Update documentation

README.md

@@ -12,11 +12,11 @@
 
 ## About
 
-An adapter wrapper for [MLflow] to use [CrateDB] as a storage database
-for [MLflow Tracking].
+An adapter for [MLflow] to use [CrateDB] as a storage database for [MLflow
+Tracking]. MLflow is an open source platform to manage the whole ML lifecycle,
+including experimentation, reproducibility, deployment, and a central model
+registry.
 
-[MLflow] is an open source platform to manage the ML lifecycle, including
-experimentation, reproducibility, deployment, and a central model registry.
 
 ## Setup
 
@@ -33,11 +33,14 @@ mlflow-cratedb cratedb --version
 ```
 
 
-## Usage
+## Documentation
+
+The [MLflow Tracking] subsystem is about recording and querying experiments, across
+code, data, config, and results.
 
 The MLflow adapter for CrateDB can be used in different ways. Please refer
-to the [handbook] and the documentation about
-[container usage].
+to the [handbook], the documentation about [container usage], and the
+[hands-on guidelines].
 
 
 ## Development
@@ -54,7 +57,6 @@ how to [install a development sandbox].
 - [Python Package Index (PyPI)](https://pypi.org/project/mlflow-cratedb/)
 
 ### Contributions
-
 This library is an open source project, and is [managed on GitHub].
 Every kind of contribution, feedback, or patch, is much welcome. [Create an
 issue] or submit a patch if you think we should include a new feature, or to
@@ -87,6 +89,7 @@ which is using [Merlion].
 [Create an issue]: https://github.com/crate-workbench/mlflow-cratedb/issues
 [development sandbox]: https://github.com/crate-workbench/mlflow-cratedb/blob/main/docs/development.md
 [handbook]: https://github.com/crate-workbench/mlflow-cratedb/blob/main/docs/handbook.md
+[hands-on guidelines]: https://github.com/crate/cratedb-examples/blob/main/framework/mlflow/readme.md
 [Harutaka Kawamura]: https://github.com/harupy
 [install a development sandbox]: https://github.com/crate-workbench/mlflow-cratedb/blob/main/docs/development.md
 [LICENSE]: https://github.com/crate-workbench/mlflow-cratedb/blob/main/LICENSE

docs/backlog.md

@@ -1,6 +1,17 @@
 # Backlog
 
+## Iteration +1
+
+### Documentation
+- Write a few words about schema/table structure:
+  Data tables are in `doc`, while MLflow tables are in `mlflow`.
+
+- Write a few words about standalone programs, and the need to import `mlflow_cratedb` there,
+  see, for example, tracking_dummy.py#L53-L55.
+  Alternatively, find an "autoload" solution for Python?
+
 ## Iteration +2
+- Apply database schema at connection time already. In this spirit, it does not need to be addresses everywhere by hand.
 - Bug: Fix SQL DDL files, see https://github.com/crate-workbench/mlflow-cratedb/issues/17
 - Other than the "MLflow Tracking" subsystem, is it sensible to unlock the "MLflow Model
   Registry" subsystem as well, when possible at all?

docs/container.md

@@ -18,6 +18,11 @@ For building your own images, see the [development documentation](./development.
 On GHCR, other than `latest` images for releases, there are also images for
 each PR, as well as `nightly` ones.
 
+On GHCR, you will find the following image tags:
+- `latest`: Points to the most recent release.
+- `main`: Builds of `main`, when pushing to this branch.
+- `nightly`: Builds of `main`, each morning a 4 o'clock CEST.
+
 
 ## Docker and Podman
 

tests/test_adapter.py

@@ -27,6 +27,7 @@ def store_empty(store):
         session.query(SqlExperiment).delete()
         for mapper in Base.registry.mappers:
             session.query(mapper.class_).delete()
+            # FIXME: `testdrive` is hardcoded here.
             sql = f"REFRESH TABLE testdrive.{mapper.class_.__tablename__};"
             session.execute(sa.text(sql))
     yield store