mirror of
https://github.com/bckelley/tconnectsync.git
synced 2026-08-24 03:34:12 -05:00
refactor: move process and synchronization code outside of main file
Splits up basal, bolus, and iob parsing code into separate files in the sync folder. Moves the single- cycle processing code into process.py
This commit is contained in:
James Woglom
@@ -11,18 +11,7 @@ import time
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from tconnectsync.api import TConnectApi
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from tconnectsync.api.common import ApiException
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from tconnectsync.parser import TConnectEntry
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from tconnectsync.nightscout import (
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NightscoutEntry,
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upload_nightscout,
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delete_nightscout,
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put_nightscout,
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last_uploaded_nightscout_entry,
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last_uploaded_nightscout_activity,
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BASAL_EVENTTYPE,
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BOLUS_EVENTTYPE,
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IOB_ACTIVITYTYPE
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)
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from tconnectsync.process import process_time_range
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try:
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from secret import (
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@@ -35,242 +24,7 @@ except Exception:
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print('Unable to import secret.py')
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sys.exit(1)
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"""
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Merges together input from the therapy timeline API into a digestable format of basal data.
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"""
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def process_ciq_basal_events(data):
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if data is None:
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return []
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suspensionEvents = {}
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for s in data["suspensionDeliveryEvents"]:
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entry = TConnectEntry.parse_suspension_entry(s)
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suspensionEvents[entry["time"]] = entry
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basalEvents = []
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for b in data["basal"]["tempDeliveryEvents"]:
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basalEvents.append(TConnectEntry.parse_ciq_basal_entry(b, delivery_type="tempDelivery"))
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for b in data["basal"]["algorithmDeliveryEvents"]:
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basalEvents.append(TConnectEntry.parse_ciq_basal_entry(b, delivery_type="algorithmDelivery"))
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for b in data["basal"]["profileDeliveryEvents"]:
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basalEvents.append(TConnectEntry.parse_ciq_basal_entry(b, delivery_type="profileDelivery"))
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basalEvents.sort(key=lambda x: arrow.get(x["time"]))
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for i in basalEvents:
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if i["time"] in suspensionEvents:
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i["suspendReason"] = suspensionEvents[i["time"]]["suspendReason"]
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return basalEvents
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"""
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Processes basal data input from the therapy timeline CSV (which only exists for pre Control-IQ data) into a digestable format.
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"""
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def add_csv_basal_events(basalEvents, data):
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last_entry = None
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for row in data:
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entry = TConnectEntry.parse_csv_basal_entry(row)
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if last_entry:
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diff_mins = (arrow.get(entry["time"]) - arrow.get(last_entry["time"])).seconds // 60
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entry["duration_mins"] = diff_mins
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basalEvents.append(entry)
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last_entry = entry
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basalEvents.sort(key=lambda x: arrow.get(x["time"]))
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return basalEvents
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"""
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Given processed basal data, adds basal events to Nightscout.
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"""
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def ns_write_basal_events(basalEvents, pretend=False):
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last_upload = last_uploaded_nightscout_entry(BASAL_EVENTTYPE)
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last_upload_time = None
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if last_upload:
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last_upload_time = arrow.get(last_upload["created_at"])
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print("Last Nightscout basal upload:", last_upload_time)
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add_count = 0
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for event in basalEvents:
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if last_upload_time and arrow.get(event["time"]) < last_upload_time:
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if pretend:
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print("Skipping basal event before last upload time:", event)
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continue
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recent_needs_update = False
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if last_upload_time and arrow.get(event["time"]) == last_upload_time:
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# If this entry has the same time as the most recent upload, but
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# has newer info, then delete and recreate it.
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recent_needs_update = (round(last_upload["duration"]) < round(event["duration_mins"]))
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reason = event["delivery_type"]
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if "suspendReason" in reason:
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reason += " (" + reason["suspendReason"] + ")"
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entry = NightscoutEntry.basal(
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value=event["basal_rate"],
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duration_mins=event["duration_mins"],
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created_at=event["time"],
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reason=reason
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)
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add_count += 1
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print(" Processing basal:", event, "entry:", entry)
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if recent_needs_update:
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print("Replacing last uploaded entry:", last_upload)
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if not pretend:
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entry['_id'] = last_upload['_id']
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put_nightscout(entry, entity='treatments')
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elif not pretend:
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upload_nightscout(entry)
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return add_count
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"""
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Given bolus data input from the therapy timeline CSV, converts it into a digestable format.
