Quartic SDK documentation

Quartic SDK is Quartic.ai’s external software development kit (SDK) which allows users to use the assets, tags, and other intelligence of the Quartic AI Platform externally. Using the Quartic SDK, third party developers can build custom applications. Quartic SDK supports two kinds of authentication: Basic Authentication and OAuth2.0. In Basic Authentication, the user must pass the parameters of username and password; and in OAuth2.0, the client token.

Contents:

Installation

Install using pip:

pip install quartic-sdk

…or follow the following steps to install it from the source:

git clone https://github.com/Quarticai/QuarticSDK/
python setup.py install

Example

Here’s an example on how the Quartic SDK can be used:

GraphQLClient

# Assuming that the Quartic.ai server is hosted at `https://test.quartic.ai/`,
# with the login credentials as username and password is "testuser" and `testpassword respectively,
# then use GraphqlClient in the following format.

from quartic_sdk import GraphqlClient

client = GraphqlClient(url='https://test.quartic.ai/', username='testuser', password='testpassword')

# Executing Query by:

query='''
query MyQuery {
  Site {
    id
    name
  }
}
'''

result = client.execute_query(query=query)

# To execute query asynchronously use the function below.

# You should see the following result:

{'data': {'Site': [{'id': '1', 'name': 'quartic'}, {'id': '8', 'name': 'ABC site 1'}, {'id': '12', 'name': 'XYC 123'}]}

async def execute_graphql_query():
    query='''
        query MyQuery {
          Site {
            id
            name
          }
        }
        '''
    resp = await client.execute_async_query(query=query)
    return resp

# Note: The above function will return a coroutine object.

# Example to upload a file.

query = '''
    mutation($file: Upload!,$edge_connector: Int!,$date_format: DateTime!) {
        uploadTelemetryCsv(
            file: $file,
            fileName: "123",
            edgeConnector: $edge_connector,
            dateFormat: $date_format
            )
            {
            taskId
            status
        }
    }
'''


variables = {
    'file': open('<path/to/file>', 'rb'),
    'edge_connector': 'edgeConnector Id',
    'date_format': 'DatTime format'
}

response = client.execute_query(query=query, variables=variables)

Getting the assets, tags, batches from the server

# Assuming that the Quartic.ai server is hosted at `https://test.quartic.ai/`,
# with the login credentials as username and password is "testuser" and `testpassword respectively,
# then use APIClient in the following format.

from quartic_sdk import APIClient

client = APIClient("https://test.quartic.ai", username="username", password="password")
user_assets = client.assets() # Get the list of all assets that the user has access to

asset = user_assets.get("name","Test Asset") # Get a specific asset with the name "Test Asset"
asset_tags = asset.get_tags() # Gets the list of all tags
asset_data = asset.data(start_time=1000000, stop_time=2000000) # Get the data of the asset for the given interval between start_time and stop_time. This returns an iterator, which can be iterated to get all the data points present.
print(asset_data[0]) # Returns the data present at the 0th index