Function parity for R and Python

This page is a translation guide for users interested in the operational parity between the R and Python versions of vetiver. Vetiver aims to provide users with a similar experience in each language. For a deeper understanding of each implementation, please refer to the R function reference or Python function reference.

Function	R	Python
Create a vetiver object for deployment of a trained model	`vetiver_model()` `new_vetiver_model()`	`VetiverModel()`
Read and write a trained model to a board of models	`vetiver_pin_write()` `vetiver_pin_read()`	`vetiver_pin_write()` `vetiver_pin_read()`
Create an API to predict with a deployable vetiver_model() object	`vetiver_api()` `vetiver_pr_post()` `vetiver_pr_docs()`	`VetiverAPI()` `VetiverAPI.vetiver_post()`
Write a deployable API file for a vetiver model	`vetiver_write_plumber()`	`vetiver_write_app()`
Deploy a vetiver model API to RStudio Connect	`vetiver_deploy_rsconnect()`
Create a model API endpoint object for prediction	`vetiver_endpoint()`	`vetiver_endpoint()`
Post new data to a deployed model API endpoint and return predictions	`predict(<vetiver_endpoint>)`	`VetiverAPI.predict()`
Fully attach or load packages for making model predictions	`attach_pkgs()` `load_pkgs()`	`load_pkgs()`
Model handler functions for API endpoint	`handler_startup()` `handler_predict()`	`VetiverModel.translator.handler_startup()` `VetiverModel.translator.handler_predict()`
Identify data types for each column in an input data prototype	`map_request_body()`
Model constructor methods	`vetiver_create_description()` `vetiver_prepare_model()`	`VetiverModel.translator.create_description()` `VetiverModel.model()`
Metadata constructors for vetiver model object	`vetiver_meta()` `vetiver_create_meta()`	`vetiver_meta() vetiver_create_meta()`
Create a vetiver input data prototype	`vetiver_ptype()` `vetiver_create_ptype()`	`VetiverModel.ptype()` `_vetiver_create_ptype()`
Convert new data at prediction time using input data prototype	`vetiver_type_convert()`