das.iot_client.interfaces package

Submodules

das.iot_client.interfaces.assets_client module

class das.iot_client.interfaces.assets_client.AssetsClient

Bases: object

Methods

`get_all_assets`([templates, event_types])	Get all assets for the organization.
`get_asset_template`([template_id, template_name])	Get details of an asset template in IoT-TICKET.
`get_asset_templates`()	Get a list of asset templates in IoT-TICKET.
`get_assets`([asset_id, asset_name, names_path])	Get information of assets in a certain position of the asset tree.
`get_attributes`([asset_id, asset_name, ...])	Read asset attributes information.
`print_asset_tree`([asset_id, asset_name, ...])	Get all available assets printed in a tree form.

get_all_assets(templates=None, event_types=None)

Get all assets for the organization.

Parameters

templatesbool: Whether to include asset template ids in the response.
event_typesbool: Whether to include active event type for assets in the response

Returns

[Asset]: All assets for the organization as a list of Asset objects.

get_asset_template(template_id=None, template_name=None)

Get details of an asset template in IoT-TICKET.

Exactly one of template_id or template_name must be provided.

Parameters

template_idstr: Id of the template to get info from.
template_namestr: Name of the template to get info from.

Returns

dict: Asset template information as a dict including the keys ‘id’, ‘name’ and ‘attributes’.

Raises

ValueError: If template with the given name isn’t found.
Exception: If there are multiple templates with the given name.

get_asset_templates()

Get a list of asset templates in IoT-TICKET.

Returns

[AssetTemplate]: All asset templates for the organization as a list of AssetTemplate objects.

get_assets(asset_id=None, asset_name=None, names_path=None)

Get information of assets in a certain position of the asset tree.

At most one of asset_id, asset_name or names_path can be given. If none of these parameters are given, root level assets are returned.

Parameters

asset_idstr: Optional parent asset id for which child assets in the assets tree are read.
asset_namestr: Optional parent asset name for which child assets in the assets tree are read. This requires that in the whole asset tree the given name is unique. Otherwise asset_id or names_path must be used.
names_path[str]: List of strings containing the path to wanted asset for which child assets in the assets tree are returned. For example to get the child assets of an asset in the path root_asset/another_asset, this parameter should be given in the form of [‘root_asset’, ‘another_asset’].

Returns

[Asset]: Asset information in the wanted location of the asset tree as a list of Asset objects.

Raises

Exception: If more than one of parameters asset_id, asset_name and names_path was given.

get_attributes(asset_id=None, asset_name=None, names_path=None, attribute_type=None)

Read asset attributes information.

Exactly one of asset_id or asset_name or names_path must be provided.

Parameters

asset_idstr: Id of the asset to read attributes from.
asset_namestr: Name of the asset to read attributes from. This requires that in the whole asset tree the name is unique. Otherwise asset_id or names_path must be used.
names_path[str]: List of strings containing the path to wanted asset. For example an attribute of an asset in the path root_asset/child_asset/wanted_asset should be in the form of [‘root_asset’, ‘child_asset’, ‘wanted_asset’].
attribute_typestr: Optional asset attribute type filter. One of AssetEvent, Calculated, DeviceEvent, Number, String or TelemetryData.

Returns

[AssetAttribute]: Attributes under the selected asset as a list of AssetAttribute objects.

Raises

Exception: If a wrong number of parameters asset_id or asset_name or names_path was given.
ValueError: If attibute_type parameter had wrong value.

print_asset_tree(asset_id=None, asset_name=None, names_path=None)

Get all available assets printed in a tree form. This method doesn’t return anything.

At most one of asset_id, asset_name or names_path can be given. If none of these parameters are given, asset tree is printed starting from the root level.

Parameters

asset_idstr

Optional parent asset id to print assets only from below the given asset.

asset_namestr

Optional parent asset name to print assets only from below the given asset.

This requires that in the whole asset tree the name is unique. Otherwise asset_id or names_path must be used.

names_path[str]

List of strings containing the path to wanted asset for which child assets in the assets tree are printed. For example to print the child assets of an asset in the path root_asset/another_asset, it should be in the form of [‘root_asset’, ‘another_asset’]

Raises

Exception: If more than one of parameters asset_id, asset_name and names_path was given.

das.iot_client.interfaces.commands_client module

class das.iot_client.interfaces.commands_client.CommandsClient

Bases: object

Methods

`get_command_details`([names_path, ...])	Read asset's latest command log entry details.
`send_command`([payload, template_variables, ...])	Trigger a command for a command attribute.
`send_control_command`(desired_value[, ...])	Trigger a control command for a command attribute.

get_command_details(names_path=None, asset_name=None, asset_id=None, identifier_name=None, timestamp='datetime', tz=None)

Read asset’s latest command log entry details. The attribute identifier name can be given to read command details from attributes with that identifier name. Note that multiple attributes can have the same attribute identifier name, and the latest details are always fetched.

Either the names_path parameter or asset_id or asset_name parameter must be given.

