connected manual samples to graphs
This commit is contained in:
Nico Melone
File diff suppressed because one or more lines are too long
@@ -5,7 +5,7 @@ codeuri = "/Users/nico/Documents/GitHub/ThingsBoard/EKKO Reports/thunderbirdfs-d
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runtime = "python3.9"
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architecture = "x86_64"
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handler = "thunderbirdfsreport.lambda_handler"
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source_hash = "96f09690c748fbb53cc41f4396ed0d83dfb501a3cb2710f29c4149645fc9c9fb"
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source_hash = "34ee8699205f989b1c9503c33660f39caa456af608fb961c68f13ce0fdacf18c"
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manifest_hash = ""
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packagetype = "Zip"
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functions = ["ThunderbirdFSReport"]
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Binary file not shown.
@@ -10,7 +10,7 @@ from email.mime.multipart import MIMEMultipart
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from email.mime.text import MIMEText
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from email import encoders
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from email.mime.base import MIMEBase
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from itertools import product
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logging.basicConfig(level=logging.DEBUG,
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format='%(asctime)s - %(levelname)s - %(module)s - %(lineno)d - %(message)s',
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@@ -50,7 +50,14 @@ def getTelemetry(rest_client, device, keys, start_ts, end_ts,limit):
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logging.error("Something went wrong in getTelemetry")
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logging.error(e)
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return False
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def getLatestTelemetry(rest_client, device, keys):
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try:
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return rest_client.get_latest_timeseries(entity_id=device.id, keys=keys) #entity_type=entity_type,
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except Exception as e:
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logging.error("Something went wrong in getTelemetry")
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logging.error(e)
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return False
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def getTime(timeRequest):
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@@ -91,12 +98,33 @@ def getThingsBoardData(url, username, password, targetCustomer, timeRequest):
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start_ts, end_ts = getTime(timeRequest)
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#print(keys)
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telemetry[d.name] = getTelemetry(rest_client=rest_client, device=device, keys=','.join(keys), start_ts=start_ts, end_ts=end_ts, limit=25000)
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latest = getLatestTelemetry(rest_client=rest_client, device=device, keys="manual_well,manual_tfs_lead,manual_copa_lead,manual_job_name")
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telemetry[d.name].update(latest)
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return telemetry
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except ApiException as e:
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logging.error(e)
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return False
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def getThingsBoardData(url, username, password, targetCustomer, timeRequest):
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# Creating the REST client object with context manager to get auto token refresh
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with RestClientCE(base_url=url) as rest_client:
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try:
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# Auth with credentials
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rest_client.login(username=username, password=password)
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# Get customers > get devices under a target customer > get keys for devices > get data for devices
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customers = rest_client.get_customers(page_size="100", page="0")
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devices = getDevices(rest_client=rest_client, customers=customers, target_customer=targetCustomer)
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telemetry = {}
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for d in devices.data:
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#print(d.name)
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device, keys, err = getDeviceKeys(rest_client=rest_client, devices=devices, target_device=d.name)
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start_ts, end_ts = getTime(timeRequest)
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#print(keys)
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telemetry[d.name] = getTelemetry(rest_client=rest_client, device=device, keys=','.join(keys), start_ts=start_ts, end_ts=end_ts, limit=25000)
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return telemetry
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except ApiException as e:
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logging.error(e)
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return False
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def getMaxWidth():
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label_mapping = {
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@@ -136,27 +164,34 @@ def formatColumnName(telemetryName):
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"Inlet Ph Temp": "INLET PH TEMP",
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"Ait 102b H2s": "INLET H₂S",
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"At 109b H2s": "OUTLET H₂S",
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"At 109c Oil In Water": "OUTLET DENSITY",
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"At 109c Oil In Water": "OUTLET OIW",
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"Ait 102a Turbitity": "INLET TURBIDITY",
