salesforcer
{salesforcer} is an R package that connects to Salesforce Platform APIs using tidy principles. The package implements actions from the SOAP, REST, Bulk 1.0, Bulk 2.0, and Metadata APIs.
Package features include:
- OAuth 2.0 (Single Sign On) and Basic (Username-Password)
Authentication methods (
sf_auth()) - CRUD (Create, Retrieve, Update, Delete) methods for records using the SOAP, REST, and Bulk APIs
- Query records via the SOAP, REST, Bulk 1.0, and Bulk 2.0 APIs using
sf_query() - Manage and execute reports and dashboards with:
sf_list_reports(),sf_create_report(),sf_run_report(), and more
- Retrieve and modify metadata (Custom Objects, Fields, etc.) using
the Metadata API with:
sf_describe_objects(),sf_create_metadata(),sf_update_metadata(), and more
- Utilize backwards compatible functions for the {RForcecom} package,
such as:
rforcecom.login(),rforcecom.getObjectDescription(),rforcecom.query(),rforcecom.create()
- Basic utility calls (
sf_user_info(),sf_server_timestamp(),sf_list_objects()) - Functions to assist with master data management (MDM) or data
integrity of records by finding duplicates (
sf_find_duplicates(),sf_find_duplicates_by_id()), merging records (sf_merge()), and converting leads (sf_convert_lead()) - Recover (
sf_undelete()) or delete from the Recycle Bin (sf_empty_recycle_bin()) and list ids of records deleted (sf_get_deleted()) or updated (sf_get_updated()) within a specific timeframe - Passing API call control parameters such as, “All or None”, “Duplicate Rule”, “Assignment Rule” execution and many more!
Table of Contents
Installation
# install the current CRAN version (0.2.0)
install.packages("salesforcer")
# or get the development version on GitHub
# install.packages("devtools")
devtools::install_github("StevenMMortimer/salesforcer")If you encounter an issue while using this package, please file a minimal reproducible example on GitHub.
Vignettes
The README below outlines the basic package functionality. For more
information please feel free to browse the pkgdown site at
https://StevenMMortimer.github.io/salesforcer which contains the
following vignettes:
- Getting Started
- Supported Queries
- Working with Bulk APIs
- Working with Reports
- Working with Attachments
- Working with Metadata
- Passing Control Args
- Transitioning from RForcecom
Usage
Authenticate
First, load the {salesforcer} package and login. There are two ways to authenticate:
- OAuth 2.0
- Basic Username-Password
It is recommended to use OAuth 2.0 so that passwords do not have to be
shared or embedded within scripts. User credentials will be stored in
locally cached file entitled “.httr-oauth-salesforcer” in the current
working directory. Also, note that if you use OAuth 2.0 authentication
then the package will automatically refresh it so you will not have to
call sf_auth() during each session if you have a cached
“.httr-oauth-salesforcer” file in the working directory. The cache
file is named that way to not conflict with the “.httr-oauth” files
created by other packages.
library(dplyr, warn.conflicts = FALSE)
library(salesforcer)
# Using OAuth 2.0 authentication
sf_auth()
# Using Basic Username-Password authentication
sf_auth(username = "test@gmail.com",
password = "{PASSWORD_HERE}",
security_token = "{SECURITY_TOKEN_HERE}")After logging in with sf_auth(), you can check your connectivity by
looking at the information returned about the current user. It should be
information about you!
# pull down information of person logged in
# it's a simple easy call to get started
# and confirm a connection to the APIs
user_info <- sf_user_info()
sprintf("Organization Id: %s", user_info$organizationId)
#> [1] "Organization Id: 00D6A0000003dN3UAI"
sprintf("User Id: %s", user_info$userId)
#> [1] "User Id: 0056A000000MPRjQAO"Create
Salesforce has objects and those objects contain records. One default object is the “Contact” object. This example shows how to create two records in the Contact object.
n <- 2
new_contacts <- tibble(FirstName = rep("Test", n),
LastName = paste0("Contact-Create-", 1:n))
created_records <- sf_create(new_contacts, object_name = "Contact")
created_records
#> # A tibble: 2 x 2
#> id success
#> <chr> <lgl>
#> 1 0033s000013Y9dsAAC TRUE
#> 2 0033s000013Y9dtAAC TRUEQuery
Salesforce has proprietary form of SQL called SOQL (Salesforce Object Query Language). SOQL is a powerful tool that allows you to return the attributes of records on almost any object in Salesforce including Accounts, Contacts, Tasks, Opportunities, even Attachments! Below is an example where we grab the data we just created including Account object information for which the Contact record is associated with.
