Fix test_init_application unit test

README.md

@@ -55,7 +55,7 @@ This assumes you have Python 3.6+ installed.
 1. Create a virtual env: `python3 -m venv venv`
 1. `source venv/bin/activate`
 1. Install packages: `pip3 install -r requirements.txt`
-1. You can run an example app with this command `python -m rl_bakery.example.cartpole`
+1. You can run an example app with this command `python -m rl_bakery.example.cartpole_dqn`
 
 To run this on a Mac, you must install java to run locally with pyspark.  https://www.java.com/en/download/mac_download.jsp
 Add 'export JAVA_HOME=/Library/Internet\ Plug-Ins/JavaAppletPlugin.plugin/Contents/Home' to your .bash_profile

rl_bakery/applications/simulation_runner.py

@@ -96,7 +96,7 @@ def make_batch_tfenv(make_env, config, start_dt, training_interval, spark_sessio
     :param make_env: A function that returns an Environment
     :param config: An ApplicationConfig
     :param start_dt: A datetime being used to simulate the first action
-    :param training_interval: A datetime indicating the lag between when an observation is generated and when it can
+    :param training_interval: A timedelta indicating the lag between when an observation is generated and when it can
                            be used for training. This simulates real world environments where there's a delay between
                            data collection and Agent updates.
     :param spark_session: A Spark session

rl_bakery/applications/tfenv/test_tf_env_rl_application.py

@@ -1,8 +1,9 @@
-from datetime import datetime
+from datetime import datetime, timedelta
 from unittest import TestCase
 from tf_agents.environments import tf_py_environment, suite_gym
 from rl_bakery.applications.tfenv.indexed_tf_env import IndexedTFEnv
 from rl_bakery.applications.tfenv.tf_env_rl_application import TFEnvRLApplication
+from rl_bakery.spark_utilities import get_spark_session
 from unittest.mock import patch
 
 
@@ -26,5 +27,8 @@ def test_init_application(self, mock_dm):
 
         steps_num_per_run = 3
 
-        app = TFEnvRLApplication(envs, training_config, steps_num_per_run, datetime.now(), 2)
+        spark_session = get_spark_session()
+        app = TFEnvRLApplication(envs, spark_session, training_config, steps_num_per_run,
+                                 engine_start_dt=datetime.now(), engine_training_interval=timedelta(days=1),
+                                 num_partitions=2)
         self.assertListEqual(app.obs_cols, ['ob_0', 'ob_1', 'ob_2', 'ob_3'])