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"At 109a Turbidity": "OUTLET TURBIDITY",
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"At 109e Orp": "OUTLET ORP",
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"Ait 102d Oil In Water": "INLET DENSITY"
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"Ait 102d Oil In Water": "INLET DENSITY",
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"Fit 106b Flow Rate": "SKIM FLOW RATE",
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"Manual Sample Time": "manual_sample_time",
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"Outlet Ph": "Outlet Ph"
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}
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return label_mapping.get(name, name)
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return label_mapping.get(name, telemetryName)
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def formatChartName(telemetryName):
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return " ".join([x.upper() for x in telemetryName.split("_")])
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def process_dataframe(telemetry, keys, time, special_handling=None, latest_only=False):
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def process_dataframe(telemetry, keys, time, special_handling=None, latest_only=False, all_keys=False):
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df = pd.DataFrame()
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# If latest_only is True, ensure missing keys are initialized
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if latest_only:
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if all_keys:
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now = dt.timestamp(dt.now())
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for key in keys:
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if key not in telemetry:
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telemetry[key] = [{'ts': dt.timestamp(dt.now()), 'value': '0'}]
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if key in special_handling["string"]:
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telemetry[key] = [{'ts': now, 'value': ''}]
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else:
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telemetry[key] = [{'ts': now, 'value': ''}]
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for datapoint in telemetry.keys():
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if datapoint in keys:
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@@ -192,9 +227,10 @@ def getManualDataFrame(telemetry, keys, time):
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telemetry, keys, time,
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special_handling={
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"datetime": ["manual_next_pigging_scheduled"],
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"string": ["manual_equipment_description", "manual_issues_concerns"]
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"string": ["manual_equipment_description", "manual_issues_concerns", "manual_well", "manual_tfs_lead", "manual_copa_lead", "manual_job_name", "manual_summary", "manual_hse_spills", "manual_quality_issues"]
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},
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latest_only=True
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latest_only=True,
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all_keys = True
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)
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def getSampleDataFrame(telemetry, keys, time):
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@@ -203,11 +239,10 @@ def getSampleDataFrame(telemetry, keys, time):
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special_handling={
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"datetime": ["manual_sample_time"],
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"string": ["manual_sample_datapoint", "manual_sample_lab", "manual_sample_location"]
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}
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},
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all_keys = True
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)
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def get_last_data_row(ws):
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# Start from the bottom row and work up to find the last row with data
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for row in range(ws.max_row, 0, -1):
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@@ -215,6 +250,60 @@ def get_last_data_row(ws):
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return row
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return 0 # If no data is found, return 0
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def transform_sample_telemetry(telemetry):
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transformed_telemetry = {}
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# Define mapping for Lab and Location
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lab_map = {"Thunderbird Lab": "T", "ConocoPhillips Lab": "C"}
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location_map = {"Inlet": "I", "Outlet": "O"}
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# Extract relevant sample keys
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times = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_time", [])}
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labs = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_lab", [])}
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locations = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_location", [])}
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datapoints = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_datapoint", [])}
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values = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_value", [])}
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# Iterate through available timestamps
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for ts in values.keys():
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lab = lab_map.get(labs.get(ts, ""), "Unknown")
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location = location_map.get(locations.get(ts, ""), "Unknown")
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datapoint = datapoints.get(ts, "Unknown")
