# Benchmarking the CodelistGenerator R package

To check the performance of the CodelistGenerator package, we can use the benchmarkCodelistGenerator(). This function generates some hypothetical study codelists using various settings and times to check how long these analyses take.

We can start for example by benchmarking our mock data, which uses duckdb.

    library(DBI)
    library(duckdb)
    library(dplyr)
    library(CDMConnector)
    library(CodelistGenerator)
    library(visOmopResults)

    # Connect to the database and create the cdm object
    con <- dbConnect(duckdb(),
                          eunomiaDir("synpuf-1k", "5.3"))
    cdm <- cdmFromCon(con = con,
                      cdmName = "Eunomia Synpuf",
                      cdmSchema   = "main",
                      writeSchema = "main",
                      achillesSchema = "main")

    timings <- benchmarkCodelistGenerator(cdm)

    visOmopTable(timings,
                 hide = c("variable_name", "variable_level", "strata_name", "strata_level"),
                 groupColumn = "task")

Data source | Dbms | N person | N concepts | Estimate name | Estimate value
--- | --- | --- | --- | --- | ---
Getting drug ingredient codes (acetaminophen, codeine, adalimumab)
Eunomia Synpuf | duckdb | 1,000 | 6,224,227 | time_taken_minutes | 0.01
Getting atc codes (atc 1st level, 1 name of interest)
Eunomia Synpuf | duckdb | 1,000 | 6,224,227 | time_taken_minutes | 0.02
Getting candidate codes for dementia, excluding `child`, within all domains, and all options set to true
Eunomia Synpuf | duckdb | 1,000 | 6,224,227 | time_taken_minutes | 0.04