setting it up as a straightforward rest api

app.py

@@ -1,6 +1,6 @@
-from flask import Flask, request
-import numpy as np
+from flask import Flask, request, jsonify, make_response
 
+from dataset.random import random_dataset
 from opts import options
 
 app = Flask(
@@ -10,25 +10,43 @@ app = Flask(
 )
 
 
-@app.route("/", methods=["GET"])
-def index():
+def is_valid(params: dict):
+    """
+    is_valid() simply checks if
+    an incoming response is valid
+    for this api or not. Key to
+    avoiding errors
+    """
+    if not request.json():
+        return False
 
-    # make sure the request is valid
-    def is_valid():
-        if request.method == "GET":
-            return True
+    if "Algorithm" not in params:
         return False
 
-    if not is_valid():
-        return  # bad request status code and error message
+    if params["Algorithm"] not in options:
+        return False
+    return True
 
-    # parse arguments
 
-    # perform analysis of choice
+@app.route("/", methods=["GET"])
+def index():
+
+    params = request.json()
+    if not is_valid(params=params):
+        return make_response(400, "bad request")
 
-    # return results
+    # parse arguments
+    algorithm = options[params["Algorithm"]]
+    args = options[params["Arguments"]]
+
+    X, y = random_dataset()
+    results = algorithm.main(
+        X=X,
+        y=y,
+        args=args,
+    )
 
-    return
+    return jsonify(results)
 
 
 if __name__ == '__main__':