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---
title: Run Salesforce Connector using the CLI
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slug: /connectors/database/salesforce/cli
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---
# Run Salesforce using the metadata CLI
{% multiTablesWrapper %}
| Feature | Status |
| :----------------- | :--------------------------- |
| Stage | PROD |
| Metadata | {% icon iconName="check" /%} |
| Query Usage | {% icon iconName="cross" /%} |
| Data Profiler | {% icon iconName="check" /%} |
| Data Quality | {% icon iconName="check" /%} |
| Lineage | {% icon iconName="cross" /%} |
| DBT | {% icon iconName="cross" /%} |
| Supported Versions | -- |
| Feature | Status |
| :----------- | :--------------------------- |
| Lineage | {% icon iconName="cross" /%} |
| Table-level | {% icon iconName="cross" /%} |
| Column-level | {% icon iconName="cross" /%} |
{% /multiTablesWrapper %}
In this section, we provide guides and references to use the Salesforce connector.
Configure and schedule Salesforce metadata and profiler workflows from the OpenMetadata UI:
- [Requirements ](#requirements )
- [Metadata Ingestion ](#metadata-ingestion )
## Requirements
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{%/inlineCallout%}
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.
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Following are the permissions you will require to fetch the metadata from Salesforce.
**API Access**: You must have the API Enabled permission in your Salesforce organization.
**Object Permissions**: You must have read access to the Salesforce objects that you want to ingest.
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### Python Requirements
To run the Salesforce ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[salesforce]"
```
## Metadata Ingestion
All connectors are defined as JSON Schemas.
[Here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/salesforceConnection.json )
you can find the structure to create a connection to Salesforce.
In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.
The workflow is modeled around the following
[JSON Schema ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json )
### 1. Define the YAML Config
This is a sample config for Salesforce:
{% codePreview %}
{% codeInfoContainer %}
#### Source Configuration - Service Connection
{% codeInfo srNumber=1 %}
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**username**: Username to connect to the Salesforce. This user should have the access as defined in requirements.
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{% /codeInfo %}
{% codeInfo srNumber=2 %}
**password**: Password to connect to Salesforce.
{% /codeInfo %}
{% codeInfo srNumber=4 %}
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**securityToken**: Salesforce Security Token is required to access the metadata through APIs. You can checkout [this doc ](https://help.salesforce.com/s/articleView?id=sf.user_security_token.htm&type=5 ) on how to get the security token.
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{% /codeInfo %}
{% codeInfo srNumber=5 %}
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**sobjectName**: Specify the Salesforce Object Name in case you want to ingest a specific object. If left blank, we will ingest all the Objects.
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{% /codeInfo %}
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{% codeInfo srNumber=6 %}
**salesforceApiVersion**: Follow the steps mentioned [here ](https://help.salesforce.com/s/articleView?id=000386929&type=1 ) to get the API version. Enter the numerical value in the field, For example `42.0` .
{% /codeInfo %}
{% codeInfo srNumber=7 %}
**salesforceDomain**: When connecting to Salesforce, you can specify the domain to use for accessing the platform. The common domains include `login` and `test` , and you can also utilize Salesforce My Domain.
By default, the domain `login` is used for accessing Salesforce.
{% /codeInfo %}
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#### Source Configuration - Source Config
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{% codeInfo srNumber=10 %}
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The `sourceConfig` is defined [here ](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceMetadataPipeline.json ):
**markDeletedTables**: To flag tables as soft-deleted if they are not present anymore in the source system.
**includeTables**: true or false, to ingest table data. Default is true.
**includeViews**: true or false, to ingest views definitions.
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**databaseFilterPattern**, **schemaFilterPattern** , **tableFilternPattern** : Note that the filter supports regex as include or exclude. You can find examples [here ](/connectors/ingestion/workflows/metadata/filter-patterns/database )
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{% /codeInfo %}
#### Sink Configuration
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{% codeInfo srNumber=11 %}
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To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest` .
{% /codeInfo %}
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{% partial file="workflow-config.md" /%}
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#### Advanced Configuration
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{% codeInfo srNumber=8 %}
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**Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to Athena during the connection. These details must be added as Key-Value pairs.
{% /codeInfo %}
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{% codeInfo srNumber=9 %}
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**Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to Athena during the connection. These details must be added as Key-Value pairs.
- In case you are using Single-Sign-On (SSO) for authentication, add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "sso_login_url"`
{% /codeInfo %}
{% /codeInfoContainer %}
{% codeBlock fileName="filename.yaml" %}
```yaml
source:
type: salesforce
serviceName: local_salesforce
serviceConnection:
config:
type: Salesforce
```
```yaml {% srNumber=1 %}
username: username
```
```yaml {% srNumber=2 %}
password: password
```
```yaml {% srNumber=4 %}
securityToken: securityToken
```
```yaml {% srNumber=5 %}
sobjectName: sobjectName
```
```yaml {% srNumber=6 %}
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salesforceApiVersion: 42.0
```
```yaml {% srNumber=7 %}
salesforceDomain: login
```
```yaml {% srNumber=8 %}
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# connectionOptions:
# key: value
```
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```yaml {% srNumber=9 %}
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# connectionArguments:
# key: value
```
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```yaml {% srNumber=10 %}
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sourceConfig:
config:
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type: DatabaseMetadata
markDeletedTables: true
includeTables: true
includeViews: true
# includeTags: true
# databaseFilterPattern:
# includes:
# - database1
# - database2
# excludes:
# - database3
# - database4
# schemaFilterPattern:
# includes:
# - schema1
# - schema2
# excludes:
# - schema3
# - schema4
# tableFilterPattern:
# includes:
# - users
# - type_test
# excludes:
# - table3
# - table4
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```
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```yaml {% srNumber=11 %}
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sink:
type: metadata-rest
config: {}
```
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{% partial file="workflow-config-yaml.md" /%}
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{% /codeBlock %}
{% /codePreview %}
### 2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
```bash
metadata ingest -c < path-to-yaml >
```
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
you will be able to extract metadata from different sources.
## Related
{% tilesContainer %}
{% tile
title="Ingest with Airflow"
description="Configure the ingestion using Airflow SDK"
link="/connectors/database/salesforce/airflow"
/ %}
{% /tilesContainer %}