my_soql <- sprintf("SELECT Id,
Account.Name,
FirstName,
LastName
FROM Contact
WHERE Id in ('%s')",
paste0(created_records$id , collapse = "','"))
queried_records <- sf_query(my_soql)
queried_records
#> # A tibble: 2 x 3
#> Id FirstName LastName
#> <chr> <chr> <chr>
#> 1 0033s000013Y9dsAAC Test Contact-Create-1
#> 2 0033s000013Y9dtAAC Test Contact-Create-2You’ll notice that the "Account.Name" column does not appear in the
results. This is because the SOAP and REST APIs do not return any
Account information if it does not exist on the record and there is no
reliable way to extract and rebuild the empty columns based on the query
string. If there were Account information, an additional column titled
"Account.Name" would appear in the results. Note, that the Bulk 1.0
and Bulk 2.0 APIs will return "Account.Name" as a column of all NA
values for this query because they return results differently.
Update
After creating records you can update them using sf_update(). Updating
a record requires you to pass the Salesforce Id of the record.
Salesforce creates a unique 18-character identifier on each record and
uses that to know which record to attach the update information you
provide. Simply include a field or column in your update dataset called
“Id” and the information will be matched. Here is an example where we
update each of the records we created earlier with a new first name
called “TestTest”.
# Update some of those records
queried_records <- queried_records %>%
mutate(FirstName = "TestTest")
updated_records <- sf_update(queried_records, object_name = "Contact")
updated_records
#> # A tibble: 2 x 2
#> id success
#> <chr> <lgl>
#> 1 0033s000013Y9dsAAC TRUE
#> 2 0033s000013Y9dtAAC TRUEBulk Operations
For really large operations (inserts, updates, upserts, deletes, and
queries) Salesforce provides the
Bulk 1.0
and
Bulk 2.0
APIs. In order to use the Bulk APIs in {salesforcer} you can just add
api_type = "Bulk 1.0" or api_type = "Bulk 2.0" to your functions and
the operation will be executed using the Bulk APIs. It’s that simple.
The benefits of using the Bulk API for larger datasets is that the operation will reduce the number of individual API calls (organization usually have a limit on total calls) and batching the requests in bulk is usually quicker than running thousands of individuals calls when your data is large. Note: the Bulk 2.0 API does NOT guarantee the order of the data submitted is preserved in the output. This means that you must join on other data columns to match up the Ids that are returned in the output with the data you submitted. For this reason, Bulk 2.0 may not be a good solution for creating, updating, or upserting records where you need to keep track of the created Ids. The Bulk 2.0 API would be fine for deleting records where you only need to know which Ids were successfully deleted.
# create contacts using the Bulk API
n <- 2
new_contacts <- tibble(FirstName = rep("Test", n),
LastName = paste0("Contact-Create-", 1:n))
created_records <- sf_create(new_contacts, "Contact", api_type = "Bulk 1.0")
created_records
#> # A tibble: 2 x 4
#> Id Success Created Error
#> <chr> <lgl> <lgl> <lgl>
#> 1 0033s000013Y9dwAAC TRUE TRUE NA
#> 2 0033s000013Y9dxAAC TRUE TRUE NA
# query large recordsets using the Bulk API
my_soql <- sprintf("SELECT Id,
FirstName,
LastName
FROM Contact
WHERE Id in ('%s')",
paste0(created_records$Id , collapse = "','"))
queried_records <- sf_query(my_soql, "Contact", api_type = "Bulk 1.0")
queried_records
#> # A tibble: 2 x 3
#> Id FirstName LastName
#> <chr> <chr> <chr>
#> 1 0033s000013Y9dwAAC Test Contact-Create-1
#> 2 0033s000013Y9dxAAC Test Contact-Create-2
# delete these records using the Bulk 2.0 API
deleted_records <- sf_delete(queried_records$Id, "Contact", api_type = "Bulk 2.0")
deleted_records
#> # A tibble: 2 x 4
#> Id sf__Id sf__Created sf__Error
#> <chr> <chr> <lgl> <lgl>
#> 1 0033s000013Y9dwAAC 0033s000013Y9dwAAC FALSE NA
#> 2 0033s000013Y9dxAAC 0033s000013Y9dxAAC FALSE NAUsing the Metadata API
Salesforce is a very flexible platform in that it provides the Metadata
API
for users to create, read, update and delete their entire Salesforce
environment from objects to page layouts and more. This makes it very
easy to programmatically setup and teardown the Salesforce environment.
