def reset_depth_series(name, **kwargs):
"""Delete all datapoints for a depthseries.
Args:
name (str): Name of depthseries to delete.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5
) + "/projects/{}/timeseries/{}?timestampInclusiveBegin=0?timestampInclusiveEnd={}".format(
project, quote_plus(name), sys.maxsize)
headers = {"api-key": api_key, "accept": "application/json"}
res = _utils.delete_request(url, headers=headers)
if res == {}:
url = config.get_base_url(
api_version=0.5
) + "/projects/{}/timeseries/{}?timestampInclusiveBegin=0?timestampInclusiveEnd={}".format(
project, quote_plus(_generateIndexName(name)), sys.maxsize)
res = _utils.delete_request(url, headers=headers)
return res.json()
def delete_assets(asset_ids: List[int], **kwargs):
"""Delete a list of assets.
Args:
asset_ids (list[int]): List of IDs of assets to delete.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/assets/delete".format(project)
body = {"items": asset_ids}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
res = utils.post_request(url,
body=body,
headers=headers,
cookies=config.get_cookies())
return res.json()
def update_time_series(time_series: List[TimeSeries], **kwargs):
"""Update an existing time series.
For each field that can be updated, a null value indicates that nothing should be done.
Args:
time_series (list[v05.dto.TimeSeries]): List of time series data transfer objects to update.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries".format(project)
body = {"items": [ts.__dict__ for ts in time_series]}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
res = _utils.put_request(url, body=body, headers=headers)
return res.json()
def download_file(id, get_contents=False, **kwargs):
"""Get list of files matching query.
Args:
id (int): Path to file to upload, if omitted a upload link will be returned.
get_contents (bool, optional): Boolean to determince whether or not to return file contents as string.
Default is False and download url is returned.
Keyword Args:
api_key (str, optional): Your api-key.
project (str, optional): Project name.
Returns:
str: Download link if get_contents is False else file contents.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/storage/{}".format(project, id)
headers = {"api-key": api_key, "accept": "application/json"}
res = _utils.get_request(url=url,
headers=headers,
cookies=config.get_cookies())
if get_contents:
dl_link = res.json()["data"]
res = requests.get(dl_link)
return res.content
return res.json()["data"]
def delete_files(file_ids, **kwargs):
"""Delete
Args:
file_ids (list[int]): List of IDs of files to delete.
Keyword Args:
api_key (str): Your api key.
project (str): Your project.
Returns:
list: List of files deleted and files that failed to delete.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/storage/delete".format(project)
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
body = {"items": file_ids}
res = _utils.post_request(url, body=body, headers=headers)
return res.json()["data"]
def get_row(database_name: str = None, table_name: str = None, row_key: str = None, api_key=None, project=None):
"""Returns a RawResponse Object containing a list of rows.
Args:
database_name (str): The database name to retrieve rows from.
table_name (str): The table name to retrieve rows from.
row_key (str): The key of the row to fetch.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v04.dto.RawResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(api_version=0.4) + "/projects/{}/raw/{}/{}/{}".format(
project, database_name, table_name, row_key
)
params = dict()
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
res = _utils.get_request(url=url, params=params, headers=headers, cookies=config.get_cookies())
return RawResponse(res.json())
def tag_matching(tag_ids, fuzzy_threshold=0, platform=None, **kwargs):
"""Returns a TagMatchingObject containing a list of matched tags for the given query.
This method takes an arbitrary string as argument and performs fuzzy matching with a user defined threshold
toward tag ids in the system.
Args:
tag_ids (list): The tag_ids to retrieve matches for.
fuzzy_threshold (int): The threshold to use when searching for matches. A fuzzy threshold of 0 means you only
want to accept perfect matches. Must be >= 0.
platform (str): The platform to search on.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v04.dto.TagMatchingResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"), kwargs.get("project"))
url = config.get_base_url(api_version=0.4) + "/projects/{}/tagmatching".format(project)
body = {"tagIds": tag_ids, "metadata": {"fuzzyThreshold": fuzzy_threshold, "platform": platform}}
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
res = _utils.post_request(url=url, body=body, headers=headers, cookies=config.get_cookies())
return TagMatchingResponse(res.json())
def post_assets(assets: List[Asset], **kwargs):
"""Insert a list of assets.
Args:
assets (list[v05.dto.Asset]): List of asset data transfer objects.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.AssetListResponse: A data object containing the posted assets with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/assets".format(project)
body = {"items": [asset.__dict__ for asset in assets]}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
res = utils.post_request(url,
body=body,
headers=headers,
cookies=config.get_cookies())
return AssetListResponse(res.json())
def get_latest(name, **kwargs):
"""Returns a LatestDatapointObject containing the latest datapoint for the given timeseries.
