Client

pingthings.timeseries.client.Client ¶

Client(loop: ClientEventLoop, client: AsyncClient)

Class that manages reusable state and client connections.

This class provides synchronous methods to connect to an asynchronous client, retrieve client and event loop information, and perform various client-related operations such as querying and streaming.

Info

For most users, this client connection will be the only necessary connection type to work with. Queries are accelerated using the asynchronous methods under the hood. If for some reason you need to use the asynchronous client, refer to pingthings.timeseries.async_client.

Create a synchronous client class that manages state for asynchronous client connections.

PARAMETER	DESCRIPTION
`loop` ¶	The event loop used by the client. TYPE: `ClientEventLoop`
`client` ¶	The asynchronous client instance. TYPE: `AsyncClient`

METHOD	DESCRIPTION
`connect`	Establish a synchronous connection to the asynchronous client.
`create`	Create a new stream with the given uuid and collection name.
`create_device`	Creates a device with fields matching the passed dictionary. `name` can not be `None` or an empty string, two
`create_unit`	Create a new representation of a unit definition in the platform.
`delete_device`	Deletes the device with the specified id
`delete_unit`	Remove a unit from the platform.
`get_async_client`	Retrieve the asynchronous client instance.
`get_collection_properties`	Get properties of a collection.
`get_device`	Returns a device with a matching id in the device table.
`get_event_loop`	Retrieve the event loop instance.
`get_unit`	Returns a unit with a matching id in the unit table.
`info`	Retrieve information about the server and proxy server the client is connected to.
`list_collections`	Returns a list of collection paths using the `prefix` argument for
`list_devices`	Returns a list of devices the user has permission to see.
`list_units`	Returns a list of units generated in the database.
`set_collection_retention`	Set retention policy on a collection of streams.
`sql_query`	Performs a SQL query on the database metadata and returns a list of
`stream_from_uuid`	Retrieve a stream based on its UUID.
`streams_in_collection`	Search for streams matching given parameters
`streamset_from_uuids`	Return a `StreamSet` from an iterable of UUIDs.
`update_device`	Updates a `device` with matching `device["id"]` using fields matching the passed dictionary. `name` can not be `None`
`update_unit`	Updates a `unit_dict` with matching `id` using fields from the passed dictionary.

ATTRIBUTE	DESCRIPTION
`concurrency_limit`	The concurrency limit for background asynchronous operations.

Attributes¶

concurrency_limit `property` `writable` ¶

concurrency_limit

The concurrency limit for background asynchronous operations.

Setting the value overrides the environment variable

If you choose to set a custom concurrency_limit, this will bypass the environment variable PINGTHINGS_CONCURRENCY_LIMIT value.

Functions¶

connect `staticmethod` ¶

connect(
    profile: Optional[str] = None,
    endpoint: Optional[str] = None,
    apikey: Optional[str] = None,
    concurrency_limit: Optional[int] = None,
) -> Client

Establish a synchronous connection to the asynchronous client.

PARAMETER	DESCRIPTION
`profile` ¶	The name of a profile containing the required connection information as found in the user's predictive grid credentials file `${HOME}/.predictivegrid/credentials.yaml`. TYPE: `Optional[str]` DEFAULT: `None`
`endpoint` ¶	The address and port of the cluster to connect to, e.g. `192.168.1.1:4411`, if not set, will look for the environment variable `$BTRDB_ENDPOINTS` TYPE: `Optional[str]` DEFAULT: `None`
`apikey` ¶	The API key used to authenticate requests, if not set, the key is looked up from the environment variable `$BTRDB_API_KEY`. TYPE: `Optional[str]` DEFAULT: `None`
`concurrency_limit` ¶	The maximum number of concurrent database requests to have in flight at any one time, if not set, will be inferred from environment variable `$PINGTHINGS_CONCURRENCY_LIMIT`. TYPE: `Optional[int]` DEFAULT: `None`

RETURNS	DESCRIPTION
`Client`	An instance of the Client class.

