Add parquet and sqlite support; add NNLS-based PEP and Q-value calculation

.github/workflows/tests.yml

@@ -2,9 +2,13 @@ name: tests
 
 on:
   push:
-    branches: [ main ]
+    branches:
+      - main
+      - develop
   pull_request:
-    branches: [ main ]
+    branches:
+      - main
+      - develop
 
 jobs:
   build:

.gitignore

@@ -109,3 +109,5 @@ venv.bak/
 # idea
 .idea/
 
+tests/integration_tests/run*
+

.gitlab-ci.yml

@@ -0,0 +1,50 @@
+image: python:3.10.5
+
+variables:
+  PIP_CACHE_DIR: "${CI_PROJECT_DIR}/.cache/pip"
+
+stages:
+  - publish
+  - test
+
+cache:
+  key: "${CI_COMMIT_REF_SLUG}"
+  paths:
+    - .cache/pip
+    - .venv
+
+.with_twine:
+  before_script:
+    - python -m pip install --upgrade pip
+    - pip install setuptools wheel twine build pip-licenses
+
+
+gather-licences:
+  extends: .with_twine
+  stage: publish
+  script:
+    - pip-licenses --from=mixed --order=license --with-system -f markdown --output-file LICENSES.md
+  artifacts:
+    when: always
+    paths:
+      - LICENSES.md
+    expire_in: 4 week
+
+
+publish:
+  extends: .with_twine
+  stage: publish
+  rules:
+    - if: '$CI_COMMIT_TAG != null'
+  script:
+    - python -m build --sdist --wheel .
+    - TWINE_PASSWORD=${CI_JOB_TOKEN} TWINE_USERNAME=gitlab-ci-token python -m twine upload --repository-url https://gitlab.com/api/v4/projects/${CI_PROJECT_ID}/packages/pypi dist/*
+
+unit_test:
+  extends: .with_twine
+  stage: test
+  script:
+    - pip install .[dev]
+    - pip install pytest
+    - pytest tests/
+

README.md

@@ -1,11 +1,5 @@
-<img src="https://raw.githubusercontent.com/wfondrie/mokapot/master/static/mokapot_logo_dark.svg" width=300>  
-
----  
-[![conda](https://img.shields.io/conda/vn/bioconda/mokapot?color=green)](http://bioconda.github.io/recipes/mokapot/README.html)
-[![PyPI](https://img.shields.io/pypi/v/mokapot?color=green)](https://pypi.org/project/mokapot/)
-[![tests](https://github.com/wfondrie/mokapot/workflows/tests/badge.svg)](https://github.com/wfondrie/mokapot/actions?query=workflow%3Atests)
-[![docs](https://readthedocs.org/projects/mokapot/badge/?version=latest)](https://mokapot.readthedocs.io/en/latest/?badge=latest)
 
+[![pipeline status](https://gitlab.com/msaid/inferys/mokapot/badges/main/pipeline.svg)](https://gitlab.com/msaid/inferys/mokapot/-/commits/main)
 
 
 Fast and flexible semi-supervised learning for peptide detection.  
@@ -70,11 +64,12 @@ Alternatively, the Python API can be used to perform analyses in the Python
 interpreter and affords greater flexibility:
 
 ```Python
->>> import mokapot
->>> psms = mokapot.read_pin("psms.pin")
->>> results, models = mokapot.brew(psms)
->>> results.to_txt()
+import mokapot
+psms = mokapot.read_pin("psms.pin")
+results, models = mokapot.brew(psms)
+results.to_txt()
 ```
 
 Check out our [documentation](https://mokapot.readthedocs.io) for more details
 and examples of mokapot in action.
+