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It offers specialised tools to tackle challenges of repeated measures data, ideal for (med.) researchers, data scientists, & analysts." authors = [ {name = "Provost Simon", email = "simon.gilbert.provost@gmail.com"}, @@ -55,6 +55,7 @@ lint = [ "docformatter[tomli]<2.0.0,>=1.6.4", ] test = [ + "pytest>=4.4.0", "pytest-cov>=4.0.0", "genbadge>=1.1.0" ] @@ -92,7 +93,7 @@ update_lock = {cmd = "pdm lock", env_file.override = ".env"} update_lock_dev = {cmd = "pdm lock -d", env_file.override = ".env"} # Testing and linting (Note: This has only been tested on Linux && OSX) -_install_dev = { cmd = "pdm install -G lint -G test -G doc --no-default", env_file.override = ".env" } +_install_dev = { cmd = "pdm install -G lint -G test -G doc", env_file.override = ".env" } install_dev = {composite = ["_set_pdm_use_venv", "_install_dev"]} tests = {cmd = "pytest scikit_longitudinal/ --cov=./ --cov-report=html --cov-config=.coveragerc --cov-report=html:htmlcov/scikit_longitudinal -s -vv --capture=no"} diff --git a/setup.py b/setup.py index 9e4713d..4fcc4fa 100644 --- a/setup.py +++ b/setup.py @@ -2,7 +2,7 @@ setup( # pragma: no cover name="Scikit-longitudinal", - version="0.0.4", + version="0.0.5", long_description=open('README.md').read(), long_description_content_type='text/markdown', url="https://github.com/simonprovost/scikit-longitudinal",