Examples:

Connecting to the timeseries platform as a commercial customer in the PingThings provided JupyterHub/Lab environment. This behavior also works if you have the environment variables set, refer to the above docstring for more information.

import pingthings as pt
conn = pt.timeseries.connect()

Connecting to the timeseries platform when you know your api key and FQDN endpoint.

import pingthings as pt
my_key = "ABC123"
my_endpoint = "example.com:4411"

conn = pt.timeseries.connect(apikey=my_key, endpoint=my_endpoint)

Connecting to the platform when you have a populated ${HOME}/.predictivegrid/credentials.yaml file with profiles.

import pingthings as pt
conn = pt.timeseries.connect(profile='my_server')

create ¶

create(
    uuid: UUID,
    collection: str,
    tags: dict[str, str],
    annotations: Optional[dict[str, str]] = None,
) -> Stream

Create a new stream with the given uuid and collection name.

PARAMETER	DESCRIPTION
`uuid` ¶	The UUID for the new stream. TYPE: `UUID`
`collection` ¶	The collection to which the stream belongs. TYPE: `str`
`tags` ¶	Tags associated with the stream. TYPE: `dict[str, str]`
`annotations` ¶	Annotations for the stream. TYPE: `Optional[dict[str, str]]` DEFAULT: `None`

RETURNS	DESCRIPTION
`Stream`	The newly created stream.

Required and Allowable Tags/Annotations

The name field in tags must be set and currently all tags/annotations must be encoded as strings and two streams can not share both the same collection and name.

Available tags in the stream table

column_name	Description
name	name of the stream
source	Where did the stream come from
device_id	What device is the stream attached to
samples_per_second	What is the nominal report rate of the data, in Hz?
time_precision	How accurate is each timestep (+- nanoseconds)
value_precision	Bit precision
dynamic	Can the timeseries stream send us data at varying report rates?
continuous	Should we expect a continuous stream of data?
description	Additional information about the timeseries stream
alt_name	Additional name that the stream may be referenced by
alt_id	Alternative ID (most likely SignalID from STTP)
norm_factor	A factor to scale the measurement by to normalize. Like “baseKV” for voltage, etc.
scaling_factor	The “m” in y=mx + b factor, line-line scaling factor, etc
bias_factor	The “b” in y=mx+b
hidden	Whether the stream should be presented to non-admin users

create_device ¶

create_device(device: dict[str, Any]) -> dict[str, Any]

Creates a device with fields matching the passed dictionary. name can not be None or an empty string, two devices can not share the same name and geo, and enabled=True by default.

PARAMETER	DESCRIPTION
`device` ¶	dictionary with the possible keys and description of expected values below. TYPE: `dict[str, Any]`

RETURNS	DESCRIPTION
`dict[str, Any]`	A dictionary with the same fields passed with create plus the `device["id"]` set

Available columns in the device table

column_name	Description
name	Name of device
device_type	Type of device (DFR/Relay/etc)
description	User readable description
geo	Coordinates, a dict {"latitude":float,"logitude":float}
elevation	Elevation of the device, float
alt_id	Alternative id, int
alt_name	Alternative name
enabled	Whether the device is expected to be sending data, bool default: True
owner	Who owns the device
protocol	What protocol the device is using to send data
model_name	The model name of the device
vendor	The company that creates/sells the device

create_unit ¶

create_unit(
    name: str,
    symbol: str,
    base: float,
    canonical: str,
    source_name: list[str],
) -> dict[str, Any]

Create a new representation of a unit definition in the platform.

Units are a main way to assign further meaning to the timeseries stored in the platform. There are usually a handful of default units provided with each cluster, however, based on user needs, additional units will need to be included to support the wide range of timeseries added to the platform.

PARAMETER	DESCRIPTION
`name` ¶	Name of the new unit. TYPE: `str`
`symbol` ¶	Symbol of the new unit. TYPE: `str`
`base` ¶	Multiplicative factor to convert the unit to the canonical representation. TYPE: `float`
`canonical` ¶	The "main" unit that this unit can be ultimately converted to. TYPE: `str`
`source_name` ¶	List of other potential `names` that this `unit` can be considered in the platform. For example, if the `unit` name is `degrees` the source_name could include the following: `["deg", "VPHA", "IPHA", "VpHA", "Deg", "DEG"]` TYPE: `list[str]`

RETURNS	DESCRIPTION
`dict[str, Any]`	Dictionary with fields corresponding to the values in the database.

