"""Utility functions for connecting to the EnEffCo database and reading data."""
from __future__ import annotations
import asyncio
import concurrent.futures
from collections.abc import Mapping
from datetime import datetime, timedelta, timezone
from logging import getLogger
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import requests
from requests_cache import CachedSession
from eta_utility.connectors.node import NodeEnEffCo
if TYPE_CHECKING:
from collections.abc import Sequence
from typing import Any
from eta_utility.type_hints import Nodes, TimeStep
from .base_classes import SeriesConnection, SubscriptionHandler
log = getLogger(__name__)
[docs]
class EnEffCoConnection(SeriesConnection[NodeEnEffCo], protocol="eneffco"):
"""
EnEffCoConnection is a class to download and upload multiple features from and to the EnEffCo database as
timeseries.
:param url: URL of the server with scheme (https://).
:param usr: Username in EnEffco for login.
:param pwd: Password in EnEffco for login.
:param api_token: Token for API authentication.
:param nodes: Nodes to select in connection.
"""
API_PATH: str = "/API/v1.0"
def __init__(
self, url: str, usr: str | None, pwd: str | None, *, api_token: str, nodes: Nodes[NodeEnEffCo] | None = None
) -> None:
url = url + self.API_PATH
self._api_token: str = api_token
super().__init__(url, usr, pwd, nodes=nodes)
if self.usr is None:
raise ValueError("Username must be provided for the EnEffCo connector.")
if self.pwd is None:
raise ValueError("Password must be provided for the EnEffCo connector.")
self._node_ids: pd.DataFrame | None = None
self._node_ids_raw: pd.DataFrame | None = None
self._sub: asyncio.Task | None = None
self._subscription_nodes: set[NodeEnEffCo] = set()
self._subscription_open: bool = False
self._session: CachedSession = CachedSession(
cache_name="eta_utility/connectors/requests_cache/eneffco_cache",
expire_after=timedelta(minutes=15),
use_cache_dir=True,
)
@classmethod
def _from_node(
cls, node: NodeEnEffCo, usr: str | None = None, pwd: str | None = None, **kwargs: Any
) -> EnEffCoConnection:
"""Initialize the connection object from an EnEffCo protocol node object
:param node: Node to initialize from.
:param usr: Username to use.
:param pwd: Password to use.
:param kwargs: Keyword arguments for API authentication, where "api_token" is required
:return: EnEffCoConnection object.
"""
api_token = kwargs.get("api_token")
if api_token is None:
raise AttributeError("Keyword parameter 'api_token' is missing.")
return super()._from_node(node, usr=usr, pwd=pwd, api_token=api_token)
[docs]
@classmethod
def from_ids(cls, ids: Sequence[str], url: str, usr: str, pwd: str, api_token: str) -> EnEffCoConnection:
"""Initialize the connection object from an EnEffCo protocol through the node IDs
:param ids: Identification of the Node.
:param url: URL for EnEffco connection.
:param usr: Username for EnEffCo login.
:param pwd: Password for EnEffCo login.
:param api_token: Token for API authentication.
:return: EnEffCoConnection object.
"""
nodes = [NodeEnEffCo(name=name, url=url, protocol="eneffco", eneffco_code=name) for name in ids]
return cls(url=url, usr=usr, pwd=pwd, api_token=api_token, nodes=nodes)
[docs]
def read(self, nodes: Nodes[NodeEnEffCo] | None = None) -> pd.DataFrame:
"""Download current value from the EnEffCo Database
:param nodes: List of nodes to read values from.
:return: pandas.DataFrame containing the data read from the connection.
"""
nodes = self._validate_nodes(nodes)
base_time = 1 # seconds
the_time = self._round_timestamp(datetime.now(), base_time).replace(tzinfo=None)
return self.read_series(the_time - timedelta(seconds=base_time), the_time, nodes, base_time)
[docs]
def write(
self, values: Mapping[NodeEnEffCo, Any] | pd.Series[datetime, Any], time_interval: timedelta | None = None
) -> None:
"""Writes some values to the EnEffCo Database
:param values: Dictionary of nodes and data to write {node: value}.
:param time_interval: Interval between datapoints (i.e. between "From" and "To" in EnEffCo Upload) (default 1s).
"""
nodes = self._validate_nodes(list(values.keys()))
if time_interval is None:
time_interval = timedelta(seconds=1)
for node in nodes:
request_url = f"rawdatapoint/{self.id_from_code(node.eneffco_code, raw_datapoint=True)}/value"
response = self._raw_request(
"POST",
request_url,
data=self._prepare_raw_data(values[node], time_interval),
headers={
"Content-Type": "application/json",
"cache-control": "no-cache",
"Postman-Token": self._api_token,
},
params={"comment": ""},
)
log.info(response.text)
def _prepare_raw_data(
self, data: Mapping[datetime, Any] | pd.Series[datetime, Any], time_interval: timedelta
) -> str:
"""Change the input format into a compatible format with EnEffCo and filter NaN values.
