added new function to handle cm-specific timestamp formatting

precog/miners/base_miner.py

@@ -6,7 +6,7 @@
 
 from precog.protocol import Challenge
 from precog.utils.cm_data import CMData
-from precog.utils.timestamp import datetime_to_iso8601, iso8601_to_datetime
+from precog.utils.timestamp import datetime_to_CM_timestamp, iso8601_to_datetime
 
 
 def get_point_estimate(timestamp: str) -> float:
@@ -23,8 +23,8 @@ def get_point_estimate(timestamp: str) -> float:
 
     # Set the time range to be as small as possible for query speed
     # Set the start time as 2 seconds prior to the provided time
-    start_time: str = datetime_to_iso8601(iso8601_to_datetime(timestamp) - timedelta(seconds=2))
-    end_time: str = timestamp
+    start_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp) - timedelta(days=1))
+    end_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp))  # built-ins handle CM API's formatting
 
     # Query CM API for a pandas dataframe with only one record
     price_data: pd.DataFrame = cm.get_CM_ReferenceRate(assets="BTC", start=start_time, end=end_time)
@@ -56,8 +56,8 @@ def get_prediction_interval(timestamp: str, point_estimate: float) -> Tuple[floa
     cm = CMData()
 
     # Set the time range to be 24 hours
-    start_time: str = datetime_to_iso8601(iso8601_to_datetime(timestamp) - timedelta(days=1))
-    end_time: str = timestamp
+    start_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp) - timedelta(days=1))
+    end_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp))  # built-ins handle CM API's formatting
 
     # Query CM API for sample standard deviation of the 1s residuals
     historical_price_data: pd.DataFrame = cm.get_CM_ReferenceRate(

precog/utils/timestamp.py

@@ -66,14 +66,14 @@ def datetime_to_iso8601(timestamp: datetime) -> str:
     """
     Convert datetime to iso 8601 string
     """
-    return timestamp.strftime("%Y-%m-%dT%H:%M:%S.%fZ")
+    return timestamp.isoformat()
 
 
 def iso8601_to_datetime(timestamp: str) -> datetime:
     """
     Convert iso 8601 string to datetime
     """
-    return datetime.strptime(timestamp, "%Y-%m-%dT%H:%M:%S.%fZ")
+    return datetime.fromisoformat(timestamp)
 
 
 def posix_to_datetime(timestamp: float) -> datetime:
@@ -83,6 +83,13 @@ def posix_to_datetime(timestamp: float) -> datetime:
     return datetime.fromtimestamp(timestamp, tz=get_timezone())
 
 
+def datetime_to_CM_timestamp(timestamp: datetime) -> str:
+    """
+    Convert iso 8601 string to coinmetrics timestamp
+    """
+    return timestamp.strftime("%Y-%m-%dT%H:%M:%S.%fZ")
+
+
 ###############################
 #          FUNCTIONS          #
 ###############################
@@ -155,7 +162,7 @@ def align_timepoints(filtered_pred_dict, cm_dict):
 
     Args:
         filtered_pred_dict (dict): {datetime: float} dictionary of predictions.
-        cm_data (dict): {datetime: float} dictionary of coinmetrics prices.
+        cm_data (dict): {datetime: float} dictionary of prices.
 
 
     Returns:

precog/validators/reward.py

@@ -8,7 +8,7 @@
 from precog.protocol import Challenge
 from precog.utils.cm_data import CMData
 from precog.utils.general import pd_to_dict, rank
-from precog.utils.timestamp import align_timepoints, datetime_to_iso8601, iso8601_to_datetime, mature_dictionary
+from precog.utils.timestamp import align_timepoints, datetime_to_CM_timestamp, iso8601_to_datetime, mature_dictionary
 
 
 ################################################################################
@@ -24,8 +24,8 @@ def calc_rewards(
     decayed_weights = decay**weights
     timestamp = responses[0].timestamp
     cm = CMData()
-    start_time: str = datetime_to_iso8601(iso8601_to_datetime(timestamp) - timedelta(hours=1))
-    end_time: str = datetime_to_iso8601(iso8601_to_datetime(timestamp))  # built-ins handle CM API's formatting
+    start_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp) - timedelta(hours=1))
+    end_time: str = datetime_to_CM_timestamp(iso8601_to_datetime(timestamp))  # built-ins handle CM API's formatting
     # Query CM API for sample standard deviation of the 1s residuals
     historical_price_data: DataFrame = cm.get_CM_ReferenceRate(
         assets="BTC", start=start_time, end=end_time, frequency="1s"