Parameters

names_path[str]: List of strings containing the path to wanted asset. For example an attribute of an asset in the path root_asset/child_asset/wanted_asset should be in the form of [‘root_asset’, ‘child_asset’, ‘wanted_asset’].
asset_namestr: Name of the asset that the wanted command attribute is in. The asset_name parameter can only be used if it is unique in the asset tree. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
asset_idstr: Id of the asset that the wanted command attribute is in. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
identifier_namestr: Optional asset attribute identifier name. If not provided get latest entries from all command attributes in the asset.
timestampstr, default=’datetime’: Optional: In which form to give the timestamps. Must be either ‘datetime’ or ‘epoch’, default is ‘datetime’. The ‘epoch’ option gives epoch milliseconds. If ‘epoch’, the tz parameter is redundant as epochs are not aware of the timezone.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). The data in IoT-TICKET is in UTC, if user wants the data in some other timezone, it can be determined here. Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

[SimpleCommandLogData]: Command details from the selected asset as a list of SimpleCommandLogData objects.

Raises

Exception: None or multiple of the parameters names_path, asset_name or asset_id were given.

send_command(payload=None, template_variables=None, names_path=None, asset_name=None, asset_id=None, attribute_name=None, attribute_id=None, aggregated=False)

Trigger a command for a command attribute.

Either the names_path parameter or ids or names for the asset and attribute must be given and either the payload or templated_variables parameter must be given.

Parameters

payload: Command payload. Should be used only when the command attribute payload type is Dynamic.
template_variablesdict: Dict of command template variable keys and values. Should be used only when the command attribute payload type is Templated. Example: {“VAL_input1”: 1,”VAL_input2”: “some string”}
names_path[str]: List of strings containing the path to the wanted attribute that is of type Command. This parameter should be given e.g. in the form of [‘root_asset’, ‘another_asset’, ‘command_attribute’].
asset_namestr: Name of the asset that the wanted command attribute is in. The asset_name parameter can only be used if it is unique in the asset tree. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
asset_idstr: Id of the asset that the wanted command attribute is in. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
attribute_namestr: Name of the wanted command attribute. If this parameter is given, it must be paired with the asset_name or the asset_id parameter to locate the attribute.
attribute_idstr: Id of the wanted command attribute. If this parameter is given, it must be paired with the asset_name or the asset_id parameter to locate the attribute.
aggregatedbool, default=False: If True, command will be sent to the given asset and all its sub assets.

Raises

Exception: For a wrong combination of locator or payload/variable parameters or if no Command attributes were found in the given asset or path.

send_control_command(desired_value, names_path=None, asset_name=None, asset_id=None, attribute_name=None, attribute_id=None, skip_first_command=False)

Trigger a control command for a command attribute.

Either the names_path parameter or ids or names for the asset and attribute must be given

Parameters

desired_value: The desired target value.
names_path[str]: List of strings containing the path to the wanted attribute that is of type Command. This parameter should be given e.g. in the form of [‘root_asset’, ‘another_asset’, ‘command_attribute’].
asset_namestr: Name of the asset that the wanted command attribute is in. The asset_name parameter can only be used if it is unique in the asset tree. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
asset_idstr: Id of the asset that the wanted command attribute is in. If this parameter is given, it must be paired with the attribute_name or the attribute_id parameter.
attribute_namestr: Name of the wanted command attribute. If this parameter is given, it must be paired with the asset_name or the asset_id parameter to locate the attribute.
attribute_idstr: Id of the wanted command attribute. If this parameter is given, it must be paired with the asset_name or the asset_id parameter to locate the attribute.
skip_first_commandbool, default=False: If True, will skip sending the first command. Command will be re-sent later if desired value has not been set.

Raises

Exception: For a wrong combination of locator parameters or if no Command attributes were found in the given asset or path.

das.iot_client.interfaces.credentials_client module

class das.iot_client.interfaces.credentials_client.CredentialsClient

Bases: object

Methods

`get_credential_query`([organization_id, ...])	Query credentials by given information.
`get_credentials`([organization_id])	Read credentials information.

get_credential_query(organization_id=None, credential_id=None, credential_name=None, client_id=None, scope=None)

Query credentials by given information.

Note that this method is only available for users with Subscription Owner role in IoT-TICKET.

Parameters

organization_idstr: The organization to get information from.
credential_idstr: Id of the credential.
credential_namestr: Name of the credential.
client_idstr: Id of the client.
scopestr: Scope of the credential.

Returns

dict: credential’s details as a dict with the following keys: id, name, description, grantType, accessTokenUrl, scope, clientId, organization, subscription, updatedBy, createdBy, updatedAt, createdAt.

get_credentials(organization_id=None)

Read credentials information.

Note that this method is only available for users with Subscription Owner or Organization Admin or Designer role on IoT-TICKET.

Parameters

organization_idstr: The organization to get information from. Default is the IoTClient’s default organization_id.