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new_name = f"{lab}-{location}-{datapoint}"
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# Initialize if not exists
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if new_name not in transformed_telemetry:
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transformed_telemetry[new_name] = []
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transformed_telemetry[new_name].append({"ts": ts, "value": values[ts]})
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# Include manual_sample_time separately for indexing
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transformed_telemetry["manual_sample_time"] = [{"ts": ts, "value": times[ts]} for ts in times]
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if transformed_telemetry["manual_sample_time"]:
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return transformed_telemetry
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else:
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return {}
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def getSampleKeys():
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# Ensure all possible column combinations exist
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unique_labs = ['C', 'T']
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unique_locations = ['I', 'O']
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unique_datapoints = ['H2S', 'Density', 'ORP', 'O2', 'H2O2', 'pH', 'Turbidity', 'OIW']
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all_possible_columns = [
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f"{lab}-{loc}-{dp}" for lab, loc, dp in product(unique_labs, unique_locations, unique_datapoints)
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]
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all_possible_columns.append("manual_sample_time")
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return all_possible_columns
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def getSampleData(telemetry, device, keys):
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sample_data = {}
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for key in keys:
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temp = telemetry[device].get(key,None)
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if temp:
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sample_data[key] = temp
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return sample_data
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def lambda_handler(event, context):
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url = "https://www.enxlekkocloud.com"
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@@ -239,14 +328,16 @@ def lambda_handler(event, context):
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)
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reportsheet = writer.book.worksheets[0]
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keys = ['ait_102a_turbitity','ait_102b_h2s', 'at_109a_turbidity', 'at_109b_h2s', 'at_109c_oil_in_water', 'at_109e_orp', 'fit_100_flow_rate', 'fit_109b_flow_rate', 'lit_116b_level', 'lit_116a_level', 'outlet_turbidity_temp', 'outlet_orp_temp', 'inlet_turbidity_temp', 'inlet_ph_temp', 'ait_102d_oil_in_water','outlet_ph']
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manual_keys = ['manual_bag_filter_changes', 'manual_cartridge_filter_changes', 'manual_clean_water_sold_per_job', 'manual_coagulant_on_hand', 'manual_diverted_water_time', 'manual_equipment_description', 'manual_equipment_time', 'manual_h202_on_hand', 'manual_issues_concerns', 'manual_next_pigging_scheduled', 'manual_skim_oil_discharged_per_job', 'manual_standby_time', 'manual_unit_uptime', 'manual_upright_tank_issues', 'manual_vac_truck_batches', 'manual_water_events', 'manual_water_events_time', 'manual_water_to_tanks_time']
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keys = ['ait_102a_turbitity','ait_102b_h2s', 'at_109a_turbidity', 'at_109b_h2s', 'at_109c_oil_in_water', 'at_109e_orp', 'fit_100_flow_rate', 'fit_109b_flow_rate', 'lit_116b_level', 'lit_116a_level', 'outlet_turbidity_temp', 'outlet_orp_temp', 'inlet_turbidity_temp', 'inlet_ph_temp', 'ait_102d_oil_in_water','outlet_ph','fit_106b_flow_rate']
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manual_keys = ['manual_bag_filter_changes', 'manual_cartridge_filter_changes', 'manual_clean_water_sold_per_job', 'manual_coagulant_on_hand', 'manual_diverted_water_time', 'manual_equipment_description', 'manual_equipment_time', 'manual_h202_on_hand', 'manual_issues_concerns', 'manual_next_pigging_scheduled', 'manual_skim_oil_discharged_per_job', 'manual_standby_time', 'manual_unit_uptime', 'manual_upright_tank_issues', 'manual_vac_truck_batches', 'manual_water_events', 'manual_water_events_time', 'manual_water_to_tanks_time',"manual_well", "manual_tfs_lead", "manual_copa_lead", "manual_job_name", "manual_summary", "manual_hse_spills", "manual_quality_issues"]
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sample_keys = ['manual_sample_datapoint', 'manual_sample_lab', 'manual_sample_location', 'manual_sample_time', 'manual_sample_value']
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#Create a Sheet for each Device
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for device in telemetry.keys():
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df = getDataFrame(telemetry[device], keys, time)
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dfm = getManualDataFrame(telemetry[device], manual_keys, time)
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dfs = getSampleDataFrame(telemetry[device], sample_keys, time)
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processed_sample_keys = getSampleKeys()
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sample_data = transform_sample_telemetry(getSampleData(telemetry=telemetry,device=device,keys=sample_keys))
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dfs = getSampleDataFrame(sample_data, processed_sample_keys, time)
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# Write the dataframe data to XlsxWriter. Turn off the default header and
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# index and skip one row to allow us to insert a user defined header.
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df.to_excel(writer, sheet_name=device, startrow=0, header=True, index=True, float_format="%.2f")
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Binary file not shown.
Binary file not shown.