Args:
name (str): The name of the timeseries to retrieve data for.
Keyword Arguments:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.LatestDatapointsResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries/latest/{}".format(
project, quote(name, safe=""))
headers = {"api-key": api_key, "accept": "application/json"}
res = _utils.get_request(url,
headers=headers,
cookies=config.get_cookies())
return LatestDatapointResponse(res.json())
def get_tables(database_name: str = None, limit: int = None, cursor: str = None, api_key=None, project=None):
"""Returns a RawObject containing a list of tables in a raw database.
Args:
database_name (str): The database name to retrieve tables from.
limit (int): A limit on the amount of results to return.
cursor (str): A cursor can be provided to navigate through pages of results.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v04.dto.RawResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(api_version=0.4) + "/projects/{}/raw/{}".format(project, database_name)
params = dict()
if not limit:
params["limit"] = limit
if not cursor:
params["cursor"] = cursor
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
res = _utils.get_request(url=url, params=params, headers=headers, cookies=config.get_cookies())
return RawResponse(res.json())
def get_asset_subtree(asset_id="", depth=None, **kwargs):
"""Returns assets with provided assetId.
Args:
asset_id (str): The asset id of the top asset to get.
depth (int): Get subassets this many levels below the top asset.
Keyword Arguments:
limit (int): The maximum nuber of assets to be returned.
cursor (str): Cursor to use for paging through results.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v04.dto.AssetResponse: A data object containing the requested assets with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/assets/{}".format(project, asset_id)
params = {
"depth": depth,
"limit": kwargs.get("limit", constants.LIMIT),
"cursor": kwargs.get("cursor")
}
headers = {"api-key": api_key, "accept": "application/json"}
res = utils.get_request(url,
params=params,
headers=headers,
cookies=config.get_cookies())
return AssetResponse(res.json())
def create_databases(database_names: list, api_key=None, project=None):
"""Creates databases in the Raw API and returns the created databases.
Args:
database_names (list): A list of databases to create.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.RawResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(
api_version=0.5) + "/projects/{}/raw/create".format(project)
body = {
"items": [{
"dbName": "{}".format(database_name)
} for database_name in database_names]
}
headers = {
"api-key": api_key,
"content-type": "*/*",
"accept": "application/json"
}
res = _utils.post_request(url=url,
body=body,
headers=headers,
cookies=config.get_cookies())
return RawResponse(res.json())
def post_time_series(time_series: List[TimeSeries], **kwargs):
"""Create a new time series.
Args:
time_series (list[v05.dto.TimeSeries]): List of time series data transfer objects to create.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries".format(project)
body = {"items": [ts.__dict__ for ts in time_series]}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
res = _utils.post_request(url, body=body, headers=headers)
return res.json()
def delete_rows(
database_name: str = None, table_name: str = None, rows: List[RawRow] = None, api_key=None, project=None
):
"""Deletes rows in the Raw API.
Args:
database_name (str): The database to create tables in.
table_name (str): The table name where the rows are at.
rows (list): The rows to delete.
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(api_version=0.4) + "/projects/{}/raw/{}/{}/delete".format(
project, database_name, table_name
)
body = {"items": [{"key": "{}".format(row.key), "columns": row.columns} for row in rows]}
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
res = _utils.post_request(url=url, body=body, headers=headers, cookies=config.get_cookies())
return res.json()
def post_multi_tag_datapoints(
timeseries_with_datapoints: List[TimeseriesWithDatapoints], **kwargs):
"""Insert data into multiple timeseries.
Args:
timeseries_with_datapoints (List[v05.dto.TimeseriesWithDatapoints]): The timeseries with data to insert.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
use_gzip (bool): Whether or not to gzip the request
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/timeseries/data".format(project)
use_gzip = kwargs.get("use_gzip", False)
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
ul_dps_limit = 100000
# Make sure we only work with TimeseriesWithDatapoints objects that has a max number of datapoints
timeseries_with_datapoints_limited = []
for entry in timeseries_with_datapoints:
timeseries_with_datapoints_limited.extend(
_split_TimeseriesWithDatapoints_if_over_limit(entry, ul_dps_limit))
# Group these TimeseriesWithDatapoints if possible so that we upload as much as possible in each call to the API
timeseries_to_upload_binned = _utils.first_fit(
list_items=timeseries_with_datapoints_limited,
max_size=ul_dps_limit,
get_count=lambda x: len(x.datapoints))
for bin in timeseries_to_upload_binned:
body = {
"items": [{
"tagId":
ts_with_data.name,
"datapoints": [dp.__dict__ for dp in ts_with_data.datapoints]
} for ts_with_data in bin]
}
res = _utils.post_request(url,
body=body,
headers=headers,
use_gzip=use_gzip)
return res.json()
def post_datapoints(name, depthdatapoints: List[DatapointDepth], **kwargs):
"""Insert a list of datapoints.
