#33
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… batch breakdown) Four polish fixes after first-impression testing on Colab: 1. Add notebook metadata `accelerator: "GPU"` + `colab.gpuType: "T4"` so the runtime defaults to a T4 GPU instead of CPU. 2. Add a dedicated GPU-check cell that prints a clear warning if the runtime is on CPU, with the exact menu path to enable GPU. 3. Make the install cell unconditional (was commented out) but guarded by an `importlib.util.find_spec` check, so it only runs when scmidas isn't already importable. `--quiet` flag plus a markdown note about the harmless google-colab/pandas dependency-resolver warning. 4. Replace the bare `mdata` print (which only showed shapes) with an explicit per-batch breakdown showing cell count and modality composition for each of the four batches — the mosaic structure is now visible at a glance. The demo is the project's first impression; smoothness here matters more than smoothness in any internal API.
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Summary
Polish the Colab quickstart based on first-impression testing.
Four fixes
accelerator: "GPU"+colab.gpuType: "T4"to notebook metadata so Colab spins up a T4 by default.✓ GPU detected: <name>or a clear warning with the exact menu path (Runtime → Change runtime type → T4 GPU) if running on CPU.# !pip install scmidas(commented), nowif importlib.util.find_spec("scmidas") is None: !pip install --quiet scmidas. Runs install on Colab automatically, no-ops on local Jupyter where scmidas is already importable.--quietreduces noise; a markdown note explains the benign google-colab/pandas resolver warning.mdatarepr (which just showed shapes) with an explicit table:Test plan
jupyter nbconvert --execute— all cells run, UMAP renders, breakdown prints correctly.