@@ -10,7 +10,7 @@ from email.mime.multipart import MIMEMultipart
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from email.mime.text import MIMEText
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from email import encoders
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from email.mime.base import MIMEBase
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from itertools import product
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logging.basicConfig(level=logging.DEBUG,
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format='%(asctime)s - %(levelname)s - %(module)s - %(lineno)d - %(message)s',
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@@ -50,7 +50,14 @@ def getTelemetry(rest_client, device, keys, start_ts, end_ts,limit):
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logging.error("Something went wrong in getTelemetry")
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logging.error(e)
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return False
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def getLatestTelemetry(rest_client, device, keys):
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try:
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return rest_client.get_latest_timeseries(entity_id=device.id, keys=keys) #entity_type=entity_type,
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except Exception as e:
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logging.error("Something went wrong in getTelemetry")
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logging.error(e)
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return False
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def getTime(timeRequest):
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@@ -91,12 +98,33 @@ def getThingsBoardData(url, username, password, targetCustomer, timeRequest):
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start_ts, end_ts = getTime(timeRequest)
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#print(keys)
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telemetry[d.name] = getTelemetry(rest_client=rest_client, device=device, keys=','.join(keys), start_ts=start_ts, end_ts=end_ts, limit=25000)
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latest = getLatestTelemetry(rest_client=rest_client, device=device, keys="manual_well,manual_tfs_lead,manual_copa_lead,manual_job_name")
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telemetry[d.name].update(latest)
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return telemetry
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except ApiException as e:
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logging.error(e)
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return False
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def getThingsBoardData(url, username, password, targetCustomer, timeRequest):
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# Creating the REST client object with context manager to get auto token refresh
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with RestClientCE(base_url=url) as rest_client:
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try:
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# Auth with credentials
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rest_client.login(username=username, password=password)
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# Get customers > get devices under a target customer > get keys for devices > get data for devices
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customers = rest_client.get_customers(page_size="100", page="0")
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devices = getDevices(rest_client=rest_client, customers=customers, target_customer=targetCustomer)
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telemetry = {}
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for d in devices.data:
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#print(d.name)
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device, keys, err = getDeviceKeys(rest_client=rest_client, devices=devices, target_device=d.name)
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start_ts, end_ts = getTime(timeRequest)
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#print(keys)
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telemetry[d.name] = getTelemetry(rest_client=rest_client, device=device, keys=','.join(keys), start_ts=start_ts, end_ts=end_ts, limit=25000)
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return telemetry
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except ApiException as e:
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logging.error(e)
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return False
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def getMaxWidth():
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label_mapping = {
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@@ -136,27 +164,34 @@ def formatColumnName(telemetryName):
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"Inlet Ph Temp": "INLET PH TEMP",
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"Ait 102b H2s": "INLET H₂S",
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"At 109b H2s": "OUTLET H₂S",
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"At 109c Oil In Water": "OUTLET DENSITY",
