### Integrations

## Agent harnesses docs

* Claude Code db 2.8

* GitHub Copilot db 2.9

* Cursor db 2.11

* Codex db 2.12

## Storage docs

Read & write:

* Local file systems

* AWS S3

* S3-compatible storage services, e.g., MinIO & Cloudflare R2

* Google Cloud Storage

Read only:

* http/https: "ln.Artifact("https://a-website.com/a-dataset.txt")"

* Hugging Face:
  "ln.Artifact("hf://datasets/org/repo/dataset.parquet")"

## Ontologies & registries

* bionty: Biological ontologies, with easy import from >20 public
  ontologies

* pertdb: Registries for perturbations (compounds, biologics, genetic
  interventions, etc.)

## Git docs

Auto-sync code with "git".

## Note taking

* Notion → docs

* Obsidian → see below

* VSCode → see below

-[ Organizing markdown notes in the development directory. ]-

Place your notes into folders in your development directory and use
your favorite editor to edit them:

To sync a notes file to the database, run:

 lamin save <topic>/<my-note.md>

To load a it back, run:

 lamin load https://lamin.ai/laminlabs/lamindata/record/mNDJgWFrkWQVW3ox

## Computational notebooks docs

You can call "ln.track()" and "ln.finish()" (or the R versions) in
four notebook types:

* Jupyter

* Marimo

* R markdown

* Quarto

For Jupyter notebooks, source code is stored in ".py" format and run
reports as html.

## MLOps

* PyTorch Lightning → "lightning"

* Weights & Biases → docs

* MLFlow → docs

* Croissant format → docs

* scVI → docs

## Workflow managers

* "nextflow" & "seqera.io" → nf-lamin

* "redun" → docs

* "prefect", "airflow", "dagster", etc. → docs

* "snakemake" → docs

## Tables & arrays

* "pyarrow" & "polars": see the "engine" argument of "open()" and the
  arrays guide

* "tiledbsoma": inhouse guide or cellxgene

* "duckdb": via parquet files, see rxrx

## Visualization

* Vitessce: see the vitessce guide

* DataVisyn: reach out for custom visualization solutions

## ELN systems

* Benchling: sync schema and data from your registries within our
  team/enterprise plan