Quick start for Soda Core and Soda Cloud

Use your command-line interface to connect Soda Core to a data source, create and examine the checks that surface “bad” data in a dataset, then run your first scan in a few minutes.

After you run your scan from the command-line, consider going further by signing up for a free trial account in Soda Cloud, the web application that offers data quality visualizations and much more.

Tutorial prerequisites
Install Soda Core
Connect Soda Core to a data source
Write a check and run a scan
Connect Soda Core to Soda Cloud (Optional)

Tutorial prerequisites

This tutorial references a MacOS development environment with a PostgreSQL data source.

Python 3.8 or greater
Pip 21.0 or greater
access details and credentials for a PostgreSQL database
a code editor such as Sublime or Visual Studio Code

Install Soda Core

Best practice dictates that you install the Soda Core CLI using a virtual environment. In your command-line interface, create a virtual environment in the .venv directory, then activate it and update the version of pip.
```
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
```
Execute the following command to install Soda Core in your virtual environment.
```
pip install soda-core-postgres
```

Validate the installation using the soda command. The command-line output is similar to the following.

Usage: soda [OPTIONS] COMMAND [ARGS]...
  Soda Core CLI version 3.0.bx
Options:
  --help  Show this message and exit.
Commands:
  scan    runs a scan
  update-dro  updates a distribution reference file

Connect Soda Core to a data source

There are several other install packages for Soda Core that correspond to different data sources. This tutorial references a MacOS development environment with a PostgreSQL data source.

In your command-line interface, create a Soda tutorial project directory in your local environment, then navigate to the directory.
```
mkdir soda_tutorial
cd soda_tutorial
```
Create a new file called confguration.yml.
Open the configuration.yml file in a code editor, then copy and paste the following connection details into the file. Replace the values for each of the fields with your own database-specific details, then save the file.

data_source my_database_name:
  type: postgres
  connection:
    host: soda-temp-demo
    port: '5432'
    username: sodademo
    password: ${POSTGRES_PASSWORD}
  database: postgres
  schema: public

Replace my_database_name with the name of your PostgreSQL database.
Note that connection: is a header, not a field.
All values are required.
Consider using system variables to securely store the values of your username and password. Refer to Configure Soda Core for details.

Write a check and run a scan

Using Finder or Terminal, create another file in the soda-tutorial directory called checks.yml. A Soda Check is a test that Soda Core performs when it scans a dataset in your data source. The checks.yml file stores the Soda Checks you write using the Soda Checks Language (SodaCL).
Open the checks.yml file in a code editor, then copy and paste the following Soda Check into the file. Replace the value for my_dataset with the name of a dataset in your data source.
This simple check validates that the dataset contains more than zero rows, which is to say, that it is not empty.
```
checks for my_dataset:
- row_count > 0 
```
Save the changes to the checks.yml file, then, in Terminal, use the following command to run a scan. As input, the command requires:
- the name of the data source to scan; replace the value for my_database_name with the name of your PostgreSQL database
- the filepath and name of the configuration.yml file
- the filepath and name of the checks.yml file
  
  Command:
```
soda scan -d my_database_name -c configuration.yml checks.yml
```
  Output:
```
Soda Core 3.0.0bx
Scan summary:
1/1 check PASSED: 
 my_dataset in my_database_name
 row_count > 0 [PASSED]
All is good. No failures. No warnings. No errors.
```
The CLI output indicates that the check passed, confirming that the dataset is not empty. (Optional) To witness an example of scan output with a failed check, open the checks.yml file and change the check to read: row_count < 5, then save the file.

(Optional) Run the same scan command to see a different scan results in the CLI.
Command:

soda scan -d my_database_name -c configuration.yml checks.yml

Output:

Soda Core 3.0.0bx
Scan summary:
1/1 check FAILED: 
 my_dataset in my_database_name
   row_count < 5 [FAILED]
     check_value: 1329
Oops! 1 failures. 0 warnings. 0 errors. 0 pass.