Returns

credentials[Credential]: All credentials for this user.

das.iot_client.interfaces.data_client module

class das.iot_client.interfaces.data_client.DataClient

Bases: object

Methods

`get_multiple_timeseries`([names_path, ...])	Get data from multiple Telemetry Data or Calculated attributes with the same call.
`get_statistics`(period, dimension[, ...])	Read asset attribute statistics values.
`get_timeseries`([names_path, attribute_id, ...])	Read asset attribute values from a single Telemetry Data or Calculated attribute.
`get_timesignal`(timesignal_id[, ...])	Read asset timesignal attribute values.
`write_calculated`(data[, names_path, ...])	Write to IoT-TICKET's Calculated attributes.
`write_static`(data[, attribute_ids, ...])	Write to IoT-TICKET's static String or Number attributes.
`write_telemetry`(data, device_id, ...[, ...])	Write data to a device in IoT-TICKET.
`write_timesignal`(device_id, device_username, ...)	Write a time signal to a device in IoT-TICKET.
`write_timesignals`(device_id, ...[, tz])	Write one or multiple time signals to a device in IoT-TICKET based on the complete payload given by the user.

get_multiple_timeseries(names_path=None, asset_name=None, asset_id=None, attribute_ids=None, attribute_type=None, start_time=None, end_time=None, chronological_order=False, limit=10000, form='DataFrame', astype=<class 'str'>, timestamp='datetime', tz=None)

Get data from multiple Telemetry Data or Calculated attributes with the same call.

Exactly one of names_path, asset_name, asset_id or attribute_ids must be provided. Using different parameters, the user can determine how to get data (see Parameters section).

For dataframes, information of the data source will be added. It can be found in the df.attrs[‘sources’].

Which information is stored in the dataframe ‘sources’ is dependent on which information the user provides for this method. If attribute_ids is provided, only attribute_ids can be saved. If asset_id, asset_name or names_path is given, also attribute_names, device_ids and asset_path are saved. Here, asset path is the path of names to the asset that is the point in the tree that data is returned under.

Parameters

names_path[str]: List of strings containing the path to an asset. All data under this asset in the whole tree will be returned, subassets included. First name must be the root level asset. For example an asset in the path root_asset/parent_asset/child_asset should be in the form of [‘root_asset’, ‘parent_asset’, ‘child_asset’]. If there are empty attributes in this asset or its subassets, they are ignored.
asset_namestr: Name of the asset to get the data under. Data from all attributes directly under this asset will be returned. If there are empty attributes in this asset, they are ignored.
asset_idstr: Id of the asset to get the data under. Data from all attributes directly under this asset will be returned. If there are empty attributes in this asset, they are ignored.
attribute_ids[str]: Ids of the attributes to get data from. If any of the given attributes is empty, an exception will be raised.
attribute_typestr: Optional attribute type filter to be used with names_path, asset_name or asset_id parameter. Will only get data from attributes of this type under the asset given. Can be one of ‘Telemetry Data’ or ‘Calculated’. For both types, use None (default).
start_timeint or str or datetime: Optional query start time, defaults to zero. If int, given in epochs. If str, given in ISO8601 format.
end_timeint or str or datetime: Optional query end time, defaults to current time. If int, given in epochs. If str, given in ISO8601 format.
chronological_orderbool, default = False: Optional chronological order parameter. Defaults to False. Use False to read measurements in descending order (newest is on top) and True to read measurements in ascending order (oldest is on top) by timestamp.
limitint, default = 10000: Optional: Maximum number of measurements to read per attribute. The default value is 10000.
formstr, default=’DataFrame’: Optional: In which form to return the fetched data. Must be one of ‘json’ or ‘DataFrame’, default is ‘DataFrame’. If ‘DataFrame’, multiple time series will be returned in separate columns. If ‘json’, the name of the respective telemetry will be the dict key.
astypetype, default=’str’: Optional: In which type to give the data. Default is str, and in that case no conversions are done.
timestampstr, default=’datetime’: Optional: In which form to give the timestamps. Must be either ‘datetime’ or ‘epoch’, default is ‘datetime’. If ‘epoch’, the tz parameter is redundant as epochs are not aware of the timezone.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). This will not affect the start_time and end_time parameters. The data in IoT-TICKET is in UTC, if user wants the data in some other timezone, it can be determined here. Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

datadict or pd.DataFrame: The fetched data.

Raises

Exception: If either multiple or none of the attributes names_path, asset_name, asset_id or attribute_ids were given. If one of the attributes was empty when attribute_ids was given.
ValueError: If an ineligible value was given for the form or timestamp parameter.
TypeError: If an ineligible value was given for the astype parameter.

get_statistics(period, dimension, names_path=None, attribute_id=None, start_time=None, end_time=None, limit=None, timestamp='datetime', tz=None)

Read asset attribute statistics values.

Exactly one of names_path or attribute_id parameter must be provided.

Start and end times are required parameters when period selection is Custom, for other period selections those are ignored.