Examples:

>>> unit_def = {"name":"volts", "symbol":"V", "base":1.0, "canonical":"volts", source_name:["VPHM", "voltage", "VOLTS", "VLTGE"]}
>>> unit = client.create_unit(**unit_def)
>>> print(unit)
{'id': 6,
'name': 'volts',
'symbol': 'V',
'canonical': 'volts',
'base': 1.0,
'source_name': ['VPHM', 'voltage', 'VOLTS', 'VLTGE']}

delete_device ¶

delete_device(device_id: int) -> None

Deletes the device with the specified id

PARAMETER	DESCRIPTION
`device_id` ¶	Corresponding id of the device to be deleted TYPE: `int`

RETURNS	DESCRIPTION
`None`	None

delete_unit ¶

delete_unit(unit_id: int) -> None

Remove a unit from the platform.

PARAMETER	DESCRIPTION
`unit_id` ¶	Integer corresponding to the id of the unit in the database. TYPE: `int`

RETURNS	DESCRIPTION
`None`	None

Examples:

>>> client.delete_unit(6)

get_async_client ¶

get_async_client() -> AsyncClient

Retrieve the asynchronous client instance.

RETURNS	DESCRIPTION
`AsyncClient`	The asynchronous client instance.

get_collection_properties ¶

get_collection_properties(
    collection: str,
) -> dict[str, Any]

Get properties of a collection.

PARAMETER	DESCRIPTION
`collection` ¶	The name of the collection. TYPE: `str`

Examples:

Get the retention policy of a collection.

>>> conn.get_collection_properties("bar")
{'retention': {'remove_older_than': datetime.timedelta(days=7)}}

get_device ¶

get_device(device_id: int) -> dict[str, Any]

Returns a device with a matching id in the device table.

PARAMETER	DESCRIPTION
`device_id` ¶	Integer corresponding to the id of the device in the database. TYPE: `int`

RETURNS	DESCRIPTION
`dict[str, Any]`	Dictionary with fields corresponding to the values in the database.

get_event_loop ¶

get_event_loop() -> ClientEventLoop

Retrieve the event loop instance.

RETURNS	DESCRIPTION
`ClientEventLoop`	The event loop instance used by the client.

get_unit ¶

get_unit(unit_id: int) -> dict[str, Any]

Returns a unit with a matching id in the unit table.

PARAMETER	DESCRIPTION
`unit_id` ¶	Integer corresponding to the id of the unit in the database. TYPE: `int`

Returns: Dictionary with fields corresponding to the values in the unit table.

info ¶

info() -> dict[str, Any]

Retrieve information about the server and proxy server the client is connected to.

RETURNS	DESCRIPTION
`dict[str, Any]`	A dictionary containing server and proxy server information.

list_collections ¶

list_collections(prefix: Optional[str] = None) -> list[str]

Returns a list of collection paths using the prefix argument for filtering.

PARAMETER	DESCRIPTION
`prefix` ¶	Filter collections that start with the string provided, if none passed, will list all collections. DEFAULT: `None`

RETURNS	DESCRIPTION
`list[str]`	All collections that match the provided prefix.

Examples:

Assuming we have the following collections in the platform: foo, bar, foo/baz, bar/baz

>>> conn = pt.connect()
>>> conn.list_collections().sort()
["bar", "bar/baz", "foo", "foo/bar"]

>>> conn.list_collections(prefix="foo")
["foo", "foo/bar"]

list_devices ¶

list_devices() -> list[dict[str, Any]]

Returns a list of devices the user has permission to see.

RETURNS	DESCRIPTION
`list[dict[str, Any]]`	Dictionary with keys matching the columns in the device table.

list_units ¶

list_units() -> list[dict[str, Any]]

Returns a list of units generated in the database.

RETURNS	DESCRIPTION
`list[dict[str, Any]]`	Dictionary with keys matching the columns in the units table.

set_collection_retention ¶

set_collection_retention(
    collection: str,
    override_per_stream: bool = False,
    remove_older_than: Optional[datetime] = None,
) -> None

Set retention policy on a collection of streams.

PARAMETER	DESCRIPTION
`collection` ¶	The name of the collection.
`override_per_stream` ¶	Whether stream-specific retention policy should be overridden. TYPE: `bool` DEFAULT: `False`
`remove_older_than` ¶	Trim time period - after which the data will get removed. Not specifying this parameter disables the trimming. TYPE: `Optional[datetime]` DEFAULT: `None`

Examples:

Keep the data for only one week.

>>> conn.set_collection_retention("bar", false, datetime.timedelta(days=7))

sql_query ¶

sql_query(
    query: str, params: Optional[list[str]] = None
) -> list[Any]

Performs a SQL query on the database metadata and returns a list of dictionaries from the resulting cursor.

