226 lines
11 KiB
Python
226 lines
11 KiB
Python
# -*- coding: utf-8 -*-
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from __future__ import unicode_literals
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import os
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import re
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import traceback
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from datetime import datetime
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import pytz
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from django.conf import settings
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from django.db import models
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from influxdb_client import InfluxDBClient, Point, WritePrecision
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from influxdb_client.client.write_api import SYNCHRONOUS
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from pyscada.models import DataSource
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tz_local = pytz.timezone(settings.TIME_ZONE)
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class InfluxDatabase(DjangoDatabase):
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bucket = models.CharField(max_length=255)
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api_key = models.CharField(max_length=255)
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organisation = models.CharField(max_length=255)
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write_precision = models.CharField(default="ms", max_length=2)
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url = models.CharField(default="127.0.0.1:8086")
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measurement_name = models.CharField(default="pyscada.models.RecordedData", max_length=255)
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only_write_to_influxdb = models.BooleanField(default=True, help_text="when selected only a copy of the data is written to the InfluxDB and the SQL Database is used for everything else")
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def connect(self):
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self.client = InfluxDBClient(url=self.url, token=self.token, org=self.organisation)
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return self.client
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def get_write_api(self):
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if self.client is None:
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self.connect()
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return self.client.write_api(write_options=SYNCHRONOUS)
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def get_query_api(self):
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if self.client is None:
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self.connect()
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return self.client.query_api()
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def create_data_element_from_variable(self, variable, value, timestamp, **kwargs):
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if value is not None:
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date_saved = (
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kwargs["date_saved"]
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if "date_saved" in kwargs
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else variable.date_saved
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if hasattr(variable, "date_saved")
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else now()
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)
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return Point(self.measurement_name)
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#.field("id", int(int(int(timestamp) * 2097152) + variable.pk))
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.tag("variable_id", variable.pk) # has to be a tag to be easily filtered by, even if it is an numeric value
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.tag("device_protocol", variable.device.protocol.protocol)
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.tag"device_id", variable.device_id) # has to be a tag to be easily filtered by, even if it is an numeric value
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.tag("value_class", variable.value_class)
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.tag("unit", str(variable.unit))
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.field("value", value)
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.field("date_saved", date_saved)
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.timestamp(timestamp / 1000)
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return None
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def last_value(self, **kwargs):
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if self.only_write_to_influxdb:
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return super(self).last_value(**kwargs)
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variable = kwargs.pop("variable") if "variable" in kwargs else None
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use_date_saved = (
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kwargs.pop("use_date_saved") if "use_date_saved" in kwargs else False
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)
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query = f'from(bucket: "{self.bucket}") |> range(start: {time_min}) |> filter(fn:(r) => r._measurement == "{self.measurement_name}" ) |> filter(fn:(r) => r.variable_id == "{variable_id}") |> filter(fn:(r) => r._field == "value") |> keep(columns: ["_time","_value"]) |> last()'
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r = query_api.query(query)
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r = r.to_values(columns=['_time','_value'])[0]
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if len(r) == 0:
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return None
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return [r[-1][0].timestamp(), r[-1][1]]
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def read_multiple(self, **kwargs):
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if self.only_write_to_influxdb:
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return super(self).read_multiple(**kwargs)
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variable_ids = kwargs.pop("variable_ids") if "variable_ids" in kwargs else []
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time_min = kwargs.pop("time_min") if "time_min" in kwargs else 0
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time_max = kwargs.pop("time_max") if "time_max" in kwargs else time.time()
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time_in_ms = kwargs.pop("time_in_ms") if "time_in_ms" in kwargs else True
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query_first_value = (
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kwargs.pop("query_first_value") if "query_first_value" in kwargs else False
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)
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variable_ids = self.datasource.datasource_check(
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variable_ids, items_as_id=True, ids_model=Variable
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)
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if kwargs.get("time_min_excluded", False):
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time_min = time_min + 0.001
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if kwargs.get("time_max_excluded", False):
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time_max = time_max - 0.001
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if time_in_ms:
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f_time_scale = 1000
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else:
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f_time_scale = 1
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values = {}
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query_api = self.get_query_api()
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tmp_time_max = time_min
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date_saved_max = time_min
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for variable_id in variable_ids:
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query = f'from(bucket: "{self.bucket}") |> range(start: {time_min}, stop: {time_max}) |> filter(fn:(r) => r._measurement == "{self.measurement_name}" ) |> filter(fn:(r) => r.variable_id == "{variable_id}") |> filter(fn:(r) => r._field == "value") |> keep(columns: ["_time","_value"])'
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r = query_api.query(query)
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values[variable_id] = [ [i_time.timestamp(), i_value] for i_time, i_value in r.to_values(["_time","_value"])]
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tmp_time_max = max(tmp_time_max, max([i_time for i_time, i_value in values[variable_id]])
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query = f'from(bucket: "{self.bucket}") |> range(start: {time_min}, stop: {time_max}) |> filter(fn:(r) => r._measurement == "{self.measurement_name}" ) |> filter(fn:(r) => r.variable_id == "{variable_id}") |> filter(fn:(r) => r._field == "date_saved") |> max()'
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r = query_api.query(query)
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date_saved_max = max(date_saved_max, r.to_values(["_value"])[0][0])
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values["timestamp"] = tmp_time_max * f_time_scale
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values["date_saved_max"] = date_saved_max * f_time_scale
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return values
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def write_multiple(self, **kwargs):
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if self.only_write_to_influxdb:
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data_model = self._import_model()
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items = kwargs.pop("items") if "items" in kwargs else []
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items = self.datasource.datasource_check(items) # FIXME what is happening here?
