feat: add built-in run_test_experiment job to test the mlflow server internally so its super easy to test if it actually works e2e

test_experiment/mlflow_tracking.py

@@ -0,0 +1,22 @@
+import os
+from random import random, randint
+
+import mlflow
+
+if __name__ == "__main__":
+    with mlflow.start_run() as run:
+        mlflow.set_tracking_uri('http://mlflow:5000')
+        print("Running mlflow_tracking.py")
+
+        mlflow.log_param("param1", randint(0, 100))
+        
+        mlflow.log_metric("foo", random())
+        mlflow.log_metric("foo", random() + 1)
+        mlflow.log_metric("foo", random() + 2)
+
+        if not os.path.exists("outputs"):
+            os.makedirs("outputs")
+        with open("outputs/test.txt", "w") as f:
+            f.write("hello world!")
+
+        mlflow.log_artifacts("outputs")