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Client

pingthings.timeseries.client.Client

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.

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.

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: Optional[dict[str, str]] = None,
    annotations: Optional[dict[str, str]] = None,
) -> Stream

Create a new stream.

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: Optional[dict[str, str]] DEFAULT: None

annotations

Annotations for the stream.

TYPE: Optional[dict[str, str]] DEFAULT: None

RETURNS DESCRIPTION
Stream

The newly created stream.

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: 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.

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.