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"At 109c Oil In Water": "OUTLET OIW",
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"Ait 102a Turbitity": "INLET TURBIDITY",
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"At 109a Turbidity": "OUTLET TURBIDITY",
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"At 109e Orp": "OUTLET ORP",
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"Ait 102d Oil In Water": "INLET DENSITY"
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"Ait 102d Oil In Water": "INLET DENSITY",
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"Fit 106b Flow Rate": "SKIM FLOW RATE",
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"Manual Sample Time": "manual_sample_time",
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"Outlet Ph": "Outlet Ph"
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}
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return label_mapping.get(name, name)
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return label_mapping.get(name, telemetryName)
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def formatChartName(telemetryName):
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return " ".join([x.upper() for x in telemetryName.split("_")])
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def process_dataframe(telemetry, keys, time, special_handling=None, latest_only=False):
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def process_dataframe(telemetry, keys, time, special_handling=None, latest_only=False, all_keys=False):
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df = pd.DataFrame()
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# If latest_only is True, ensure missing keys are initialized
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if latest_only:
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if all_keys:
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now = dt.timestamp(dt.now())
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for key in keys:
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if key not in telemetry:
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telemetry[key] = [{'ts': dt.timestamp(dt.now()), 'value': '0'}]
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if key in special_handling["string"]:
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telemetry[key] = [{'ts': now, 'value': ''}]
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else:
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telemetry[key] = [{'ts': now, 'value': ''}]
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for datapoint in telemetry.keys():
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if datapoint in keys:
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@@ -192,9 +227,10 @@ def getManualDataFrame(telemetry, keys, time):
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telemetry, keys, time,
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special_handling={
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"datetime": ["manual_next_pigging_scheduled"],
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"string": ["manual_equipment_description", "manual_issues_concerns"]
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"string": ["manual_equipment_description", "manual_issues_concerns", "manual_well", "manual_tfs_lead", "manual_copa_lead", "manual_job_name", "manual_summary", "manual_hse_spills", "manual_quality_issues"]
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},
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latest_only=True
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latest_only=True,
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all_keys = True
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)
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def getSampleDataFrame(telemetry, keys, time):
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@@ -203,11 +239,10 @@ def getSampleDataFrame(telemetry, keys, time):
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special_handling={
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"datetime": ["manual_sample_time"],
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"string": ["manual_sample_datapoint", "manual_sample_lab", "manual_sample_location"]
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}
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},
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all_keys = True
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)
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def get_last_data_row(ws):
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# Start from the bottom row and work up to find the last row with data
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for row in range(ws.max_row, 0, -1):
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@@ -215,6 +250,60 @@ def get_last_data_row(ws):
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return row
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return 0 # If no data is found, return 0
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def transform_sample_telemetry(telemetry):
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transformed_telemetry = {}
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# Define mapping for Lab and Location
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lab_map = {"Thunderbird Lab": "T", "ConocoPhillips Lab": "C"}