:param data: Data to write to node {time: value}. Could be a dictionary or a pandas Series.
:param time_interval: Interval between datapoints (i.e. between "From" and "To" in EnEffCo Upload).
:return upload_data: String from dictionary in the format for the upload to EnEffCo.
"""
if isinstance(data, (dict, pd.Series)):
upload_data: dict[str, list[Any]] = {"Values": []}
for time, val in data.items():
# Only write values if they are not nan
if not np.isnan(val):
aware_time = self._assert_tz_awareness(time).astimezone(timezone.utc)
upload_data["Values"].append(
{
"Value": float(val),
"From": aware_time.strftime("%Y-%m-%d %H:%M:%SZ"),
"To": (aware_time + time_interval).strftime("%Y-%m-%d %H:%M:%SZ"),
}
)
else:
raise ValueError("Unrecognized data format for EnEffCo upload. Provide dictionary or pandas series.")
return str(upload_data)
[docs]
def read_info(self, nodes: Nodes[NodeEnEffCo] | None = None) -> pd.DataFrame:
"""Read additional datapoint information from Database.
:param nodes: List of nodes to read values from.
:return: pandas.DataFrame containing the data read from the connection.
"""
nodes = self._validate_nodes(nodes)
values = []
for node in nodes:
request_url = f"datapoint/{self.id_from_code(node.eneffco_code)}"
response = self._raw_request("GET", request_url)
values.append(pd.Series(response.json(), name=node.name))
return pd.concat(values, axis=1)
[docs]
def subscribe(
self, handler: SubscriptionHandler, nodes: Nodes[NodeEnEffCo] | None = None, interval: TimeStep = 1
) -> None:
"""Subscribe to nodes and call handler when new data is available. This will return only the
last available values.
:param handler: SubscriptionHandler object with a push method that accepts node, value pairs.
:param interval: Interval for receiving new data. It is interpreted as seconds when given as an integer.
:param nodes: Identifiers for the nodes to subscribe to.
"""
self.subscribe_series(handler=handler, req_interval=1, nodes=nodes, interval=interval, data_interval=interval)
[docs]
def read_series(
self,
from_time: datetime,
to_time: datetime,
nodes: Nodes[NodeEnEffCo] | None = None,
interval: TimeStep = 1,
**kwargs: Any,
) -> pd.DataFrame:
"""Download timeseries data from the EnEffCo Database
:param nodes: List of nodes to read values from.
:param from_time: Starting time to begin reading (included in output).
:param to_time: Time to stop reading at (not included in output).
:param interval: Interval between time steps. It is interpreted as seconds if given as integer.
:param kwargs: Other parameters (ignored by this connector).
:return: Pandas DataFrame containing the data read from the connection.
"""
_interval = interval if isinstance(interval, timedelta) else timedelta(seconds=interval)
nodes = self._validate_nodes(nodes)
def read_node(node: NodeEnEffCo) -> pd.DataFrame:
request_url = (
f"datapoint/{self.id_from_code(node.eneffco_code)}/value?"
f"from={self.timestr_from_datetime(from_time)}&"
f"to={self.timestr_from_datetime(to_time)}&"
f"timeInterval={int(_interval.total_seconds())!s}&"
"includeNanValues=True"
)
response = self._raw_request("GET", request_url).json()
data = pd.DataFrame(
data=(r["Value"] for r in response),
index=pd.to_datetime([r["From"] for r in response], utc=True, format="%Y-%m-%dT%H:%M:%SZ").tz_convert(
self._local_tz
),
columns=[node.name],
dtype="float64",
)
data.index.name = "Time (with timezone)"
return data
with concurrent.futures.ThreadPoolExecutor() as executor:
results = executor.map(read_node, nodes)
return pd.concat(results, axis=1, sort=False)
[docs]
def subscribe_series(
self,
handler: SubscriptionHandler,
req_interval: TimeStep,
offset: TimeStep | None = None,
nodes: Nodes[NodeEnEffCo] | None = None,
interval: TimeStep = 1,
data_interval: TimeStep = 1,
**kwargs: Any,
) -> None:
"""Subscribe to nodes and call handler when new data is available. This will always return a series of values.
If nodes with different intervals should be subscribed, multiple connection objects are needed.
:param handler: SubscriptionHandler object with a push method that accepts node, value pairs.
:param req_interval: Duration covered by requested data (time interval). Interpreted as seconds if given as int.
:param offset: Offset from datetime.now from which to start requesting data (time interval).
Interpreted as seconds if given as int. Use negative values to go to past timestamps.
:param data_interval: Time interval between values in returned data. Interpreted as seconds if given as int.
:param interval: interval (between requests) for receiving new data.