PARAMETER	DESCRIPTION
`query` ¶	A SQL statement to be executed on the BTrDB metadata. Available columns in the `stream` table are noted below. To sanitize inputs use a `$1` style parameter such as `select * from streams where name = $1 or name = $2`. TYPE: `str`
`params` ¶	A list of parameter values to be sanitized and interpolated into the SQL statement. Using parameters forces value/type checking and is considered a best practice at the very least. TYPE: `Optional[list[str]]` DEFAULT: `None`

RETURNS	DESCRIPTION
`list[Any]`	The result of the SQL query.

Available columns in the stream table

column_name	data_type
uuid	uuid
collection	character varying
name	character varying
unit	character varying
ingress	character varying
property_version	bigint
annotations	hstore
distiller	character varying
created_at	timestamp with time zone
updated_at	timestamp with time zone
geo	postgis geometry
last_written	timestamp with time zone
previous_last_written	timestamp with time zone
estimated_count_delta	bigint
long_term_autoregressive_average	double precision
count_last_updated	timestamp with time zone
previous_count_last_updated	timestamp with time zone
watched	boolean

stream_from_uuid ¶

stream_from_uuid(uuid: UUID | str) -> Stream

Retrieve a stream based on its UUID.

PARAMETER	DESCRIPTION
`uuid` ¶	The UUID of the stream. TYPE: `UUID \| str`

RETURNS	DESCRIPTION
`Stream`	The stream associated with the provided UUID.

RAISES	DESCRIPTION
`TypeError`	If the provided `uuid` is not a valid UUID

streams_in_collection ¶

streams_in_collection(
    collection: str = "",
    is_collection_prefix: bool = True,
    tags: Optional[dict[str, str]] = None,
    annotations: Optional[dict[str, Any]] = None,
) -> StreamSet

Search for streams matching given parameters

PARAMETER	DESCRIPTION
`collection` ¶	collections to use when searching for streams, case sensitive. TYPE: `str` DEFAULT: `''`
`is_collection_prefix` ¶	Whether the collection is a prefix of the whole collection name. TYPE: `bool` DEFAULT: `True`
`tags` ¶	The tags to identify the stream. TYPE: `Optional[dict[str, str]]` DEFAULT: `None`
`annotations` ¶	The annotations to identify the stream. TYPE: `Optional[dict[str, Any]]` DEFAULT: `None`

RETURNS	DESCRIPTION
`StreamSet`	The grouping of streams matching given parameters.

streamset_from_uuids ¶

streamset_from_uuids(
    uuids: list[UUID | str], fetch_metadata: bool = True
) -> StreamSet

Return a StreamSet from an iterable of UUIDs.

PARAMETER	DESCRIPTION
`uuids` ¶	List of stream identifiers TYPE: `list[UUID \| str]`
`fetch_metadata` ¶	Whether to fetch metadata for the streams in the set. Default is True. TYPE: `bool` DEFAULT: `True`

Advanced user feature

Be cautious about using fetch_metadata=False. Many stream metadata values like collection, name, unit, tags, annotations will not be available, meaning filtering and other operations that require metadata will not work.

RETURNS	DESCRIPTION
`StreamSet`	The `StreamSet` associated with the provided iterable of UUIDs.

update_device ¶

update_device(
    device: dict[str, Any], replace: bool = False
) -> dict[str, Any]

Updates a device with matching device["id"] using fields matching the passed dictionary. name can not be None or an empty string.

PARAMETER	DESCRIPTION
`device` ¶	dictionary with the possible keys and description of expected values below. TYPE: `dict[str, Any]`
`replace` ¶	whether to change all unspecified values to `None` (`device["enabled"]=True` by default). TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`dict[str, Any]`	Dictionary with the updated fields and original unmodified fields of the device

Update Behavior

This function updates a field if it has been set, otherwise it inserts a new value. Not passing a value for an existing field will not clear the value from that field. For that you must choose replace=True. If replace=True name can not be None or an empty string. Even with replace=True geo will not be set to None.