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location_map = {"Inlet": "I", "Outlet": "O"}
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# Extract relevant sample keys
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times = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_time", [])}
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labs = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_lab", [])}
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locations = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_location", [])}
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datapoints = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_datapoint", [])}
|
||||
values = {entry["ts"]: entry["value"] for entry in telemetry.get("manual_sample_value", [])}
|
||||
|
||||
# Iterate through available timestamps
|
||||
for ts in values.keys():
|
||||
lab = lab_map.get(labs.get(ts, ""), "Unknown")
|
||||
location = location_map.get(locations.get(ts, ""), "Unknown")
|
||||
datapoint = datapoints.get(ts, "Unknown")
|
||||
|
||||
new_name = f"{lab}-{location}-{datapoint}"
|
||||
|
||||
# Initialize if not exists
|
||||
if new_name not in transformed_telemetry:
|
||||
transformed_telemetry[new_name] = []
|
||||
|
||||
transformed_telemetry[new_name].append({"ts": ts, "value": values[ts]})
|
||||
|
||||
# Include manual_sample_time separately for indexing
|
||||
transformed_telemetry["manual_sample_time"] = [{"ts": ts, "value": times[ts]} for ts in times]
|
||||
if transformed_telemetry["manual_sample_time"]:
|
||||
return transformed_telemetry
|
||||
else:
|
||||
return {}
|
||||
|
||||
def getSampleKeys():
|
||||
# Ensure all possible column combinations exist
|
||||
unique_labs = ['C', 'T']
|
||||
unique_locations = ['I', 'O']
|
||||
unique_datapoints = ['H2S', 'Density', 'ORP', 'O2', 'H2O2', 'pH', 'Turbidity', 'OIW']
|
||||
all_possible_columns = [
|
||||
f"{lab}-{loc}-{dp}" for lab, loc, dp in product(unique_labs, unique_locations, unique_datapoints)
|
||||
]
|
||||
all_possible_columns.append("manual_sample_time")
|
||||
return all_possible_columns
|
||||
|
||||
def getSampleData(telemetry, device, keys):
|
||||
sample_data = {}
|
||||
for key in keys:
|
||||
temp = telemetry[device].get(key,None)
|
||||
if temp:
|
||||
sample_data[key] = temp
|
||||
return sample_data
|
||||
|
||||
def lambda_handler(event, context):
|
||||
url = "https://www.enxlekkocloud.com"
|
||||
|
||||
@@ -239,14 +328,16 @@ def lambda_handler(event, context):
|
||||
)
|
||||
|
||||
reportsheet = writer.book.worksheets[0]
|
||||
keys = ['ait_102a_turbitity','ait_102b_h2s', 'at_109a_turbidity', 'at_109b_h2s', 'at_109c_oil_in_water', 'at_109e_orp', 'fit_100_flow_rate', 'fit_109b_flow_rate', 'lit_116b_level', 'lit_116a_level', 'outlet_turbidity_temp', 'outlet_orp_temp', 'inlet_turbidity_temp', 'inlet_ph_temp', 'ait_102d_oil_in_water','outlet_ph']
|
||||
manual_keys = ['manual_bag_filter_changes', 'manual_cartridge_filter_changes', 'manual_clean_water_sold_per_job', 'manual_coagulant_on_hand', 'manual_diverted_water_time', 'manual_equipment_description', 'manual_equipment_time', 'manual_h202_on_hand', 'manual_issues_concerns', 'manual_next_pigging_scheduled', 'manual_skim_oil_discharged_per_job', 'manual_standby_time', 'manual_unit_uptime', 'manual_upright_tank_issues', 'manual_vac_truck_batches', 'manual_water_events', 'manual_water_events_time', 'manual_water_to_tanks_time']
|
||||
keys = ['ait_102a_turbitity','ait_102b_h2s', 'at_109a_turbidity', 'at_109b_h2s', 'at_109c_oil_in_water', 'at_109e_orp', 'fit_100_flow_rate', 'fit_109b_flow_rate', 'lit_116b_level', 'lit_116a_level', 'outlet_turbidity_temp', 'outlet_orp_temp', 'inlet_turbidity_temp', 'inlet_ph_temp', 'ait_102d_oil_in_water','outlet_ph','fit_106b_flow_rate']
|
||||
manual_keys = ['manual_bag_filter_changes', 'manual_cartridge_filter_changes', 'manual_clean_water_sold_per_job', 'manual_coagulant_on_hand', 'manual_diverted_water_time', 'manual_equipment_description', 'manual_equipment_time', 'manual_h202_on_hand', 'manual_issues_concerns', 'manual_next_pigging_scheduled', 'manual_skim_oil_discharged_per_job', 'manual_standby_time', 'manual_unit_uptime', 'manual_upright_tank_issues', 'manual_vac_truck_batches', 'manual_water_events', 'manual_water_events_time', 'manual_water_to_tanks_time',"manual_well", "manual_tfs_lead", "manual_copa_lead", "manual_job_name", "manual_summary", "manual_hse_spills", "manual_quality_issues"]
|
||||
sample_keys = ['manual_sample_datapoint', 'manual_sample_lab', 'manual_sample_location', 'manual_sample_time', 'manual_sample_value']
|
||||
#Create a Sheet for each Device
|
||||
for device in telemetry.keys():
|
||||
df = getDataFrame(telemetry[device], keys, time)
|
||||
dfm = getManualDataFrame(telemetry[device], manual_keys, time)
|
||||
dfs = getSampleDataFrame(telemetry[device], sample_keys, time)
|
||||
processed_sample_keys = getSampleKeys()
|
||||
sample_data = transform_sample_telemetry(getSampleData(telemetry=telemetry,device=device,keys=sample_keys))
|
||||
dfs = getSampleDataFrame(sample_data, processed_sample_keys, time)
|
||||
# Write the dataframe data to XlsxWriter. Turn off the default header and
|
||||
# index and skip one row to allow us to insert a user defined header.
|
||||
df.to_excel(writer, sheet_name=device, startrow=0, header=True, index=True, float_format="%.2f")
|
||||
|
||||
Reference in New Issue
Block a user