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Get the guidedbt Core uses dedicated adapters for each data platform to facilitate communication. These adapters are Python modules that enable dbt Core to interact with databases, query engines, and other data platforms. Each adapter is specifically designed for a unique SQL-speaking technology.
pip install dbt-postgres
This code example demonstrates how to install the PostgreSQL adapter for dbt Core using pip, a package manager for Python. This is a necessary step before you can connect to dbt Core.
To connect to dbt Core, you need to install the adapter for your data platform, connect to dbt Core, and set up a profiles.yml file. This can be done using the command line (CLI).
dbt debug --config-dir
This code example shows how to check the location of the profiles.yml file using dbt debug command. The profiles.yml file is where you define your connection configurations to dbt Core.
SQL-speaking platforms are data platforms that dbt Core can communicate with. These platforms include warehouses, databases, lakes, and query engines. The adapters for these platforms are categorized as Verified, Trusted, or Community.
# No specific code example for this section
There is no specific code example for this section as it is more of a conceptual understanding rather than a practical application.
The profiles.yml file is where you define your connection configurations to dbt Core. It is a crucial component in the setup process to connect to dbt Core.
profiles:
target: dev
outputs:
dev:
type: postgres
host: localhost
user: [username]
pass: [password]
dbname: [database name]
schema: [schema name]
This code example shows a basic configuration of a profiles.yml file for a PostgreSQL database. You need to replace [username], [password], [database name], and [schema name] with your actual database details.
dbt Core supports a wide range of data platforms by using dedicated adapters for each platform. These adapters are Python modules that allow dbt Core to communicate with various SQL-speaking platforms such as warehouses, databases, lakes, and query engines.
# No specific code example for this section
There is no specific code example for this section as it is more of a conceptual understanding rather than a practical application.
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