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"""
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def process_bolus_events(bolusdata):
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bolusEvents = []
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for b in bolusdata:
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parsed = TConnectEntry.parse_bolus_entry(b)
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if parsed["completion"] != "Completed":
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if parsed["insulin"] and float(parsed["insulin"]) > 0:
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# Count non-completed bolus if any insulin was delivered (vs. the amount of insulin requested)
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parsed["description"] += " (%s)" % parsed["completion"]
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else:
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print("Skipping non-completed bolus data:", b, "parsed:", parsed)
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continue
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bolusEvents.append(parsed)
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bolusEvents.sort(key=lambda event: arrow.get(event["completion_time"] if not event["extended_bolus"] else event["bolex_start_time"]))
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return bolusEvents
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"""
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Given processed bolus data, adds bolus events to Nightscout.
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"""
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def ns_write_bolus_events(bolusEvents, pretend=False):
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last_upload = last_uploaded_nightscout_entry(BOLUS_EVENTTYPE)
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last_upload_time = None
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if last_upload:
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last_upload_time = arrow.get(last_upload["created_at"])
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print("Last Nightscout bolus upload:", last_upload_time)
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add_count = 0
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for event in bolusEvents:
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if last_upload_time and arrow.get(event["completion_time"]) <= last_upload_time:
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if pretend:
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print("Skipping basal event before last upload time:", event)
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continue
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entry = NightscoutEntry.bolus(
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bolus=event["insulin"],
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carbs=event["carbs"],
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created_at=event["completion_time"] if not event["extended_bolus"] else event["bolex_start_time"],
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notes="{}{}{}".format(event["description"], " (Override)" if event["user_override"] == "1" else "", " (Extended)" if event["extended_bolus"] == "1" else "")
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)
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add_count += 1
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print(" Processing bolus:", event, "entry:", entry)
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if not pretend:
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upload_nightscout(entry)
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return add_count
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"""
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Given IOB data input from the therapy timeline CSV, converts it into a digestable format.
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"""
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def process_iob_events(iobdata):
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iobEvents = []
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for d in iobdata:
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iobEvents.append(TConnectEntry.parse_iob_entry(d))
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iobEvents.sort(key=lambda x: arrow.get(x["time"]))
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return iobEvents
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"""
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Given processed IOB data, creates a single Nightscout activity definition to store IOB.
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"""
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def ns_write_iob_events(iobEvents, pretend=False):
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last_upload = last_uploaded_nightscout_activity(IOB_ACTIVITYTYPE)
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last_upload_time = None
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if last_upload:
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last_upload_time = arrow.get(last_upload["created_at"])
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print("Last Nightscout iob upload:", last_upload_time)
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if not iobEvents or len(iobEvents) == 0:
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print("No IOB events: skipping")
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return 0
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event = iobEvents[-1]
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if last_upload_time and arrow.get(event["time"]) <= last_upload_time:
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print(" Skipping already uploaded iob event:", event)
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return 0
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entry = NightscoutEntry.iob(
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iob=event["iob"],
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created_at=event["time"]
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)
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print(" Processing iob:", event, "entry:", entry)
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if not pretend:
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upload_nightscout(entry, entity='activity')
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# Delete the previous activity
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if last_upload and '_id' in last_upload:
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print(" Deleting old iob entry:", last_upload)
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if not pretend:
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delete_nightscout('activity/{}'.format(last_upload['_id']))
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return 1
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def process_time_range(tconnect, time_start, time_end, pretend):
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print("Downloading t:connect ControlIQ data")
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try:
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ciqBasalData = tconnect.controliq.therapy_timeline(time_start, time_end)
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except ApiException as e:
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# The ControlIQ API returns a 404 if the user did not have a ControlIQ enabled
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# device in the time range which is queried. Since it launched in early 2020,
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# ignore 404's before February.
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if e.status_code == 404 and time_start.date() < datetime.date(2020, 2, 1):
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print("Ignoring HTTP 404 for ControlIQ API request before Feb 2020")
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ciqBasalData = None
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else:
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raise e
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print("Downloading t:connect CSV data")
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csvdata = tconnect.ws2.therapy_timeline_csv(time_start, time_end)
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readingData = csvdata["readingData"]
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iobData = csvdata["iobData"]
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csvBasalData = csvdata["basalData"]
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bolusData = csvdata["bolusData"]
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if readingData and len(readingData) > 0:
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print("Last CGM reading from t:connect:", readingData[-1]['EventDateTime'] if 'EventDateTime' in readingData[-1] else readingData)
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added = 0
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basalEvents = process_ciq_basal_events(ciqBasalData)
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if csvBasalData:
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add_csv_basal_events(basalEvents, csvBasalData)
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added += ns_write_basal_events(basalEvents, pretend=pretend)
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bolusEvents = process_bolus_events(bolusData)
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added += ns_write_bolus_events(bolusEvents, pretend=pretend)
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iobEvents = process_iob_events(iobData)
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added += ns_write_iob_events(iobEvents, pretend=pretend)
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return added
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def parse_args():
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parser = argparse.ArgumentParser(description="Syncs bolus, basal, and IOB data from Tandem Diabetes t:connect to Nightscout.")
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