Parameters

periodstr: Statistics value period: The time span from which the statistics are calculated. Available values: CurrentMoment, CurrentDay, PreviousDay, CurrentWeek, PreviousWeek, CurrentMonth, PreviousMonth, CurrentQuarter, PreviousQuarter, CurrentYear, PreviousYear, Custom (case-sensitive).
dimensionstr: Calculated values dimension: How to group values into bins. Available values: Minute, Hour, Day, Week, Quarter, Month, Year (case-sensitive).
names_path[str]: List of strings containing the path to the wanted attribute. For example, an attribute of an asset in the path root_asset/parent_asset/child_asset should be in the form of [‘root_asset’, ‘parent_asset’, ‘child_asset’, ‘attribute_name’].
attribute_idstr: Attribute id to read statistics from.
start_timeint or str or datetime: Required query start time, when period selection is Custom, ignored otherwise. If int, given in epochs. If str, given in ISO8601 format.
end_timeint or str or datetime: Required query end time, when period selection is Custom, ignored otherwise. If int, given in epochs. If str, given in ISO8601 format.
limitint: Optional maximum number of measurements to read, maximum and the default value is 10000.
timestampstr, default=’datetime’: Optional: In which form to output the timestamps. Must be either ‘datetime’ or ‘epoch’, default is ‘datetime’. If ‘epoch’, the tz parameter is redundant as epochs are not aware of the timezone.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). This will not affect the start_time and end_time parameters. The data in IoT-TICKET is in UTC, if user wants the data in some other timezone, it can be determined here. Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

list: A list of dicts containing the keys stattime, count, sum, avg, min and max.

get_timeseries(names_path=None, attribute_id=None, start_time=None, end_time=None, chronological_order=False, limit=10000, form='DataFrame', astype=<class 'str'>, timestamp='datetime', tz=None)

Read asset attribute values from a single Telemetry Data or Calculated attribute.

Exactly one of attribute_id or names_path must be provided.

For dataframes, information of the data source will be added. It can be found in the df.attrs[‘sources’]. This can help the user keep track of the data’s origins.

Which information is stored in the dataframe ‘sources’ is dependent on which information the user provides for this method. If attribute_ids is provided, only attribute_ids can be saved. If asset_id, asset_name or names_path is given, also attribute_names, device_ids and asset_path are saved. Here, asset_path is the path of names to the asset that is the point in the tree that data is returned under.

Parameters

names_path[str]: List of strings containing the path to the wanted attribute. The first name must be the root level asset and last name the wanted attribute name. For example an attribute in the path root_asset/parent_asset/child_asset should be in the form of [‘root_asset’, ‘parent_asset’, ‘child_asset’, ‘attribute_name’].
attribute_idstr: Id of the attribute to get data from.
start_timeint or str or datetime: Optional query start time, defaults to zero. If int, given in epochs. If str, given in ISO8601 format.
end_timeint or str or datetime: Optional query end time, defaults to current time. If int, given in epochs. if str, given in ISO8601 format.
chronological_orderbool, default = False: Optional chronological order parameter. Defaults to False. Use False to read measurements in descending order (newest is on top) and True to read measurements in ascending order (oldest is on top) by timestamp.
limitint, default = 10000: Optional: Maximum number of measurements to read, the default value is 10000.
formstr, default=’DataFrame’: Optional: In which form to return the fetched data. Must be one of ‘json’ or ‘DataFrame’, the default is ‘DataFrame’.
astypetype, default=str: Optional: In which type to give the data. Default is str, and in that case no conversions are done.
timestampstr, default=datetime: Optional: In which form to give the timestamps Must be either ‘datetime’ or ‘epoch’, default is ‘datetime’ If ‘epoch’, the tz parameter is redundant as epochs are not aware of the timezone.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). This will not affect the start_time and end_time parameters. The data in IoT-TICKET is in UTC, if user wants the data in some other timezone, it can be determined here. Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

datadict or pd.DataFrame: The fetched data. If dataframe, it contains only two columns: timestamp and value If json, it is a list of timestamp and value dicts.

Raises

Exception: Wrong number of attribute_id or names_path parameters.
ValueError: The value of the form or timestamp parameters was wrong.
TypeError: The parameter value astype was not of type ‘type’.

get_timesignal(timesignal_id, attribute_id=None, names_path=None, timestamp='datetime', tz=None)

Read asset timesignal attribute values. Exactly one of attribute_id or names_path must be provided.

Parameters

timesignal_idstr: Time signal id to read content for.
attribute_idstr: Id for the attribute to read timesignal content from.
names_path[str]: List of strings containing the path to the wanted attribute. First name must be the root level asset and last name the wanted attribute name. For example an attribute in the path root_asset/parent_asset/child_asset should be in the form of [‘root_asset’, ‘parent_asset’, ‘child_asset’, ‘attribute_name’].
timestampstr, default=’datetime’: Optional: In which form to give the timestamps. Must be either ‘datetime’ or ‘epoch’. Default is ‘datetime’.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). The data in IoT-TICKET is in UTC, if user wants the data in some other timezone, it can be determined here.

Returns

dict: Time signal values.

write_calculated(data, names_path=None, attribute_ids=None, tz=None)

Write to IoT-TICKET’s Calculated attributes.

Exactly one of attribute_ids or names_path parameters must be given.

