Add codecov

.github/workflows/ci.yml

@@ -36,5 +36,11 @@ jobs:
           python-version: ${{ matrix.python-version }}
       - name: Run tests
         run: |
-          make init
-          make test
+          pip install -e .[test]
+          pytest --cov-report=xml --no-cov-on-fail
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }} # use token for more robust uploads
+          name: ${{ matrix.python-version }}
+          fail_ci_if_error: false

README.md

@@ -7,6 +7,7 @@
 ![Read the Docs](https://img.shields.io/readthedocs/causalpy)
 ![PyPI - Downloads](https://img.shields.io/pypi/dm/causalpy)
 ![Interrogate](img/interrogate_badge.svg)
+[![codecov](https://codecov.io/gh/pymc-labs/CausalPy/branch/main/graph/badge.svg?token=FDKNAY5CZ9)](https://codecov.io/gh/pymc-labs/CausalPy)
 
 A Python package focussing on causal inference in quasi-experimental settings. The package allows for sophisticated Bayesian model fitting methods to be used in addition to traditional OLS.
 

codecov.yml

@@ -0,0 +1,16 @@
+coverage:
+  status:
+    project:
+      default:
+        # basic
+        target: auto
+        threshold: 2%
+        base: auto
+        paths:
+          - "causalpy/"
+       # advanced settings
+        branches:
+          - main
+        if_ci_failed: error #success, failure, error, ignore
+        informational: false
+        only_pulls: false