fix: pre commit and url fixes

Author: lwasser

ci-data/index.md

@@ -1 +1,2 @@
 aways
+Soler

codespell-ignore.txt

@@ -0,0 +1,11 @@
+(ci-cd-intro)=
+# Continuous Integration (CI) and Continuous Deployment (CD) for your Python package
+
+
+:::{toctree}
+:hidden:
+:caption: Continuous Integration
+
+
+What is CI?  <ci.md>
+:::

ci-data/ci.md renamed to continuous-integration/ci.md

@@ -324,8 +324,8 @@ Tests  <tests/index>
 
 :::{toctree}
 :hidden:
-:caption: CI & Data
+:caption: Continuous Integration
 
-CI & Data  <ci-data/index>
+CI/CD  <continuous-integration/index>
 
 :::

continuous-integration/index.md

@@ -34,7 +34,7 @@ Some common services for analyzing code coverage are [codecov.io](https://codeco
 :height: 450px
 :alt: Screenshot of the code cov service - showing test coverage for the stravalib package. This image shows a list of package modules and the associated number of lines and % lines covered by tests. At the top of the image, you can see what branch is being evaluated and the path to the repository.
 
-The CodeCov platform is a useful tool if you wish to track code coverage visually. Using it, you can not only get the same summary information that you can get with the **pytest-cov** extension. You can also see what lines are covered by your tests and what lines are not covered. Code coverage is useful for evaluating unit tests and/or how much of your package code is "covered". It, however, will not evaluate things like integration tests and end-to-end workflows.
+The CodeCov platform is a useful tool if you wish to track code coverage visually. Using it, you can not only get the same summary information that you can get with the **pytest-cov** extension. You can also see what lines are covered by your tests and which are not. Code coverage is useful for evaluating unit tests and/or how much of your package code is "covered". It, however, will not evaluate things like integration tests and end-to-end workflows.
 
 :::