Parameters

datapandas.DataFrame: Data to write to the attribute. First column must be named ‘timestamp’ and it must contain timestamps in datetime, str or int (epochs). If names_path parameter is used, data columns must be named with corresponding names with the target attribute names.
names_path[str]: List of strings containing the path to the wanted asset. For example an asset in the path root_asset/parent_asset/child_asset should be in the form of [‘root_asset’, ‘parent_asset’, ‘child_asset’]. Here, dataframe column names are used to find which attributes to write to.
attribute_ids[str]: The attributes to write data to. The number of attribute_ids given must match the number of data columns in the data.
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

responsebool: Tells whether sending the requests were succesful. Note that based on this return value being True, it cannot be known whether data was written succesfully, as the operation on server-side is asynchronic.

das.iot_client.interfaces.devices_client module

class das.iot_client.interfaces.devices_client.DevicesClient

Bases: object

Methods

`get_device`(device_id)	Get information from a specific device.
`get_devices`([asset_id, asset_name, names_path])	Get device ids.

get_device(device_id)

Get information from a specific device.

Parameters

device_idstr: The device to get information from.

Returns

deviceDevice: The Device base class.

get_devices(asset_id=None, asset_name=None, names_path=None)

Get device ids.

At most one of asset_id or asset_name or names_path must be given. If none of these parameters are given, all devices are returned.

Parameters

asset_idstr: Asset id to search devices linked to the given asset only.
asset_namestr: Asset name to search devices linked to the given asset only.
names_path[str]: List of strings containing the path to wanted asset to search devices linked to that asset only.

Returns

devices[str]: List of device ids.

Raises

Exception: If more than one of the parameters asset_id, asset_name and names_path was given.

das.iot_client.interfaces.events_client module

class das.iot_client.interfaces.events_client.EventsClient

Bases: object

Attributes

asset_event_active_count: Get the number of events that are currently active.

Methods

`get_asset_event_history`([asset_ids, ...])	Get event history from IoT-TICKET for an organization.
`get_asset_events_active`([asset_ids, ...])	Get active asset events from IoT-TICKET for an organization.
`write_device_event`(device_id, ...[, ...])	Write a device event to IoT-TICKET.
`write_device_events`(device_id, ...[, tz])	Write multiple device events to IoT-TICKET based on the complete json payload that is delivered by the user.

property asset_event_active_count

Get the number of events that are currently active.

Returns

int: The number of active events

Raises

Exception: If there are over 10000 active events.

get_asset_event_history(asset_ids=None, asset_names=None, event_type=None, start_time=None, end_time=None, acknowledged=True, only_acknowledged=False, limit=10000)

Get event history from IoT-TICKET for an organization.

Exactly one of asset_ids or asset_names must be provided.

Parameters

asset_ids[str]: List of strings to filter from which assets to get events from based on the asset ids.
asset_names[str]: List of strings to filter from which assets to get events from based on the asset names.
event_typestr: Optional parameter to filter based on the event’s type. Possible values are: ‘Alarm’, ‘Notification’, ‘Warning’.
start_timeint or str or datetime: Optional filter parameter to get events that started only after the given start_time. If int, given in epochs. If str, given in ISO8601 format.
end_timeint or string or datetime: Optional filter parameter to get events that started only before the given end_time. If int, given in epochs. If str, given in ISO8601 format.
acknowledgedbool, default=True: Optional: whether to include the acknowledged events in the response.
only_acknowledgedbool, default=False: Optional: whether to include only the acknowledged events in the response.
limitint, default=10000: Optional parameter to limit the number of events returned. The default value is 10000.

Returns

[AssetEventReadResponse]: A list of AssetEventReadResponse objects.

Raises

ValueError: If event_type parameter had an invalid value.
Exception: If both or none of asset_ids and asset_names were given. If only_acknowledged=True and acknowledged=False. This would result in an empty list every time.

get_asset_events_active(asset_ids=None, asset_names=None, event_type=None, start_time=None, acknowledged=True, limit=10000)

Get active asset events from IoT-TICKET for an organization.

At most one of asset_ids or asset_names must be provided.

Parameters

asset_ids[str]: Optional list of strings to filter from which assets to get events from based on the asset ids.
asset_names[str]: Optional list of strings to filter from which assets to get events from based on the asset names.
event_typestr: Optional parameter to filter based on the event’s type. Possible values are: ‘Alarm’, ‘Notification’, ‘Warning’.
start_timeint or str or datetime: Optional filter parameter to get events that started only after the given start_time. If int, given in epochs. If str, given in ISO8601 format.
acknowledgedbool, default=True: Optional: whether to include acknowledged events in the response.
limitint, default=10000: Optional parameter to limit the number of events returned. The default value is 10000.

Returns

[AssetEventReadResponse]: A list of AssetEventReadResponse objects.

Raises

ValueError: If event_type parameter had an invalid value.
Exception: If both of asset_ids and asset_names were given.

write_device_event(device_id, device_username, device_password, event_id, message, timestamp, event_group_name=None, event_type=None, severity=None, is_active=None, tz=None)

Write a device event to IoT-TICKET.

Parameters

device_idstr: The device to add data to.
device_usernamestr
device_passwordstr: Device credentials. These are created and can be reseted in the IoT-TICKET UI in Data Management -> Devices.
event_idstr: Required text field for event identification. Max length is 255.
messagestr: Required text field for event message. Max length is 255.
timestampstr or int or datetime: Timestamp in str or int (epochs) or datetime. If string, must be in ISO8601 format. This form is of ‘{year}-{month}-{day}T{hours}:{minutes}:{seconds}.{milliseconds}Z’.
event_group_namestr: Optional text fields for event group names. Max length is 255.
event_typestr: Optional type of the event. Accepted values are “Alarm”, “Warning” and “Notification” (case-sensitive).
severitystr: Optional severity level for the event. Accepted values are “Low”, “Normal”, “High” and “Critical” (case-sensitive).
is_activebool: Optional boolean to indicate event state (active / inactive).
tzstr: Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

bool: True if the request was sent succesfully.