It is interpreted as seconds when given as an integer.
:param nodes: Identifiers for the nodes to subscribe to.
:param kwargs: Other, ignored parameters.
"""
nodes = self._validate_nodes(nodes)
interval = interval if isinstance(interval, timedelta) else timedelta(seconds=interval)
req_interval = req_interval if isinstance(req_interval, timedelta) else timedelta(seconds=req_interval)
if offset is None:
offset = -req_interval
else:
offset = offset if isinstance(offset, timedelta) else timedelta(seconds=offset)
data_interval = data_interval if isinstance(data_interval, timedelta) else timedelta(seconds=data_interval)
self._subscription_nodes.update(nodes)
if self._subscription_open:
# Adding nodes to subscription is enough to include them in the query. Do not start an additional loop
# if one already exists
return
self._subscription_open = True
loop = asyncio.get_event_loop()
self._sub = loop.create_task(
self._subscription_loop(
handler,
int(interval.total_seconds()),
req_interval,
offset,
data_interval,
)
)
[docs]
def close_sub(self) -> None:
"""Close an open subscription."""
self._subscription_open = False
if self.exc:
raise self.exc
try:
self._sub.cancel() # type: ignore
except Exception:
pass
async def _subscription_loop(
self,
handler: SubscriptionHandler,
interval: TimeStep,
req_interval: TimeStep,
offset: TimeStep,
data_interval: TimeStep,
) -> None:
"""The subscription loop handles requesting data from the server in the specified interval
:param handler: Handler object with a push function to receive data.
:param interval: Interval for requesting data in seconds.
:param req_interval: Duration covered by the requested data.
:param offset: Offset from datetime.now from which to start requesting data (time interval).
Use negative values to go to past timestamps.
:param data_interval: Interval between data points.
"""
interval = interval if isinstance(interval, timedelta) else timedelta(seconds=interval)
req_interval = req_interval if isinstance(req_interval, timedelta) else timedelta(seconds=req_interval)
data_interval = data_interval if isinstance(data_interval, timedelta) else timedelta(seconds=data_interval)
offset = offset if isinstance(offset, timedelta) else timedelta(seconds=offset)
try:
while self._subscription_open:
from_time = datetime.now() + offset
to_time = from_time + req_interval
values = self.read_series(from_time, to_time, self._subscription_nodes, interval=data_interval)
for node in self._subscription_nodes:
handler.push(node, values[node.name])
await asyncio.sleep(interval.total_seconds())
except BaseException as e:
self.exc = e
[docs]
def id_from_code(self, code: str, raw_datapoint: bool = False) -> str:
"""
Function to get the raw EnEffCo ID corresponding to a specific (raw) datapoint
:param code: Exact EnEffCo code.
:param raw_datapoint: Returns raw datapoint ID.
"""
# Only build lists of IDs if they are not available yet
if self._node_ids is None:
response = self._raw_request("GET", "/datapoint")
self._node_ids = pd.DataFrame(data=response.json())
if self._node_ids_raw is None:
response = self._raw_request("GET", "/rawdatapoint")
self._node_ids_raw = pd.DataFrame(data=response.json())
def find_id(node_ids: pd.DataFrame) -> str:
if len(node_ids.loc[node_ids["Code"] == code, "Id"]) <= 0:
raise ValueError(f"Code {code} does not exist on server {self.url}.")
return node_ids.loc[node_ids["Code"] == code, "Id"].to_numpy().item()
return find_id(self._node_ids_raw) if raw_datapoint else find_id(self._node_ids)
[docs]
def timestr_from_datetime(self, dt: datetime) -> str:
"""Create an EnEffCo compatible time string.
:param dt: Datetime object to convert to string.
:return: EnEffCo compatible time string.
"""
return dt.isoformat(sep="T", timespec="seconds").replace(":", "%3A").replace("+", "%2B")
def _raw_request(self, method: str, endpoint: str, **kwargs: Any) -> requests.Response:
"""Perform EnEffCo request and handle possibly resulting errors.
:param method: HTTP request method.
:param endpoint: Endpoint for the request (server URI is added automatically).
:param kwargs: Additional arguments for the request.
"""
assert self.usr is not None, "Make sure to specify a username before performing EnEffCo requests."
assert self.pwd is not None, "Make sure to specify a password before performing EnEffCo requests."
response = self._session.request(
method, self.url + "/" + str(endpoint), auth=requests.auth.HTTPBasicAuth(self.usr, self.pwd), **kwargs
)
response.raise_for_status()
return response
def _validate_nodes(self, nodes: Nodes[NodeEnEffCo] | None) -> set[NodeEnEffCo]: # type: ignore
vnodes = super()._validate_nodes(nodes)
_nodes = set()
for node in vnodes:
if isinstance(node, NodeEnEffCo):
_nodes.add(node)
return _nodes