pyclarify 0.3.5

Python SDK for reading and writing signals to Clarify.

PyClarify

Useful tutorials and documentation

• PyClarify SDK
• PyClarify documentation
• Clarify Developer documentation
• Basic tutorial on using Python with Clarify
• Clarify Forecast tutorial
• Pattern Recognition tutorial
• Google Cloud Hosting tutorial

Prerequisites

In order to start using the Python SDK, you need

• To know a bit of Python. For a refresher, see the Official Python tutorial.
• Python3 (>= 3.7) and pip.
• Credentials from a Clarify integration. See the introduction notebook for a complete introduction.

Install and import PyClarify

To install this package:

$ pip install pyclarify

import pyclarify

Interact with Clarify

PyClarify provides a fast and easy way to interact with Clarify using the APIClient and ClarifyClient class. This class takes as an argument the path of your credentials in string format, which should always be the first step when starting to interact with PyClarify.

The APIClient and ClarifyClient class can do the almost the same operations, but the ClarifyClient provides a more pythonic way.

For information about the Clarify Developer documentation click here.

Using Python with Clarify

Use colab to learn fast end easy how to interact with Clarify using Python. In this introduction tutorial you will learn all the basics to get you started.

Quickstart

Save signals

Example:

from pyclarify import ClarifyClient, SignalInfo

client = ClarifyClient("./clarify-credentials.json")

signal = SignalInfo(
   name = "Home temperature",
   description = "Temperature in the bedroom",
   labels = {"data-source": ["Raspberry Pi"], "location": ["Home"]}
)

response = client.save_signals(input_ids=["<INPUT_ID>"], signals=[signal], create_only=False)
print(response.json())

Insert data into a signal

Example:

from pyclarify import DataFrame, ClarifyClient

client = APIClient("./clarify-credentials.json")

date = ["2021-11-01T21:50:06Z",  "2021-11-02T21:50:06Z"]

data = DataFrame(
    series={"<INPUT_ID_1>": [1, None], "<INPUT_ID_2>": [None, 5]},
    times = date,
)

response = client.insert(data)
print(response.json())

Get metadata from signals and/or items

Example:

from pyclarify import ClarifyClient

client = ClarifyClient("./clarify-credentials.json")

response = client.select_signals(
                ids = ['<SIGNAL_ID>'],
                name = "Electricity",
                labels = {"city": "Trondheim"},
                limit = 10,
                skip = 0,
                include_items = False
)
print(response.json())

Publish signals

Example:

from pyclarify import ClarifyClient, Item

client = ClarifyClient("./clarify-credentials.json")

item = Item(
   name = "Home temperature",
   description = "Temperature in the bedroom",
   labels = {"data-source": ["Raspberry Pi"], "location": ["Home"]},
   visible=True
)
response = client.publish_signals(signal_ids=['<SIGNAL_ID>'], items=[item], create_only=False)
print(response.json())

Get Item data

Example:

from pyclarify import ClarifyClient

client = ClarifyClient("./clarify-credentials.json")

response = client.select_items_data(
    ids = ['<ITEM_ID>'],
    limit = 10,
    skip = 0,
    not_before = "2021-10-01T12:00:00Z",
    before = "2021-11-10T12:00:00Z",
    rollup = "P1DT"
)
print(response.json())

Get Item metadata

Example:

from pyclarify import ClarifyClient

client = ClarifyClient("./clarify-credentials.json")

response = client.select_items_metadata(
    ids = ['<ITEM_ID>'],
    name = "Electricity",
    labels = {"city": "Trondheim"},
    limit = 10,
    skip = 0
)
print(response.json())

Changelog

Wondering about upcoming or previous changes to the SDK? Take a look at the CHANGELOG.

Contributing

Want to contribute? Check out CONTRIBUTING.