Demyst Python Cheat Sheet
For a quick reference to our Python API, check out our cheat sheet that contains the concise set of methods to enable access to external data.
Authorization
Username and Password
analytics_up = Analytics(username="EMAIL ADDRESS",
password="DEMYST PASSWORD")
API Key
analytics_key = Analytics(key="REPLACE W/ API KEY")
Single Sign On/SAML
analytics_sso = Analytics(username="EMAIL ADDRESS",
jwt="REPLACE W/ TOKEN")
Inputs
Validate Input Dataframe
analytics.validate(input_dataframe)
Validate Input Dataframe Against Product Input
analytics.validate(input_dataframe,
providers=["PRODUCT NAME"])
Search
Product search using input
analytics.search(input_dataframe)
Product search w/ exact match for inputs
analytics.search(input_dataframe,
strict=True)
Response Attribute Search
analytics.attribute_search("ATTRIBUTE_NAME")
Catalog
List all data products and details
analytics.products()
See catalog for a product
analytics.product_catalog(["PRODUCT/S NAME"])
See catalog for all products
analytics.product_catalog(all_products=TRUE)
View Inputs of a product
analytics.product_inputs(["PRODUCT/S NAME"])
View Outputs of a product
analytics.product_outputs(["PRODUCT/S NAME"])
Enrich
Get enriched data for your input dataframe
analytics.enrich_and_download(["PRODUCT/S NAME"],
input_dataframe)
Run enrichment asynchronously
analytics.enrich(["PRODUCT/S NAME"],
input_dataframe)
Download the enrichment result from enrich()
analytics.enrich_download(enrich_job_ id)
Check if enrichment is complete
analytics.enrich_status(enrich_job_id)
Wait for enrichment completion
analytics.enrich_wait(enrich_job_id)
Cost of an enrichment
analytics.enrich_credits(["PRODUCT/S NAME"],
input_dataframe)
Stats
Statistics on enriched data
from demyst.analytics.report import *
report(input_dataframe, enrich_result)
Statistics on the product and its attributes
analytics.product_stats(["PRODUCT/S NAME"])