Args:
name (str): Name of timeseries to insert to.
datapoints (list[v05.data_objects.Datapoint): List of datapoint data transfer objects to insert.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
offset = 0 # Random timestamp to start the time series
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries/data".format(project)
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
datapoints = []
depthpoints = []
for datapoint in depthdatapoints:
datapoints.append(Datapoint(offset, datapoint.value))
depthpoints.append(Datapoint(offset, datapoint.depth))
offset += MS_INCREMENT
ul_dps_limit = 100000
i = 0
while i < len(datapoints):
body = {
"items": [
{
"name":
name,
"datapoints":
[dp.__dict__ for dp in datapoints[i:i + ul_dps_limit]]
},
{
"name":
_generateIndexName(name),
"datapoints":
[dp.__dict__ for dp in depthpoints[i:i + ul_dps_limit]],
},
]
}
_utils.post_request(url, body=body, headers=headers)
i += ul_dps_limit
return {}
def get_assets(name=None,
path=None,
description=None,
metadata=None,
depth=None,
fuzziness=None,
**kwargs):
"""Returns assets matching provided description.
Args:
name (str): The name of the asset(s) to get.
path (str): The path of the subtree to search in.
description (str): Search query.
metadata (dict): The metadata values used to filter the results.
depth (int): Get sub assets up oto this many levels below the specified path.
fuzziness (int): The degree of fuzziness in the name matching.
Keyword Arguments:
limit (int): The maximum number of assets to be returned.
cursor (str): Cursor to use for paging through results.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.AssetListResponse: A data object containing the requested assets with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/assets".format(project)
params = {
"name": name,
"description": description,
"path": path,
"metadata": str(metadata) if metadata else None,
"depth": depth,
"fuzziness": fuzziness,
"cursor": kwargs.get("cursor"),
"limit": kwargs.get("limit", constants.LIMIT),
}
headers = {"api-key": api_key, "accept": "application/json"}
res = utils.get_request(url,
params=params,
headers=headers,
cookies=config.get_cookies())
return AssetListResponse(res.json())
def create_rows(
database_name: str = None,
table_name: str = None,
rows: List[RawRow] = None,
api_key=None,
project=None,
ensure_parent=False,
use_gzip=False,
):
"""Creates tables in the given Raw API database.
Args:
database_name (str): The database to create rows in.
table_name (str): The table names to create rows in.
rows (list[v04.dto.RawRow]): The rows to create.
api_key (str): Your api-key.
project (str): Project name.
ensure_parent (bool): Create database/table if it doesn't exist already
use_gzip (bool): Compress content using gzip
Returns:
An empty response
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(api_version=0.4) + "/projects/{}/raw/{}/{}/create".format(
project, database_name, table_name
)
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
if ensure_parent:
params = {"ensureParent": "true"}
else:
params = {}
ul_row_limit = 1000
i = 0
while i < len(rows):
body = {"items": [{"key": "{}".format(row.key), "columns": row.columns} for row in rows[i : i + ul_row_limit]]}
res = _utils.post_request(
url=url, body=body, headers=headers, params=params, cookies=config.get_cookies(), use_gzip=use_gzip
)
i += ul_row_limit
return res.json()
def get_event(event_id, **kwargs):
"""Returns a EventResponse containing an event matching the id.
Args:
event_id (int): The event id.
Keyword Arguments:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.EventResponse: A data object containing the requested event.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"), kwargs.get("project"))
url = config.get_base_url(api_version=0.5) + "/projects/{}/events/{}".format(project, event_id)
headers = {"api-key": api_key, "content-type": "application/json", "accept": "application/json"}
res = _utils.get_request(url, headers=headers, cookies=config.get_cookies())
return EventResponse(res.json())
def update_depth_series(depth_series: List[TimeSeries], **kwargs):
"""Update an existing time series.
For each field that can be updated, a null value indicates that nothing should be done.