One common use case for the Metadata API is retrieving information about
an object (fields, permissions, etc.). You can use the
sf_read_metadata() function to return a list of objects and their
metadata. In the example below we retrieve the metadata for the Account
and Contact objects. Note that the metadata_type argument is
“CustomObject”. Standard Objects are an implementation of
CustomObjects, so they are returned using that metadata type.
read_obj_result <- sf_read_metadata(metadata_type='CustomObject',
object_names=c('Account', 'Contact'))
read_obj_result[[1]][c('fullName', 'label', 'sharingModel', 'enableHistory')]
#> $fullName
#> [1] "Account"
#>
#> $label
#> [1] "Account"
#>
#> $sharingModel
#> [1] "ReadWrite"
#>
#> $enableHistory
#> [1] "false"
first_two_fields_idx <- head(which(names(read_obj_result[[1]]) == 'fields'), 2)
# show the first two returned fields of the Account object
read_obj_result[[1]][first_two_fields_idx]
#> $fields
#> $fields$fullName
#> [1] "AccountNumber"
#>
#> $fields$trackFeedHistory
#> [1] "false"
#>
#>
#> $fields
#> $fields$fullName
#> [1] "AccountSource"
#>
#> $fields$trackFeedHistory
#> [1] "false"
#>
#> $fields$type
#> [1] "Picklist"The data is returned as a list because object definitions are highly
nested representations. You may notice that we are missing some really
specific details, such as, the picklist values of a field with type
“Picklist”. You can get that information using
sf_describe_object_fields(). Here is an example using
sf_describe_object_fields() where we get a tbl_df with one row for
each field on the Account object:
acct_fields <- sf_describe_object_fields('Account')
acct_fields %>% select(name, label, length, soapType, type)
#> # A tibble: 69 x 5
#> name label length soapType type
#> <chr> <chr> <chr> <chr> <chr>
#> 1 Id Account ID 18 tns:ID id
#> 2 IsDeleted Deleted 0 xsd:boolean boolean
#> 3 MasterRecordId Master Record ID 18 tns:ID reference
#> 4 Name Account Name 255 xsd:string string
#> 5 Type Account Type 40 xsd:string picklist
#> # … with 64 more rows
# show the picklist selection options for the Account Type field
acct_fields %>%
filter(label == "Account Type") %>%
.$picklistValues
#> [[1]]
#> # A tibble: 7 x 4
#> active defaultValue label value
#> <chr> <chr> <chr> <chr>
#> 1 true false Prospect Prospect
#> 2 true false Customer - Direct Customer - Direct
#> 3 true false Customer - Channel Customer - Channel
#> 4 true false Channel Partner / Reseller Channel Partner / Reseller
#> 5 true false Installation Partner Installation Partner
#> # … with 2 more rowsFuture
Future APIs to support (roughly in priority order):
- Connect (Chatter) REST API
- Analytics External Data API
- Analytics REST API
- Tooling API
- Actions API
- Streaming API
- Place Order API
- Industries API
- Data.com API
Credits
This application uses other open source software components. The authentication components are mostly verbatim copies of the routines established in the {googlesheets} package (https://github.com/jennybc/googlesheets). Methods are inspired by the {RForcecom} package (https://github.com/hiratake55/RForcecom). We acknowledge and are grateful to these developers for their contributions to open source.
More Information
Salesforce provides client libraries and examples in many programming
languages (Java, Python, Ruby, and PhP) but unfortunately R is not a
supported language. However, most all operations supported by the
Salesforce APIs are available via this package. This package makes
requests best formatted to match what the APIs require as input. This
articulation is not perfect and continued progress will be made to add
and improve functionality. For details on formatting, attributes, and
methods please refer to Salesforce’s
documentation
as they are explained better there. More information is also available
on the pkgdown site at
https://StevenMMortimer.github.io/salesforcer.
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Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.