database example

unit-test.html

@@ -162,10 +162,17 @@ <h3>Content</h3>
 
       <section id="introduction">
         <h2>Introduction</h2>
-        (<strong>Reference: </strong>For more details, please checkout my github repo: <a href="https://github.com/arunp77/Data-engineering-tools/tree/main/Unit-test" target="_blank">Unit testing</a>.)
         Unit testing is a software testing technique where individual units or components of a software application are tested in isolation. The main purpose is to validate that each unit of the software 
         performs as designed. In data science and analytics, unit testing can be applied to functions, modules, or algorithms to ensure they produce the expected output for a given set of inputs. It helps 
-        identify and fix bugs early in the development process, improving the overall reliability and maintainability of the code
+        identify and fix bugs early in the development process, improving the overall reliability and maintainability of the code. 
+
+        <div class="box">
+          <ul>
+            <li><strong>Reference: </strong>For more details, please checkout my github repo: <a href="https://github.com/arunp77/Data-engineering-tools/tree/main/Unit-test" target="_blank">Unit testing</a>.</li>
+            <li><strong>Note: </strong>
+              For the difference between the <code>unittest</code> and <code>pytest</code>, please visit the repo and the readme file in <a href="https://github.com/arunp77/Data-engineering-tools/blob/main/Unit-test/unittest_pytest.md" target="_blank">Unittesting and pytest differences</a>.</li>
+          </ul>
+        </div>
 
 
       <section>