Args:
depth_series (list[v05.dto.TimeSeries]): List of time series data transfer objects to update.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries".format(project)
body = {"items": [ts.__dict__ for ts in depth_series]}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
res = _utils.put_request(url, body=body, headers=headers)
if res.json() == {}:
for dsdto in depth_series:
dsdto.name = _generateIndexName(dsdto.name)
dsdto.isString = None
dsdto.unit = None
items = [
ts.__dict__ for ts in depth_series if _has_depth_index_changes(ts)
]
body = {"items": items}
if len(items) > 0:
res = _utils.put_request(url, body=body, headers=headers)
return res.json()
def delete_databases(database_names: list, recursive: bool = False, api_key=None, project=None):
"""Deletes databases in the Raw API.
Args:
database_names (list): A list of databases to delete.
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(api_version=0.4) + "/projects/{}/raw/delete".format(project)
body = {"items": [{"dbName": "{}".format(database_name)} for database_name in database_names]}
params = {"recursive": recursive}
headers = {"api-key": api_key, "content-type": "*/*", "accept": "application/json"}
res = _utils.post_request(url=url, body=body, params=params, headers=headers, cookies=config.get_cookies())
return res.json()
def get_file_info(id, **kwargs):
"""Returns information about a file.
Args:
id (int): Id of the file.
Keyword Args:
api_key (str, optional): Your api-key.
project (str, optional): Project name.
Returns:
v04.dto.FileInfoResponse: A data object containing the requested file information.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/storage/{}/info".format(project, id)
headers = {"api-key": api_key, "accept": "application/json"}
res = _utils.get_request(url, headers=headers)
return FileInfoResponse(res.json())
def post_events(events, **kwargs):
"""Adds a list of events and returns an EventListResponse object containing created events.
Args:
events (List[v05.dto.Event]): List of events to create.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.EventListResponse
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"), kwargs.get("project"))
url = config.get_base_url(api_version=0.5) + "/projects/{}/events".format(project)
headers = {"api-key": api_key, "content-type": "application/json", "accept": "application/json"}
body = {"items": [event.__dict__ for event in events]}
res = _utils.post_request(url, body=body, headers=headers)
return EventListResponse(res.json())
def get_asset(asset_id, **kwargs):
"""Returns the asset with the provided assetId.
Args:
asset_id (int): The asset id of the top asset to get.
Keyword Arguments:
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.AssetResponse: A data object containing the requested assets with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/assets/{}/subtree".format(
project, asset_id)
headers = {"api-key": api_key, "accept": "application/json"}
res = utils.get_request(url, headers=headers, cookies=config.get_cookies())
return AssetResponse(res.json())
def delete_tables(database_name: str = None,
table_names: list = None,
api_key=None,
project=None):
"""Deletes databases in the Raw API.
Args:
database_name (str): The database to create tables in.
table_names (list): The table names to create.
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(
api_version=0.5) + "/projects/{}/raw/{}/delete".format(
project, database_name)
body = {
"items": [{
"tableName": "{}".format(table_name)
} for table_name in table_names]
}
headers = {
"api-key": api_key,
"content-type": "*/*",
"accept": "application/json"
}
res = _utils.post_request(url=url,
body=body,
headers=headers,
cookies=config.get_cookies())
return res.json()
def post_datapoints(tag_id, datapoints: List[Datapoint], **kwargs):
"""Insert a list of datapoints.
Args:
tag_id (str): ID of timeseries to insert to.
datapoints (list[v04.dto.Datapoint): List of datapoint data transfer objects to insert.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.4) + "/projects/{}/timeseries/data/{}".format(
project, quote(tag_id, safe=""))
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "application/json"
}
ul_dps_limit = 100000
i = 0
while i < len(datapoints):
body = {
"items": [dp.__dict__ for dp in datapoints[i:i + ul_dps_limit]]
}
res = _utils.post_request(url, body=body, headers=headers)
i += ul_dps_limit
return res.json()
def get_databases(limit: int = None,
cursor: str = None,
api_key=None,
project=None):
"""Returns a RawObject containing a list of raw databases.
Args:
limit (int): A limit on the amount of results to return.
cursor (str): A cursor can be provided to navigate through pages of results.
api_key (str): Your api-key.
project (str): Project name.
Returns:
v05.dto.RawResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(api_key, project)
url = config.get_base_url(
api_version=0.5) + "/projects/{}/raw".format(project)
params = {"limit": limit, "cursor": cursor}
headers = {
"api-key": api_key,
"content-type": "*/*",
"accept": "application/json"
}
res = _utils.get_request(url=url,
params=params,
headers=headers,
cookies=config.get_cookies())
return RawResponse(res.json())
def delete_time_series(name, **kwargs):
"""Delete a timeseries.
Args:
name (str): Name of timeseries to delete.
