✨ setup pyproject.toml file

- 🐛 if namespaces are used by default, this can lead to subpackages being installed...

pyproject.toml

@@ -1,3 +1,65 @@
+[project]
+authors = [{ name = "Henry Webel", email = "[email protected]" }]
+description = "Imputing (MS-based prote-) omics data using self supervised deep learning models."
+name = "pimms-learn"
+# This means: Load the version from the package itself.
+# See the section below: [tools.setuptools.dynamic]
+dynamic = ["version"]
+readme = "README.md"
+requires-python = ">=3.8, <3.9"
+# These are keywords
+classifiers = [
+  "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
+  "Intended Audience :: Healthcare Industry",
+  "Intended Audience :: Science/Research",
+  "Programming Language :: Python :: 3",
+  "Topic :: Scientific/Engineering :: Bio-Informatics",
+]
+dependencies = [
+  "njab",
+  "numpy",
+  "matplotlib",
+  "pandas",
+  "plotly",
+  "torch",
+  "scikit-learn>=1.0",
+  "scipy",
+  "seaborn<0.13",
+  "fastai",
+  "omegaconf",
+  "tqdm",
+  "mrmr-selection",
+  "pingouin",
+]
+
+[project.scripts]
+pimms-setup-imputation-comparison = "vaep.cmd_interface.setup_imp_cp_website:main"
+
+[project.urls]
+"Bug Tracker" = "https://github.com/RasmussenLab/pimms/issues"
+"Homepage" = "https://github.com/RasmussenLab/pimms"
+
+[project.optional-dependencies]
+docs = [
+  "sphinx",
+  "sphinx-book-theme",
+  "myst-nb",
+  "ipywidgets",
+  "sphinx-new-tab-link!=0.2.2",
+]
+
+[tool.flake8]
+max-line-length = 120
+aggressive = 2
+ignore = ["E501"]
+
 [build-system]
-requires = ["setuptools", "wheel"]
-build-backend = "setuptools.build_meta"
+build-backend = "setuptools.build_meta"
+requires = ["setuptools>=64", "setuptools_scm>=8", "wheel"]
+
+[tool.setuptools_scm]
+# https://setuptools-scm.readthedocs.io/ 
+# used to pick up the version from the git tags or the latest commit.
+
+[tool.setuptools.packages.find]
+include = ["vaep"]

setup.cfg

@@ -1,57 +1,8 @@
-[metadata]
-name = pimms-learn
-version = attr:vaep.__version__
-description = Imputing (MS-based prote-) omics data using self supervised deep learning models
-long_description = file: README.md
-long_description_content_type = text/markdown
-url = https://github.com/RasmussenLab/pimms
-author = Henry Webel
-author_email = "Henry Webel" <[email protected]>
-license = gpl-3.0
-license_files = LICENSE
-classifiers =
-    License :: OSI Approved :: GNU General Public License v3 (GPLv3)
-    Intended Audience :: Healthcare Industry
-    Intended Audience :: Science/Research
-    Programming Language :: Python :: 3
-    Topic :: Scientific/Engineering :: Bio-Informatics
-[options]
-# package_dir =
-packages = find:
-include_package_data = True
-install_requires =
-    njab
-    numpy
-    matplotlib
-    pandas
-    plotly
-    torch
-    scikit-learn>=1.0
-    scipy
-    seaborn<0.13
-    fastai
-    omegaconf
-    tqdm
-    mrmr-selection
-    pingouin
-
-[options.extras_require]
-docs =
-    sphinx
-    sphinx-book-theme
-    myst-nb
-    sphinx-new-tab-link!=0.2.2
-
 
 [options.packages.find]
 # where = vaep
 exclude =
     test*
-
-[options.entry_points]
-console_scripts =
-    pimms-setup-imputation-comparison = vaep.cmd_interface.setup_imp_cp_website:main
-
 ######################
 # Tool configuration #
 ######################

setup.py

@@ -1,2 +1,3 @@
 from setuptools import setup
+
 setup()

vaep/__init__.py

@@ -3,30 +3,36 @@
 Variatonal autoencoder for proteomics
 """
 from __future__ import annotations
-# Set default logging handler to avoid "No handler found" warnings.
-import logging
-from logging import NullHandler
 
-logging.getLogger(__name__).addHandler(NullHandler())
+# Set default logging handler to avoid "No handler found" warnings.
+import logging as _logging
+from importlib import metadata
 
-# put into some pandas_cfg.py file and import all
 import pandas as pd
 import pandas.io.formats.format as pf
 
-import vaep.pandas
-import vaep.plotting
+# from . import logging, nb, pandas, plotting
 import vaep.logging
+import vaep.nb
+import vaep.pandas
 import vaep.plotting
 
-import vaep.nb
+_logging.getLogger(__name__).addHandler(_logging.NullHandler())
+
+
+# put into some pandas_cfg.py file and import all
+
 
 savefig = vaep.plotting.savefig
 
 __license__ = 'GPLv3'
-__version__ = (0, 2, 0)
+__version__ = metadata.version("pimms-learn")
 
+__all__ = ['logging', 'nb', 'pandas', 'plotting', 'savefig']
 
 # set some defaults
+
+
 class IntArrayFormatter(pf.GenericArrayFormatter):
     def _format_strings(self):
         formatter = self.formatter or '{:,d}'.format