# OHDSI code style for R

## Case

Examples:

• cohortData <- loadCohortData("myFolder")
• The SqlRender package

## Naming conventions

Function names typically start with a verb. Variable names are typically nouns. Do not encode the data type in the variable names. Also, everything is data, so no need to say that unless unavoidable.

Good

• The fitOutcomeModel function.
• The computeCovariateBalance function.
• The population argument.

• sampling as variable name (not a noun)
• namesVector, covariatesDf (encodes the data type)
• getResultData (everything is data)

## Spacing

Place spaces around all infix operators (=, +, -, <-, etc.). The same rule applies when using = in function calls. Always put a space after a comma, and never before (just like in regular English).

Good

average <- mean(feet / 12 + inches, na.rm = TRUE)

average<-mean(feet/12+inches,na.rm=TRUE)

There’s a small exception to this rule: :, :: and ::: don’t need spaces around them.

Good

x <- 1:10
base::get

x <- 1 : 10
base :: get

Place a space before left parentheses, except in a function call.

Good

if (debug) {
do(x)
}

plot(x, y)

if(debug){
do(x)
}

plot (x, y)

Extra spacing (i.e., more than one space in a row) is ok if it improves alignment of equal signs or assignments (<-).

Do not place spaces around code in parentheses or square brackets (unless there’s a comma, in which case see above).

Good

if (debug) {
do(x)
}

diamonds[5, ]

if ( debug ) {  # No spaces around debug
do(x)
}

x[1,]   # Needs a space after the comma
x[1 ,]  # Space goes after comma not beforeCurly braces

An opening curly brace should never go on its own line and should always be followed by a new line. A closing curly brace should always go on its own line, unless it’s followed by else.

## Indentation

Always indent the code inside curly braces. It’s ok to leave very short statements on the same line:

if (y < 0 && debug) {
message("Y is negative")
}

Strive to limit your code to 100 characters per line. This fits comfortably on a printed page with a reasonably sized font. If you find yourself running out of room, this is a good indication that you should encapsulate some of the work in a separate function.

When indenting your code, use tabs. Never use spaces or mix tabs and spaces.

Hint: In RStudio you can use ctrl-i to automatically indent the code for you.

## Assignment

Use <-, not =, for assignment.

Good

x <- 5

x = 5

## If-then-else

If-then-else clauses should always use curly brackets, even if there’s only one clause and it’s one statement.

Good

if (a == b) {
doSomething()
}

if (a == b) doSomething()

## Use named arguments

When calling a function that has more than one argument, make sure to refer to each argument by name instead of relying on the order of arguments.

Good

translateSql(sql = "COMMIT", targetDialect = "PDW")

translateSql("COMMIT", "PDW")

## Commenting guidelines

Comment your code only where the intent is not immediately obvious. Each line of a comment should begin with the comment symbol and a single space: #. Comments should explain the why, not the what.

Use commented lines of - to break up your file into easily readable chunks, for example:

## Load data ---------------------------

## Plot data ---------------------------
plot(x)

## Curly brackets and new line

Opening curly brackets should precede a new line. A closing curly bracket should be followed by a new line except when it is followed by else or a closing parenthesis.

Good

if (a == b) {
doSomething()
} else {
doSomethingElse()
}

if (a == b)
{
doSomething()
}
else
{
doSomethingElse()
}

## Dplyr joins and merges

Dplyr joins and merge statements should always have a ‘by’ argument.

Good

foo %>%
inner_join(bar, by = "covariateId")

foo %>%
inner_join(bar)

# OHDSI code style for SQL

The OHDSI code style for SQL is heavily inspired by the Poor Man’s T-SQL Formatter, which is available as a NotePad++ plugin. The only difference with the default settings is that in OHDSI, commas are trailing. You can automatically format your SQL correctly by using the Poor Man’s T-SQL Formatter Online Tool (but don’t forget to set Trailing Commas).

## Case

Because several database platforms are case-insensitive and tend to convert table and field names to either uppercase (e.g. Oracle) or lowercase (e.g. PostgreSQL), we use snake_case. All names should be in lowercase. Reserved words should be in upper case.

Good

SELECT COUNT(*) AS person_count FROM person

SELECT COUNT(*) AS personCount FROM person

SELECT COUNT(*) AS Person_Count FROM person

SELECT COUNT(*) AS PERSON_COUNT FROM person

select count(*) as person_count from person

## Commas

Commas should be trailing.

Good

SELECT COUNT(*) AS person_count,
condition_concept_id,
condition_type_concept_id
FROM condition_era
GROUP BY condition_concept_id,
condition_type_concept_id

SELECT COUNT(*) AS person_count
,condition_concept_id
,condition_type_concept_id
FROM condition_era
GROUP BY condition_concept_id
,condition_type_concept_id

## Indentation and new lines

Indentation is done using tabs. Field definitions are followed by a new line.

Good

SELECT COUNT(*) AS person_count,
condition_type_concept_id
FROM (
SELECT *
FROM condition_era
WHERE condition_concept_id = 123
) tmp
GROUP BY condition_type_concept_id;

SELECT COUNT(*) AS person_count, condition_type_concept_id
FROM (SELECT * FROM condition_era WHERE condition_concept_id = 123) tmp
GROUP BY condition_type_concept_id;

# Interfacing between R and SQL

In R we use camel case, and in SQL we use snake case. Therefore, on the interface between the two languages we must convert from one convention to the other. To facilitate this, the OHDSI SqlRender and DatabaseConnector packages provide various features.

In general, in R we can convert from one case to another using the camelCaseToSnakeCase and snakeCaseToCamelcase functions in the SqlRender package:

data <- data.frame(cohortId = 1,
cohortName = "test")

colnames(data) <- camelCaseToSnakeCase(colnames(data))
colnames(data)
# [1] "cohort_id" "cohort name"

colnames(data) <- snakeCaseToCamelcase(colnames(data))
colnames(data)
# [1] "cohortId" "cohortName"

When downloading data, a shortcut is to use the snakeCaseToCamelcase argument of the querySql function in the DatabaseConnector package:

sql <- "SELECT cohort_definition_id, subject_id  FROM cdm.cohort;"
cohort <- querySql(connection = connection,
sql = sql,
snakeCaseToCamelcase = TRUE)

Where cohort will be a data frame with columns cohortDefinitionId and subjectId.

## When inserting data in the database

When uploading data, a shortcut is to use the camelCaseToSnakeCase argument of the insertTable in the DatabaseConnector package:

dataToInsert <- data.frame(cohortId = 1,
cohortName = "test")

insertTable(connection = connection,
tableName = "my_table",
data = dataToInsert,
camelCaseToSnakeCase = TRUE)

Where the table called my_table will have columns named cohort_id and cohort_name.