Update experiment to new format

standalone_project/Dockerfile

@@ -1,17 +1,8 @@
 # Start from a base image
 FROM python:2.7-alpine
 
-# Install empirical library
-RUN apk add --update build-base wget
-
-# TODO: These should be replaced by pip install empirical
-RUN pip install zerorpc 
-RUN pip install requests
-
 # Add files
 COPY . /my-approach
 WORKDIR /my-approach
 
-RUN wget --no-check-certificate https://raw.githubusercontent.com/empiricalci/empirical.py/master/empirical.py
-
 ENTRYPOINT ["python", "main.py"]

standalone_project/dataset.json

@@ -0,0 +1,12 @@
+{
+  "resources": {
+    "answers": {
+      "url": "https://raw.githubusercontent.com/empiricalci/fixtures/master/answers.csv",
+      "hash": "3d7219dab4803e82ad97ece9a49fc25c6fd3762a369236d131cb729f32946ff2"
+    },
+    "somedata": {
+      "url": "https://raw.githubusercontent.com/empiricalci/fixtures/master/data.csv",
+      "hash": "75821d9915567987edd0ff3271e276c922218c638e05efb2955a32c4526abdd9"
+    }
+  }
+}      

standalone_project/empirical.yml

@@ -3,9 +3,4 @@ experiments:
     type: standalone
     environment:
       build: .
-    dataset:
-      resources:
-        - url: "https://raw.githubusercontent.com/empiricalci/fixtures/master/answers.csv"
-          hash: "3d7219dab4803e82ad97ece9a49fc25c6fd3762a369236d131cb729f32946ff2"
-        - url: "https://raw.githubusercontent.com/empiricalci/fixtures/master/data.csv"
-          hash: "75821d9915567987edd0ff3271e276c922218c638e05efb2955a32c4526abdd9"
+    dataset: dataset.json

standalone_project/main.py

@@ -1,4 +1,3 @@
-import empirical
 import csv
 
 # Define and Instantiate Solver
@@ -22,32 +21,25 @@ def read_answers():
 
 # Send problems to solvers
 dataset = read_data()
-print 'data:', dataset
 solutions = []
 for problem in dataset:
     solutions.append(solver.solve(*problem))
 
 # Evaluate solutions against ground truth
 answers = read_answers()
-print 'answers:', answers
 correct_count = 0
 for i in xrange(len(dataset)):
     if solutions[i] == answers[i]:
         correct_count = correct_count + 1
 
 accuracy = correct_count / len(dataset)
 
-# Save results
+# Save overall
 results = {
-    'overall': {
-        'type': 'table',
-        'metric': 'Accuracy',
-        'value': accuracy
-    }
+    'metric': 'Accuracy',
+    'value': accuracy
 }
-empirical.postResults(results)
 
-# Also save them to the workspace
 import json
-with open('/workspace/output.json', 'w') as output:
+with open('/workspace/overall.json', 'w') as output:
     json.dump(results, output)