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points = []
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recordings = []
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date_saved = kwargs.pop("date_saved") if "date_saved" in kwargs else now()
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write_api = self.get_write_api()
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batch_size = kwargs.pop("batch_size") if "batch_size" in kwargs else 5000
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i = 0
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for item in items:
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logger.debug(f"{item} has {len(item.cached_values_to_write)} to write.")
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if len(item.cached_values_to_write):
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for cached_value in item.cached_values_to_write:
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# add date saved if not exist in variable object, if date_saved is in kwargs it will be used instead of the variable.date_saved (see the create_data_element_from_variable function)
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if not hasattr(item, "date_saved") or item.date_saved is None:
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item.date_saved = date_saved
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# create the recorded data object
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point = self.create_data_element_from_variable(
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item, cached_value[1], cached_value[0], **kwargs
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)
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if self.only_write_to_influxdb:
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rc = data_model.objects.create_data_element_from_variable(
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item, cached_value[1], cached_value[0], **kwargs
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)
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if rc is not None:
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recordings.append(rc)
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# append the object to the elements to save
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if point is not None:
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points.append(point)
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i += 1
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if i%batch_size == 0:
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write_api.write(bucket=bucket, org="tub", record=points, write_precision=self.write_precision)
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points = []
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if self.only_write_to_influxdb:
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try:
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data_model.objects.bulk_create(recorded_datas, batch_size=batch_size, **kwargs)
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except IntegrityError:
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logger.debug(
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f'{data_model._meta.object_name} objects already exists, retrying ignoring conflicts for : {", ".join(str(i.id) + " " + str(i.variable.id) for i in recorded_datas)}'
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)
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data_model.objects.bulk_create(
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recorded_datas, ignore_conflicts=True, batch_size=batch_size, **kwargs
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)
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if len(points) > 0:
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write_api.write(bucket=bucket, org="tub", record=points, write_precision=self.write_precision)
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for item in items:
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item.date_saved = None
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def get_first_element_timestamp(self, **kwargs):
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"""this will likly time out and should be considert non functioning!
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"""
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if self.only_write_to_influxdb:
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return super(self).get_first_element_timestamp(**kwargs)
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return self.get_edge_element_timestamp(first_last="first", **kwargs)
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def get_last_element_timestamp(self, **kwargs):
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if self.only_write_to_influxdb:
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return super(self).get_last_element_timestamp(**kwargs)
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return self.get_edge_element_timestamp(first_last="last", **kwargs)
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def get_edge_element_timestamp(self, first_last="last", **kwargs):
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if "variables" in kwargs:
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variable_ids = [ v.pk for v in kwargs["variables"]]
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elif "variable" in kwargs:
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variable_ids = [ kwargs["variable"].pk ]
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elif "variable_ids" in kwargs:
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variable_ids = kwargs["variable_ids"]
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elif "variable_id" in kwargs:
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variable_ids = [ kwargs["variable_id"]]
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else:
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return None
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query_api = self.get_query_api()
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start_time = "-24h"
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query = f'from(bucket: "{self.bucket}") |> range(start: {start_time}) |> filter(fn:(r) => r._measurement == "{self.measurement_name}" ) |> filter(fn:(r) =>'
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for variable_id in variable_ids:
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query += ' r.variable_id == "{variable_id}" or '
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query = query[:-3]
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if first_last == "last":
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query += ') |> keep(columns: ["_time"]) |> sort(columns: ["_time"], desc: false) |> last(column: "_time")'
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elif first_last == "first":
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query += ') |> keep(columns: ["_time"]) |> sort(columns: ["_time"], desc: false) |> first(column: "_time")'
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else:
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return None
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r = query_api.query(query)
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r = r.to_values(columns=['_time'])[0]
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if len(r) == 0:
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return None
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if first_last == "last":
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return r[-1].timestamp()
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elif first_last == "first":
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return r[0].timestamp() |