(Optional) To see more detail in the scan results output in the CLI, add the -V option to the scan command to return a verbose version of the output.

Command:

soda scan -d my_database_name -c configuration.yml -V checks.yml

Output:

Soda Core 3.0.0bx
Reading configuration file "/Users/username/.soda/configuration.yml"
Reading SodaCL file "checks.yml"
Scan execution starts
Query aws_postgres_retail.orders.aggregation[0]:
SELECT 
  COUNT(*) 
FROM orders
Scan summary:
1/1 query OK
  my_database_name.my_dataset.aggregation[0] [OK] 0:00:00.285771
1/1 check FAILED: 
 my_dataset in my_database_name
   row_count < 5 [FAILED]
     check_value: 1329
Oops! 1 failures. 0 warnings. 0 errors. 0 pass.

(Optional) If you like, adjust or add more checks to the checks.yml file to further explore the things that SodaCL can do.
To exit the virtual environment in your command-line interface, type deactivate then press enter.
OR
Continue to the next section to connect Soda Core to a Soda Cloud account.

Connect Soda Core to Soda Cloud

Though you can use Soda Core as a standalone CLI tool to monitor data quality, you may wish to connect to the Soda Cloud web application that vastly enriches the data quality monitoring experience.

Beyond increasing the observability of your data, Soda Cloud enables you to automatically detect anomalies, and view samples of the rows that failed a test during a scan. Integrate Soda Cloud with your Slack workspace to collaborate with your team on data monitoring.

Soda Core uses an API to connect to Soda Cloud. To use the API, you must generate API keys in your Soda Cloud account, then add them to the configuration YAML file. When it runs a scan, Soda Core pushes the test results to Soda Cloud.

If you have not already done so, create a Soda Cloud account at cloud.soda.io.

In a code editor, open your configuration.yml file, then add the soda_cloud syntax to the file, as in the example below.

data_source my_database_name:
  type: postgres
  connection:
 host: soda-temp-demo
 port: '5432'
 username: sodademo
 password: ${POSTGRES_PASSWORD}
  database: postgres
  schema: public
soda_cloud:
  host: cloud.soda.io
  api_key_id: 
  api_key_secret: 

Save the configuration.yml file.
In Soda Cloud, navigate to your avatar > Profile > API Keys, then click the plus icon to generate new API keys.
- Copy the API Key ID, then paste it into the configuration.yml file as the value for api_key_id.
- Copy the API Key Secret, then paste it into the configuration.yml file as the value for api_key_secret.
  You may wish to securely store the values for the API keys as system variables.
Save the changes to the configuration.yml file. Close the Create API Key dialog box in your Soda Cloud account.

From the command-line, in your soda_tutorial directory, use Soda Core to scan the datasets in your data source again.
Command:

soda scan -d my_database_name -c configuration.yml checks.yml

Output:

Soda Core 3.0.0bx
Scan summary:
1/1 check FAILED: 
 my_dataset in my_database_name
   row_count < 5 [FAILED]
     check_value: 1329
Oops! 1 failures. 0 warnings. 0 errors. 0 pass.
Sending results to Soda Cloud

Go to your Soda Cloud account in your browser and navigate to the Monitors dashboard. Review the results of your scan in Monitor Results.
Navigate to the Datasets dashboard, then click to select the name of your dataset to review statistics and metadata about the dataset.
Explore Soda Cloud!
- integrate your Slack workspace to receive notifications of failed checks and collaborate on data quality investigations
- set up alerts and notifications for the checks in your account (Monitors > Monitor Results > stacked dots > Edit Monitor)
- open and track data quality incidents and collaborate to resolve them with your team in Slack

To exit the virtual environment in your command-line interface, type deactivate then press enter.

Go further

Consider completing the Quick start for SodaCL.
Explore the built-in metrics and checks you can use with SodaCL.
Set up programmatic scans to automate data quality monitoring.
Need help? Join the Soda community on Slack.

Last modified on 01-Jul-22

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