Raises

jsonschema.exceptions.ValidationError: For incorrect event parameters.
requests.HTTPError: An error based on requests.response.raise_for_status().

write_device_events(device_id, device_username, device_password, payload, tz=None)

Write multiple device events to IoT-TICKET based on the complete json payload that is delivered by the user.

An alternative way to write device events is to use the write_device_event method, which will construct the payload of a single event based on user’s parameters.

Parameters

device_idstr

The device to add data to

device_usernamestr

device_passwordstr

Device credentials. These are created and can be reseted in the IoT-TICKET UI in Data Management -> Devices.

payloaddict

Complete json to send with the request. Each event must include the fields “id”, “m” (for message) and “ts” (for timestamp). Optional fields are “gn” (event group name), “type” (“Alarm”, “Warning” or “Notification”), “severity” (“Low”, “Normal”, “High” or “Critical”) and “active” (boolean). Payload (of two events) can for example be in a form of:

{
    "e": [{
            "id": "111_COLL_ALARM",
            "m": "Streetlight Collision Alarm",
            "gn": "Collisions",
            "ts": "2021-04-17T17:00:00.000Z",
            "type": "Alarm",
            "severity": "High",
            "active": true
        },
        {
            "id": "112_TOO_HOT",
            "m": "Temperature currently 94 degrees, (over recommended 50)",
            "gn": "Temperatures",
            "ts": "2021-04-17T17:00:00.000Z",
            "type": "Alarm",
            "severity": "High",
            "active": false
        },
        ...
    ]
}

Timestamps must be in str or int (epochs) or datetime. If string, must be in ISO8601 format. This form is of ‘{year}-{month}-{day}T{hours}:{minutes}:{seconds}.{milliseconds}Z’.

tzstr

Optional: Timezone in the form of ±[hh]:[mm], ±[hh][mm], or ±[hh]. Defaults to UTC (‘+00:00’). Note that the timestamps seen in IoT-TICKET are shown as converted to your local timezone.

Returns

bool: True if the request was sent succesfully.

Raises

jsonschema.exceptions.ValidationError: For incorrect payload parameter
requests.HTTPError: An error based on requests.response.raise_for_status()

das.iot_client.interfaces.models_client module

class das.iot_client.interfaces.models_client.BaseClient: Bases: object

class das.iot_client.interfaces.models_client.ModelsClient

Bases: BaseClient

Attributes

analytics_items_count: Get the count of how many analytics items (MLModels, MLServices and OnnxModels) are currently registered to IoT-TICKET.

Methods

`delete_model`([model_name, model_id])	Delete a registered model in IoT-TICKET.
`get_all_analytics_items`()	List all data-analytics items that are registered to IoT-TICKET, including models, services and ONNX-models.
`get_model_details`([model_name, model_id])	Get details of a model registered into IoT-TICKET.
`get_model_list`()	List all models that are registered into IoT-TICKET.
`register_model`(model)	Create a registered ML model to IoT-TICKET.
`update_model`(model)	Update a model in IoT-TICKET.

property analytics_items_count

Get the count of how many analytics items (MLModels, MLServices and OnnxModels) are currently registered to IoT-TICKET.

The amount is limited by IoT-TICKET based on your subscription. The limit can be seen in IoT-TICKET by the organization admin in the Organization management -> Statistics tab.

Returns

int: How many analytics items are currently registered to IoT-TICKET.

delete_model(model_name=None, model_id=None)

Delete a registered model in IoT-TICKET.

Exactly one of model_id or model_name must be given.

A model can only be deleted if it is not used in an asset in IoT-TICKET

Parameters

model_namestr: The name of the model in IoT-TICKET.
model_idstr: The id of the model in IoT-TICKET. Note that the model id is not visible in the IoT-TICKET UI, but must be queried with the .get_model_list()-method

Returns

bool: True if the model was deleted.

Raises

Exception: If the model was in use in an asset in IoT-TICKET

get_all_analytics_items()

List all data-analytics items that are registered to IoT-TICKET, including models, services and ONNX-models.

Returns

[dict]: List of dicts containing the model id, name, level and type. Type is one of ‘MLModel’, ‘MLService’ or ‘OnnxModel’. Level is one of ‘organization’, ‘subscription’ or ‘platform’.

get_model_details(model_name=None, model_id=None)

Get details of a model registered into IoT-TICKET.

Exactly one of model_id or model_name must be given.

Parameters

model_namestr: The name of the model in IoT-TICKET.
model_idstr: The id of the model in IoT-TICKET. Note that the model id is not visible in the IoT-TICKET UI, but must be queried with the .get_model_list()-method.

Returns

dict: The details of the model including the following keys: id, name, description, helpText, triggerUrl, jobId, clientId, token, organization, subscription, updatedBy, createdBy, updatedAt, createdAt, inputs, outputs, headers.