Available columns in the device table

column_name	Description
id	Internal id of device
name	Name of device
device_type	Type of device (DFR/Relay/etc)
description	User readable description
geo	Coordinates, a dict {"latitude":float,"logitude":float}
elevation	Elevation of the device, float
alt_id	Alternative id, int
alt_name	Alternative name
enabled	Whether the device is expected to be sending data, bool default: True
owner	Who owns the device
protocol	What protocol the device is using to send data
model_name	The model name of the device
vendor	The company that creates/sells the device

update_unit ¶

update_unit(unit_dict: dict[str, Any]) -> dict[str, Any]

Updates a unit_dict with matching id using fields from the passed dictionary.

Modify the unit where the unit_dict['id'] is the id number of the unit you want to update.

Update Behavior

You are not requried to include fields that you want to keep the same. Although including them will not cause issues.

PARAMETER	DESCRIPTION
`unit_dict` ¶	Dictionary with fields corresponding to the values in the database you want to update TYPE: `dict[str, Any]`

RETURNS	DESCRIPTION
`dict[str, Any]`	Dictionary with the updated fields and original unmodified fields of the unit

Examples:

>>> original_unit = client.get_unit(6)
>>> print(original_unit)
{'id': 6,
'name': 'volts',
'symbol': 'V',
'canonical': 'volts',
'base': 1.0,
'source_name': ['VPHM', 'voltage', 'VOLTS', 'VLTGE']}
>>> updated_unit = {"id":6, "name":"volt"}
>>> client.update_unit(updated_unit)
{'id': 6,
 'name': 'volt',
 'symbol': 'V',
 'canonical': 'volts',
 'base': 1.0,
 'source_name': ['VPHM', 'voltage', 'VOLTS', 'VLTGE']}

pingthings.timeseries.client.ClientEventLoop ¶

ClientEventLoop()

The object responsible for task running.

This leverages the asyncio event loop.

Are you sure you need to manually use this?

This object is automatically created and leveraged whenever you use the standard connect or async_connect

METHOD	DESCRIPTION
`run_coroutine_threadsafe`	A wrapper to run coroutines threadsafe.

Functions¶

run_coroutine_threadsafe ¶

run_coroutine_threadsafe(
    coro: Coroutine[Any, Any, CO_RESULT_TYPE]
) -> Future[CO_RESULT_TYPE]

A wrapper to run coroutines threadsafe.

Client

pingthings.timeseries.client.Client ¶

loop ¶

client ¶

Attributes¶

concurrency_limit property writable ¶

Functions¶

connect staticmethod ¶

profile ¶

endpoint ¶

apikey ¶

concurrency_limit ¶

create ¶

uuid ¶

collection ¶

tags ¶

annotations ¶

create_device ¶

device ¶

create_unit ¶

name ¶

symbol ¶

base ¶

canonical ¶

source_name ¶

delete_device ¶

device_id ¶

delete_unit ¶

unit_id ¶

get_async_client ¶

get_collection_properties ¶

collection ¶

get_device ¶

device_id ¶

get_event_loop ¶

get_unit ¶

unit_id ¶

info ¶

list_collections ¶

prefix ¶

list_devices ¶

list_units ¶

set_collection_retention ¶

collection ¶

override_per_stream ¶

remove_older_than ¶

sql_query ¶

query ¶

params ¶

stream_from_uuid ¶

uuid ¶

streams_in_collection ¶

collection ¶

is_collection_prefix ¶

tags ¶

annotations ¶

streamset_from_uuids ¶

uuids ¶

fetch_metadata ¶

update_device ¶

device ¶

replace ¶

update_unit ¶

unit_dict ¶

pingthings.timeseries.client.ClientEventLoop ¶

Functions¶

run_coroutine_threadsafe ¶

`loop` ¶

`client` ¶

concurrency_limit `property` `writable` ¶

connect `staticmethod` ¶

`profile` ¶

`endpoint` ¶

`apikey` ¶

`concurrency_limit` ¶

`uuid` ¶

`collection` ¶

`tags` ¶

`annotations` ¶

`device` ¶

`name` ¶

`symbol` ¶

`base` ¶

`canonical` ¶

`source_name` ¶

`device_id` ¶

`unit_id` ¶

`collection` ¶

`device_id` ¶

`unit_id` ¶

`prefix` ¶

`collection` ¶

`override_per_stream` ¶

`remove_older_than` ¶

`query` ¶

`params` ¶

`uuid` ¶

`collection` ¶

`is_collection_prefix` ¶

`tags` ¶

`annotations` ¶

`uuids` ¶

`fetch_metadata` ¶

`device` ¶

`replace` ¶

`unit_dict` ¶