+
+
+ Wrap-up: Workflow managers
+
+
+
+
+
+
+
+
+
+
+
+
+ Wrap-up: Workflow managers
+
+
+
+
+What we have learned
+-
+
- How to create and execute workflows +
- How to rerun workflows (and what triggers reruns) +
- How to capture logs and errors +
- How to set parameters to make workflows more flexible +
- How to generalize workflows +
Comparison
+| + | Snakemake | +Nextflow | +
|---|---|---|
| language | +Python | +Groovy | +
| philosophy | +‘pull’ | +‘push’ | +
| data | +file(s) | +channel(s) | +
| unit of execution | +rule | +process | +
| execution | +working directory | +each job in its own directory | +
If you want to learn more
+-
+
- NBIS Snakemake BYOC (bring-your-own-code) workshop (check https://www.scilifelab.se/events/#calendar for next instance) +
- Nextflow Training (https://training.nextflow.io/) +
+
+
+
+ 
'
+format: nbis-revealjs
+---
+
+## What we have learned
+
+* How to create and execute workflows
+* How to rerun workflows (and what triggers reruns)
+* How to capture logs and errors
+* How to set parameters to make workflows more flexible
+* How to generalize workflows
+
+## Comparison {.smaller}
+
+| | Snakemake | Nextflow |
+|---------|-----------|----------|
+| language | Python | Groovy |
+| philosophy | 'pull' | 'push' |
+| data | file(s) | channel(s) |
+| unit of execution | rule | process |
+| execution | working directory | each job in its own directory |
+
+## If you want to learn more {.smaller}
+
+- NBIS Snakemake BYOC (bring-your-own-code) workshop (check [https://www.scilifelab.se/events/#calendar](https://www.scilifelab.se/events/#calendar) for next instance)
+- Nextflow Training ([https://training.nextflow.io/](https://training.nextflow.io/))
\ No newline at end of file
diff --git a/pages/jupyter/jupyter-7-reproducibility.md b/pages/jupyter/jupyter-7-reproducibility.md
index bf72f81c..fa8f21fb 100644
--- a/pages/jupyter/jupyter-7-reproducibility.md
+++ b/pages/jupyter/jupyter-7-reproducibility.md
@@ -122,9 +122,9 @@ notebooks. It works by executing each cell in the notebook and comparing the
output to the output stored in the notebook. If the output is the same, the test
passes. If the output differs, the test fails. `nbval` is also pre-installed in
the `jupyter-env` Conda environment you're using for this tutorial.
-
+
As an example, we'll keep working with the `Analysis.ipynb` notebook we've
-created.
+created.
Let's say we want to estimate the size of the bill of penguins using the
`bill_length_mm` and `bill_depth_mm` columns. We'll do this by adding a new cell
@@ -156,7 +156,7 @@ to the output stored in the notebook. If the output is the same, the test
passes. The output of the test should look something like this:
```
-collected 4 items
+collected 4 items
Analysis.ipynb .... [100%]
@@ -171,7 +171,7 @@ Change the third cell of the notebook so that it reads:
```python
penguins["bill_size"] = (penguins["bill_length_mm"] * penguins["bill_depth_mm"]) / penguins["body_mass_g"]
-sns.scatterplot(data=df, x="bill_size", y="flipper_length_mm", hue="island")
+sns.scatterplot(data=penguins, x="bill_size", y="flipper_length_mm", hue="island")
```
Re-run the cell and save the notebook. So far so good! Let's test the notebook
@@ -190,7 +190,7 @@ FAILED Analysis.ipynb::Cell 3
================== 1 failed, 3 passed in 1.83s ==================
```
-What happened here was that we modified the cell where we calculated the
+What happened here was that we modified the cell where we calculated the
`bill_size` value, but we didn't re-run the cell where we output the mean of
each column grouped by `island`. This means that the output of the last cell in
the notebook now differs from what is actually stored in the notebook variables.
@@ -208,10 +208,10 @@ kernel before re-running you make sure that you haven't introduced any 'hidden s
> **Ignoring specific cells**