Raises

Exception: If either both or none of model_id and model_name were given.

get_model_list()

List all models that are registered into IoT-TICKET.

Returns

[dict]: Registered models as a list of dicts including the following keys: id, name, jobId, organization, subscription.

register_model(model)

Create a registered ML model to IoT-TICKET.

Parameters

modeldict: The dict must include following keys: name, description, help_text, trigger_url, method (one of ‘POST’, ‘GET’, ‘PUT’), client_id&scope (or headers), inputs and outputs. Best practice is to give this with the DatabricksJob.as_dict() method (see example).

Returns

str: The id of the registered model as a string.

Raises

ValidationError: If given model dict was in a wrong form.

Examples

Best practice is to use helper classes to create a job instance:

>>> from das import DatabricksJob
>>> job = DatabricksJob(name = ...)

DatabricksClient from the das package can also be used to do

>>> job_json = databricksClient.jobs.list_jobs()['jobs'][job index]
>>> job = DatabricksJob.from_json(job_json, credential)

The inputs and outputs must be defined for the job instance:

>>> job.notebook_inputs = [NotebookNode('name', ...)]
>>> job.notebook_outputs = [NotebookNode('name', ...)]

The model can then be registered:

>>> client.register_model(model=job.as_dict())

update_model(model)

Update a model in IoT-TICKET.

If the model is being used in an asset, only basic info can be updated. This means that the inputs or outputs cannot be updated while being used.

Parameters

modeldict: The dict must include the keys for basic info, which are name, description, help_text, trigger_url, method, job_id and credential_id. The dict can include also the keys inputs and outputs, but in this case the model cannot be in used in an asset or the call will fail. Best practice is to give this parameter with the DatabricksJob.as_dict() method for full info or DatabricksJob.base_body property for the basic info.

Returns

bool: True if model was updated.

Raises

ValidationError: If the given model dict was in a wrong form.
Exception: If the “model” parameter included more than the basic info, but the registered model was in use in an asset in IoT-TICKET.

class das.iot_client.interfaces.models_client.OnnxClient

Bases: object

Methods

`delete_onnx_model`([model_name, model_id])	Delete an ONNX model that is registered into IoT-TICKET
`get_onnx_model_details`([model_name, model_id])	Get details of a registered ONNX Model.
`get_onnx_model_list`()	Get all registered ONNX Models.
`register_onnx_model`(name[, onnx_model, ...])	Register a model to IoT-TICKET in ONNX (Open Neural Network Exchange) form.
`update_onnx_model`(payload[, model_id])	Update ONNX model basic information.

delete_onnx_model(model_name=None, model_id=None)

Delete an ONNX model that is registered into IoT-TICKET

One of model_id or model_name must be given.

Parameters

model_name: str: The name of the model to delete.
model_idstr: The id of the model to delete. Note that the model id is not visible in the IoT-TICKET UI, but must be queried with the .get_onnx_model_list()-method.

Returns

bool: True if model was deleted succesfully.

Raises

Exception: If either both or none of model_id and model_name were given.

get_onnx_model_details(model_name=None, model_id=None)

Get details of a registered ONNX Model.

Exactly one of model_id or model_name must be given.

Parameters

model_namestr: The name of the model to get.
model_idstr: The id of the model to get. Note that the model id is not visible in the IoT-TICKET UI, but must be queried with the .get_onnx_model_list()-method.

Returns

dict: The model as a dict containing the keys id, name, description, helpText, inputs, outputs, organization, subscription, updatedBy, createdBy, updatedAt, createdAt.

Raises

Exception: If either both or none of model_id and model_name were given.

get_onnx_model_list()

Get all registered ONNX Models.

Returns

[dict]: List of dicts containing the model id, name, level and type. For this call, type is always ‘OnnxModel’. Level is one of ‘organization’, ‘subscription’ or ‘platform’.

register_onnx_model(name, onnx_model=None, file_location=None, description=None, help_text=None)

Register a model to IoT-TICKET in ONNX (Open Neural Network Exchange) form. One of the onnx_file or file_location must be given.

Parameters

namestr: Name of the model.
onnx_modelonnx.ModelProto,: The ONNX model.
file_locationstr: Path to the ONNX file.
descriptionstr: Model description to be shown in IoT-TICKET. Can be empty or missing.
help_textstr: Model help text in markdown. Can be empty or missing.

Returns

str: The id of the created ONNX Model.

Raises

Exception: Multiple or none of the parameters onnx_model and file_location were provided. The given file_location path didn’t lead to a file with type .onnx
TypeError: The given onnx model was not a ModelProto object.
FileNotFoundError: File with the given file_location path was not found.

update_onnx_model(payload, model_id=None)

Update ONNX model basic information.

Parameters

payloaddict: The model information to update. Must contain at least the key ‘name’. Can also contain the keys ‘description’ and ‘help_text’ to update those. These will be converted to strings.
model_idstr: The id of the model to update. Optional, if the name included in the payload is unique. Note that the model id is not visible in the IoT-TICKET UI, but must be queried with the .get_onnx_model_list()-method.

Returns

bool: True if model was edited succesfully.

