improved docker container readme

README.md

@@ -60,12 +60,13 @@ Each stage runs (and source controls input-outputs) corresponding notebooks usin
 
 Getting started
 -------------------
+
+You can either use micromamba/conda/anaconda or docker container to setup the project.
+
+### Micromamba/Conda setup
+
 First you have to create a [Conda environment](https://docs.conda.io/en/latest/miniconda.html) or [Micromamba environment](https://github.com/mamba-org/mamba) for the project:
 Micromamba is a superior alternative to Conda with very similar API.
-Alternatively, you can use docker container that already contains micromamba environment with everything pre-installed:
-```
-docker run -i -t quay.io/comp-bio-aging/yspecies:latest
-```
 
 To create environment you can do:
 ```bash
@@ -87,6 +88,24 @@ dvc repro
 ```
 or can run jupyter notebooks to explore notebooks on your own (see running notebooks section)
 
+### Docker setup
+
+Alternatively, you can use docker container that already contains micromamba environment with everything pre-installed.
+Get inside the container with:
+```
+docker run -i -t --network host quay.io/comp-bio-aging/yspecies:latest
+```
+Micromamba environment will be automatically activated inside the container.
+To reproduce the pipelines you can run:
+```
+dvc repro
+```
+You can also pull the data and start jupyterlab to work with notebooks
+```bash
+dvc pull
+jupyter lab notebooks --allow-root
+```
+
 Running stages
 --------------
 DVC stages are in dvc.yaml file, to run dvc stage just use dvc repro <stage_name>:

environment.yaml

@@ -5,21 +5,22 @@ channels:
   - bioconda
   - defaults
 dependencies:
-  - python=3.9
-  - jupyterlab=3.2.3
-  - dvc=2.8.3
-  - dvc-gdrive=2.8.3
-  - papermill=2.3.3
-  - scikit-learn=1.0.1
-  - anaconda-client=1.9.0
-  - conda-build=3.21.6
-  - mamba=0.17.0
-  - scikit-learn=1.0.1
-  - more-itertools=8.11.0
-  - lightgbm=3.2.1
+  - python=3.10
+  - numba=0.55.2
+  - jupyterlab=3.4.4
+  - matplotlib=3.5.2
+  - dvc=2.16.0
+  - dvc-gdrive=2.16.0
+  - papermill=2.3.4
+  - scikit-learn=1.1.1
+  - anaconda-client=1.10.0
+  - conda-build=3.21.9
+  - mamba=0.25.0
+  - more-itertools=8.13.0
+  - lightgbm=3.3.2
   - statsmodels=0.13.1
-  - click=8.0.3
-  - loguru=0.5.3
-  - plotly=5.3.1
-  - shap=0.40.0
-  - optuna=2.10.0
+  - click=8.1.3
+  - loguru=0.6.0
+  - plotly=5.9.0
+  - shap=0.41.0
+  - optuna=2.10.1

notebooks/debug.ipynb

@@ -1858,7 +1858,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1872,7 +1872,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.10.5"
   }
  },
  "nbformat": 4,