🎨 Refactoring

Signed-off-by: zethson <[email protected]>

docs/mcmicro.ipynb

@@ -15,19 +15,14 @@
    "source": [
     "[Nextflow](https://www.nextflow.io/) is a workflow management system used for executing scientific workflows across platforms scalably, portably, and reproducibly.\n",
     "\n",
-    "Here, we'll run a demo of the microscopy pipeline [mcmicro](https://github.com/labsyspharm/mcmicro) to correct uneven illumination. [Reference](https://mcmicro.org/)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8e7d3a5e",
-   "metadata": {},
-   "source": [
-    "```{note}\n",
+    "There are several options to automatically ingest Nextflow pipeline outputs into Lamindb instances:\n",
+    "\n",
+    "1. Using a serverless environment trigger (e.g., AWS Lambda) to execute a Python script.\n",
+    "2. By using a [post-run script](https://docs.seqera.io/platform/23.4.0/launch/advanced#pre-and-post-run-scripts) on the Seqera Platform.\n",
     "\n",
-    "Typically, you run the Nextflow workflow from the command line or Seqera Platform and then register input and output data with a script.\n",
-    "The Seqera Platform allows for [post-run scripts](https://docs.seqera.io/platform/23.4.0/launch/advanced#pre-and-post-run-scripts) that can automate this process.\n",
-    "```"
+    "Both approaches execute a script that connects to the Lamindb instance and ingests the run output, similar to the one shown below.\n",
+    "\n",
+    "This guide shows how to manually ingest a Nextflow run and illustrates what such an automated script could look like by registering the output of a run of the [mcmicro](https://github.com/labsyspharm/mcmicro) [Reference](https://mcmicro.org/) microscopy pipeline into a lamin instance."
    ]
   },
   {
@@ -103,14 +98,6 @@
     "## Data lineage"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "54595d81",
-   "metadata": {},
-   "source": [
-    "View data lineage:"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

docs/mcmicro.py

@@ -23,10 +23,10 @@
     reference="https://github.com/labsyspharm/mcmicro",
 )
 ln.context.track(transform=transform)
-run = ln.context.run
+run = ln.context.unun
 
-# get the input data from LaminDB
-mcmicro_input = ln.Artifact.using("laminlabs/lamindata").get(uid="iTLHluoQczqH6ZypgDxA")
+# get the input data from a predecessor pipeline through LaminDB and make it available in the current working directory
+mcmicro_input = ln.Artifact.using("laminlabs/lamindata").get(description=args.input)
 input_dir = mcmicro_input.cache()
 if not (dest := Path.cwd() / Path(input_dir.path).name).exists():
     shutil.copytree(input_dir.path, dest)
@@ -71,9 +71,11 @@
 run.params.add_values({"qc_params": qc_params})
 
 # register the output artifact
-Path(f"{dest}/registration").joinpath(f"{Path(dest).name}.ome.tif").rename(
-    Path(f"{dest}/registration/exemplar-001.ome.tif")
+(Path(dest) / "registration" / f"{Path(dest).name}.ome.tif").rename(
+    Path(dest) / "registration" / "exemplar-001.ome.tif"
 )
+
+
 output = ln.Artifact.from_dir(f"{dest}/registration")
 ln.save(output)