Raises

Exception: If the given payload parameter was invalid.

class das.iot_client.interfaces.models_client.ServicesClient

Bases: BaseClient

Methods

`delete_service`([service_name, service_id])	Delete a registered service in IoT-TICKET.
`get_service_details`([service_name, service_id])	Get details of a service registered into IoT-TICKET.
`get_service_list`()	List all services that are registered into IoT-TICKET.
`register_service`(service)	Create a registered ML service to IoT-TICKET.
`update_service`(service[, service_name, ...])	Update a service in IoT-TICKET.

delete_service(service_name=None, service_id=None)

Delete a registered service in IoT-TICKET.

Exactly one of service_id or service_name must be given.

Parameters

service_namestr: The name of the service in IoT-TICKET.
service_idstr: The id of the service in IoT-TICKET. Note that the service id is not visible in the IoT-TICKET UI, but must be queried with the .get_service_list()-method.

Returns

bool: True if the service was deleted
Exception: If either both or none of service_id and service_name were given.

get_service_details(service_name=None, service_id=None)

Get details of a service registered into IoT-TICKET.

Exactly one of service_id or service_name must be given.

Parameters

service_namestr: The name of the service in IoT-TICKET.
service_idstr: The id of the service in IoT-TICKET. Note that the service id is not visible in the IoT-TICKET UI, but must be queried with the .get_service_list()-method.

Returns

dict: The details of the service including the following keys: id, name, description, helpText, triggerUrl, requestContainsTimestamps, responseContainsTimestamps, headers, inputSchema, outputSchema, organization, subscription, updatedBy, createdBy, updatedAt, createdAt.

Raises

Exception: If either both or none of service_id and service_name were given.

get_service_list()

List all services that are registered into IoT-TICKET.

Returns

[dict]: Registered services as a list of dicts including the following keys: id, name, description, helpText, triggerUrl, requestContainsTimestamps, responseContainsTimestamps, headers, inputSchema, outputSchema, organization, subscription, updatedBy, createdBy, updatedAt, createdAt. Values of only basic info are in the returned value, as others have None values.

register_service(service)

Create a registered ML service to IoT-TICKET.

Parameters

servicedict: The dict must include following keys: name, description, help_text, trigger_url, method, client_id&scope (or headers), input_schema, request_contains_timestamps, output_schema and response_contains_timestamps. Best practice is to give this with one of the registration classes’ .as_dict() method (see example).

Returns

str: The id of the registered service as a string.

Raises

ValidationError: If given service dict was in a wrong form.

Examples

Best practice is to use helper registration classes to create a function instance:

>>> from das import AzureFunction
>>> job = AzureFunction(name = ...)

AzureFunctionsClient from the das package can also be used to do

>>> function_json = azureFunctionsClient.list_functions()['value'][function index]
>>> function = AzureFunction.from_json(function_json, credential)

The inputs and outputs must be defined, or they can be inferred by running the function:

>>> function.try_out_infer(example_data, inplace=True)

Tell IoT-TICKET wheter to send timestamps when running the function:

>>> function['request_contains_timestamps'] = False
>>> function['response_contains_timestamps'] = False

The service can then be registered:

>>> client.register_service(service=function.as_dict())

update_service(service, service_name=None, service_id=None)

Update a service in IoT-TICKET.

Exactly one of service_id or service_name must be given.

Parameters

servicedict: The dict must include the keys for at least the basic info, which are name, description, help_text, trigger_url, method, credential_id, request_contains_timestamps and response_contains_timestamps. The dict can also include keys input_schema and output_schema to update those. Best practice is to give this with on of the .as_dict() method of the registration class for full info or .base_body property for basic info.
service_namestr: The name of the service in IoT-TICKET.
service_idstr: The id of the service in IoT-TICKET. Note that the service id is not visible in the IoT-TICKET UI, but must be queried with the .get_service_list()-method.

Returns

bool: True if service was updated.

Raises

ValidationError: If given service dict was in a wrong form.
Exception: If either both or none of service_id and service_name were given.

das.iot_client.interfaces.organizations_client module

class das.iot_client.interfaces.organizations_client.OrganizationsClient

Bases: object

Methods

`get_organization_details`([organization_id])	Get details for current organization (default), or for the organization of which id was given.
`get_organizations`()	Read organizations information.

get_organization_details(organization_id=None)

Get details for current organization (default), or for the organization of which id was given.

Note that this method is only available for subscription owner.

Parameters

organization_idstr: Optional organization_id to find details for another organization.

Returns

dict: Organization’s details as a dict including the following keys: id, name, description, enable, contactPerson, ccountManager, limits, usedLimits, createdBy, modifiedBy, created, lastModified

get_organizations()

Read organizations information.

Returns

[Organization]: All organizations for this user as a list of Organization objects.

das.iot_client.interfaces package

Submodules

das.iot_client.interfaces.assets_client module

das.iot_client.interfaces.commands_client module

das.iot_client.interfaces.credentials_client module

das.iot_client.interfaces.data_client module

das.iot_client.interfaces.devices_client module

das.iot_client.interfaces.events_client module

das.iot_client.interfaces.models_client module

das.iot_client.interfaces.organizations_client module

Module contents