AIOconnect Impact API¶
List of Functions¶
Definition of Functions¶
- aioconnect.impact_api.create_DOT(token: str, DOT_name: str, DOT_baseline: float, DOT_description: Optional[str] = None, DOT_type_id: str = '6019fa2072b96c00133df326', METRIC_type_id: str = '5fb7bf2f8ce87f0012fcc8f3')¶
Create a new DOT in AIO Impact.
- Parameters
- tokenstr
Token which was returned from the user login.
- DOT_namestr
Name of the DOT.
- DOT_baselinefloat
Baseline value of the DOT.
- DOT_descriptionstr = DOT_name
Description of the DOT.
- DOT_type_idstr = “6019fa2072b96c00133df326”
ID of the DOT type.
- METRIC_type_idstr = “5fb7bf2f8ce87f0012fcc8f3”
ID of the METRIC type.
- Returns
- requests.Response
HTTP response.
Examples
>>> token = aioconnect.get_token( >>> email="firstname.lastname@aioneers.com", password="xxx", >>> ) >>> >>> res = aioconnect.create_DOT( >>> token=token, >>> DOT_name="TEST_DOT", >>> DOT_description="TEST_DOT description", >>> DOT_baseline=1234, >>> DOT_type_id="6019fa2072b96c00133df326", >>> METRIC_type_id="5fb7bf2f8ce87f0012fcc8f3", >>> )
- aioconnect.impact_api.create_bulk_DOT(token: str, dots_df: pandas.core.frame.DataFrame, DOT_type_id: str = '6019fa2072b96c00133df326', METRIC_type_id: str = '5fb7bf2f8ce87f0012fcc8f3')¶
Function to create DOTs from a data frame and additional key.
- Parameters
- tokenstr
Token which was returned from the user login.
- dots_dfPandas.DataFrame
Dataframe which contains the key in the same format as it would be in the CSV upload.
- DOT_type_idstr
ID of the DOT type.
- METRIC_type_idstr
ID of the METRIC type.
- Returns
- requests.Response
Returns the HTTP response.
Examples
>>> username, df_t = transform_string(arg_string = "UserDirectory=AZUREQLIK; UserId=sebastian.szilvas@aioneers.com;DOT_name=1045,1058,1110,1449,3114;DOT_description=4K Ultra HD_1045,4K Ultra HD_1110,4K Ultra HD_1449,4K Ultra HD_3114,TVs_1000_1058;DOT_baseline=10846.75202,210810.99078,23874.0138,77647.14595363676,78107.53207446463") >>> mytoken = get_token() >>> res = create_bulk_DOT( >>> token = mytoken, >>> dots_df = df_t, >>> DOT_type_id = "6019fa2072b96c00133df326", >>> METRIC_type_id = "5fb7bf2f8ce87f0012fcc8f3", >>> )
- aioconnect.impact_api.delete_DOT_wID(token: str, DOT_id: str)¶
Function to delete a DOT.
- Parameters
- tokenstr
Token which was returned from the user login.
- DOT_idstr
ID of the DOT.
- Returns
- requests.Response
Returns the HTTP response.
Examples
>>> token = aioconnect.get_token( >>> email="firstname.lastname@aioneers.com", password="xxx", >>> ) >>> res = delete_DOT_wID( >>> token = token, >>> DOT_id = "606b54d1c8153d00193838bd", >>> )
- aioconnect.impact_api.get_list(token: str, url: str = 'https://dev-api.aioneers.tech/v1/', object: str = 'dotTypes', key: str = '_id') → list¶
Get List of values for a key of an object of the API.
- Parameters
- tokenstr
Token which was returned from the user login.
- urlstr = “https://dev-api.aioneers.tech/v1/”
Url of the API.
- objectstr = “dotTypes”
Object to be extracted from the API.
- keystr = “_id”
Key of the DOT.
- Returns
- list
Values for the provided key of the object.
- Raises
- ValueError
In case there was an object type given which does not exist.
- aioconnect.impact_api.get_object(token: str, url: str = 'https://dev-api.aioneers.tech/v1/', object: str = 'dotTypes') → list¶
Get JSON object.
- Parameters
- tokenstr
Token which was returned from the user login.
- urlstr = “https://dev-api.aioneers.tech/v1/”
Url of the API.
- objectstr = “dotTypes”
Object to be extracted from the API.
- Returns
- list
List of JSON objects.
- Raises
- ValueError
Raises ValueError when the input is not correct.
- aioconnect.impact_api.get_token(email: str, password: str)¶
Log into AIO Impact and get a token.
- Parameters
- emailstr
Email address of the user account.
- passwordstr
Password of the user account.
- Returns
- str
Bearer token.
Examples
>>> aioconnect.get_token( >>> email="firstname.lastname@aioneers.com", password="xxx", >>> )
- aioconnect.impact_api.transform_string(arg_string: str) → pandas.core.frame.DataFrame¶
Transform the string input from Qlik Sense and extract the relevant key.
- Parameters
- arg_stringstr
Input string sent from Qlik Sense.
- Returns
- str
The username, extracted from the string.
- Pandas.DataFrame
A dataframe containing the key in a structured format.
Examples
>>> input_from_qlik = "UserDirectory=AZUREQLIK; UserId=sebastian.szilvas@aioneers.com;DOT_name=1045,1058,1110,1449,3114;DOT_description=4K Ultra HD_1045,4K Ultra HD_1110,4K Ultra HD_1449,4K Ultra HD_3114,TVs_1000_1058;DOT_baseline=10846.75202,210810.99078,23874.0138,77647.14595363676,78107.53207446463" >>> (username, dots_df) = transform_string(arg_string=input_from_qlik)
- aioconnect.impact_api.upsert_DOT(token: str, dataframe: pandas.core.frame.DataFrame) → list¶
Create a new DOT in AIO Impact or update it if the DOT is already existing.
- Parameters
- tokenstr
Token which was returned from the user login.
- dataframePandas.DataFrame
Dataframe containing DOT details.
- Returns
- requests.Response
HTTP response.
Examples
>>> token = aioconnect.get_token( >>> email="firstname.lastname@aioneers.com", password="xxx", >>> ) >>> res = aioconnect.upsert_DOT( >>> token=token, >>> dataframe = df >>> )