Removing some trailing whitespaces etc.

CHANGELOG.rst

@@ -2,9 +2,12 @@
 Changelog
 =========
 
+Version 0.2
+===========
+
+- Reworked the general layout some more
+
 Version 0.1
 ===========
 
-- Feature A added
-- FIX: nasty bug #1729 fixed
-- add your changes here!
+- Initial commit

README.md

@@ -5,11 +5,11 @@
 # pyscaffoldext-dsproject
 
 [PyScaffold] extension tailored for *Data Science* projects. This extension is inspired by
-[cookiecutter-data-science] and enhanced in many ways. The main differences are that it:
+[cookiecutter-data-science] and enhanced in many ways. The main differences are that it
 1. advocates a proper Python package structure that can be shipped and distributed,
 2. uses a [conda] environment instead of something `virtualenv` based and is thus more suitable
-   for data science projects.
-3. has tons more default configuration for [Sphinx], [py.test], [pre-commit], etc. to foster
+   for data science projects,
+3. more default configurations for [Sphinx], [py.test], [pre-commit], etc. to foster
    clean coding and best practices.
 
 The final directory structure looks like:
@@ -18,43 +18,43 @@ The final directory structure looks like:
 ├── CHANGELOG.rst           <- Changelog to keep track of new features and fixes between versions.
 ├── LICENSE.txt             <- License as chosen as specified on the command-line.
 ├── README.md               <- The top-level README for developers using this project.
-│                          
-├── data                   
+│
+├── data
 │   ├── external            <- Data from third party sources.
 │   ├── interim             <- Intermediate data that has been transformed.
 │   ├── processed           <- The final, canonical data sets for modeling.
 │   └── raw                 <- The original, immutable data dump.
-│                          
+│
 ├── docs                    <- Directory for Sphinx documentation as in the standard PyScaffold setup.
-│                          
+│
 ├── environment.yaml        <- The conda environment file for reproducing the analysis environment.
-│                          
+│
 ├── models                  <- Trained and serialized models, model predictions, or model summaries
-│                          
+│
 ├── notebooks               <- Jupyter notebooks. Naming convention is a number (for ordering),
 │                              the creator's initials, and a short `-` delimited description, e.g.
 │                              `1.0-fw-initial-data-exploration`.
-│                          
+│
 ├── references              <- Data dictionaries, manuals, and all other explanatory materials.
-│                          
+│
 ├── reports                 <- Generated analysis as HTML, PDF, LaTeX, etc.
 │   └── figures             <- Generated graphics and figures to be used in reporting
 │
 ├── scripts                 <- Analysis and production scripts which import the actual PYTHON_PKG,
 │                              e.g. train_model, run_model. etc.
-│                          
+│
 ├── setup.cfg               <- Declarative configuration of your project.
-│                          
-├── setup.py                <- Make this project pip installable with `pip install -e` 
-│                              or `python setup.py develop`. 
-│                                                  
+│
+├── setup.py                <- Make this project pip installable with `pip install -e`
+│                              or `python setup.py develop`.
+│
 ├── src
 │   └── PYTHON_PKG          <- Actual Python package where the main functionality goes.
-│                          
+│
 ├── tests                   <- Unit tests which can be run with `py.test` or `python setup.py test`.
-│                          
+│
 ├── .coveragerc             <- Configuration for coverage reports of unit tests.
-│                          
+│
 ├── .isort.cfg              <- Configuration for git hook that sorts imports.
 │
 └── .pre-commit-config.yaml <- Configuration of pre-commit git hooks.
@@ -67,7 +67,7 @@ the the documentation of [PyScaffold] for more information.
 ## Usage
 
 Just install this package with `pip install pyscaffoldext-dsproject`
-and note that `putup -h` shows a new option `--dsproject`. 
+and note that `putup -h` shows a new option `--dsproject`.
 Creating a data science project is then as easy as:
 ```
 putup --dsproject my_ds_project
@@ -85,4 +85,5 @@ information on PyScaffold see https://pyscaffold.org/.
 [dsproject-demo]: https://github.com/pyscaffold/dsproject-demo
 [Sphinx]: http://www.sphinx-doc.org/
 [py.test]: https://docs.pytest.org/
+[conda]: https://docs.conda.io/
 [pre-commit]: https://pre-commit.com/

src/pyscaffoldext/dsproject/templates/readme_md.template

@@ -10,7 +10,7 @@ A longer description of your project goes here...
 
 In order to set up the necessary environment:
 
-1. create an environment `${project}` with the help of [Miniconda],
+1. create an environment `${project}` with the help of [conda],
    ```
    conda env create -f environment.yaml
    ```
@@ -107,7 +107,7 @@ Then take a look into the `experiments` and `notebooks` folder.
 This project has been set up using PyScaffold ${version}. For details and usage
 information on PyScaffold see https://pyscaffold.org/.
 
-[Miniconda]: https://docs.conda.io/en/latest/miniconda.html
+[conda]: https://docs.conda.io/
 [pre-commit]: https://pre-commit.com/
 [Jupyter]: https://jupyter.org/
 [nbstripout]: https://github.com/kynan/nbstripout

src/pyscaffoldext/dsproject/templates/train_model_py.template

@@ -16,14 +16,17 @@ _logger = logging.getLogger(__name__)
 
 
 @click.command()
-@click.option('-c', '--config', 'cfg_path', required=True, type=click.Path(exists=True),
-              help='path to config file')
+@click.option('-c', '--config', 'cfg_path', required=True,
+              type=click.Path(exists=True), help='path to config file')
 @click.option('--quiet', 'log_level', flag_value=logging.WARNING, default=True)
 @click.option('-v', '--verbose', 'log_level', flag_value=logging.INFO)
 @click.option('-vv', '--very-verbose', 'log_level', flag_value=logging.DEBUG)
 @click.version_option(${package}.__version__)
 def main(cfg_path: Path, log_level: int):
-    logging.basicConfig(stream=sys.stdout, level=log_level)
+    logging.basicConfig(stream=sys.stdout,
+                        level=log_level,
+                        datefmt='%Y-%m-%d %H:%M',
+                        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
     # YOUR CODE GOES HERE! Keep the main functionality in src/${package}
     # est = ${package}.models.Estimator()