Keyword Args:
api_key (str): Your api-key.
project (str): Project name.
Returns:
An empty response.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries/{}".format(
project, quote(name, safe=""))
headers = {"api-key": api_key, "accept": "application/json"}
res = _utils.delete_request(url, headers=headers)
return res.json()
def get_timeseries(prefix=None,
description=None,
include_metadata=False,
asset_id=None,
path=None,
**kwargs):
"""Returns a TimeseriesObject containing the requested timeseries.
Args:
prefix (str): List timeseries with this prefix in the name.
description (str): Filter timeseries taht contains this string in its description.
include_metadata (bool): Decide if the metadata field should be returned or not. Defaults to False.
asset_id (int): Get timeseries related to this asset.
path (str): Get timeseries under this asset path branch.
Keyword Arguments:
limit (int): Number of results to return.
api_key (str): Your api-key.
project (str): Project name.
autopaging (bool): Whether or not to automatically page through results. If set to true, limit will be
disregarded. Defaults to False.
Returns:
v05.dto.TimeSeriesResponse: A data object containing the requested timeseries with several getter methods with different
output formats.
"""
api_key, project = config.get_config_variables(kwargs.get("api_key"),
kwargs.get("project"))
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries".format(project)
headers = {"api-key": api_key, "accept": "application/json"}
params = {
"q":
prefix,
"description":
description,
"includeMetadata":
include_metadata,
"assetId":
asset_id,
"path":
path,
"limit":
kwargs.get("limit", 10000) if not kwargs.get("autopaging") else 10000,
}
time_series = []
res = _utils.get_request(url=url,
headers=headers,
params=params,
cookies=config.get_cookies())
time_series.extend(res.json()["data"]["items"])
next_cursor = res.json()["data"].get("nextCursor")
while next_cursor and kwargs.get("autopaging"):
params["cursor"] = next_cursor
res = _utils.get_request(url=url,
headers=headers,
params=params,
cookies=config.get_cookies())
time_series.extend(res.json()["data"]["items"])
next_cursor = res.json()["data"].get("nextCursor")
return TimeSeriesResponse({
"data": {
"nextCursor": next_cursor,
"previousCursor": res.json()["data"].get("previousCursor"),
"items": time_series,
}
})
def _get_datapoints_frame_user_defined_limit(time_series, aggregates,
granularity, start, end, limit,
**kwargs):
"""Returns a DatapointsResponse object with the requested data.
No paging or parallelizing is done.
Args:
time_series (str): The list of timeseries names to retrieve data for. Each timeseries can be either a string containing the
ts name or a dictionary containing the ts name and a list of specific aggregate functions.
aggregates (list): The list of aggregate functions you wish to apply to the data. Valid aggregate functions
are: 'average/avg, max, min, count, sum, interpolation/int, stepinterpolation/step'.
granularity (str): The granularity of the aggregate values. Valid entries are : 'day/d, hour/h, minute/m,
second/s', or a multiple of these indicated by a number as a prefix e.g. '12hour'.
start (Union[str, int, datetime]): Get datapoints after this time. Format is N[timeunit]-ago where timeunit is w,d,h,m,s.
E.g. '2d-ago' will get everything that is up to 2 days old. Can also send time in ms since
epoch or a datetime object which will be converted to ms since epoch UTC.
end (Union[str, int, datetime]): Get datapoints up to this time. Same format as for start.
limit (int): Max number of rows to retrieve. Max is 100,000.
Keyword Arguments:
api_key (str): Your api-key. Obligatory in this helper method.
project (str): Project name. Obligatory in this helper method.
Returns:
v05.dto.DatapointsResponse: A data object containing the requested data with several getter methods with different
output formats.
"""
api_key, project = kwargs.get("api_key"), kwargs.get("project")
cookies = kwargs.get("cookies")
url = config.get_base_url(
api_version=0.5) + "/projects/{}/timeseries/dataframe".format(project)
body = {
"items": [{
"name": "{}".format(ts)
} if isinstance(ts, str) else {
"name": "{}".format(ts["name"]),
"aggregates": ts.get("aggregates", [])
} for ts in time_series],
"aggregates":
aggregates,
"granularity":
granularity,
"start":
start,
"end":
end,
"limit":
limit,
}
headers = {
"api-key": api_key,
"content-type": "application/json",
"accept": "text/csv"
}
res = _utils.post_request(url=url,
body=body,
headers=headers,
cookies=cookies)
df = pd.read_csv(
io.StringIO(
res.content.decode(
res.encoding if res.encoding else res.apparent_encoding)))
return df
