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  • Forest Admin
  • Getting started
    • How it works
    • Quick start
      • Flask
      • Django
    • Create your agent
    • Troubleshooting
    • Migrating legacy agents
      • Pre-requisites
      • Recommendations
      • Migration steps
      • Code transformations
        • API Charts
        • Live Queries
        • Smart Charts
        • Route overrides
        • Smart Actions
        • Smart Fields
        • Smart Relationships
        • Smart Segments
  • Data Sources
    • Getting Started
      • Collection selection
      • Naming conflicts
      • Query interface and Native Queries
        • Fields and projections
        • Filters
        • Aggregations
    • Provided data sources
      • SQLAlchemy
      • Django
        • Polymorphic relationships
    • Write your own
      • Translation strategy
        • Structure declaration
        • Capabilities declaration
        • Read implementation
        • Write implementation
        • Intra-data source Relationships
      • Contribute
  • Agent customization
    • Getting Started
    • Actions
      • Scope and context
      • Result builder
      • Static Forms
      • Widgets in Forms
      • Dynamic Forms
      • Form layout customization
      • Related data invalidation
    • Charts
      • Value
      • Objective
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      • Leaderboard
      • Time-based
    • Fields
      • Add fields
      • Move, rename and remove fields
      • Override binary field mode
      • Override writing behavior
      • Override filtering behavior
      • Override sorting behavior
      • Validation
    • Hooks
      • Collection hook
      • Collection override
    • Pagination
    • Plugins
      • Write your own
    • Relationships
      • To a single record
      • To multiple records
      • Computed foreign keys
      • Under the hood
    • Search
    • Segments
  • Frontend customization
    • Smart Charts
      • Create a table chart
      • Create a bar chart
      • Create a cohort chart
      • Create a density map
    • Smart Views
      • Create a Map view
      • Create a Calendar view
      • Create a Shipping view
      • Create a Gallery view
      • Create a custom tinder-like validation view
      • Create a custom moderation view
  • Deploying to production
    • Environments
      • Deploy on AWS
      • Deploy on Heroku
      • Deploy on GCP
      • Deploy on Ubuntu
    • Development workflow
    • Using branches
    • Deploying your changes
    • Forest Admin CLI commands
      • init
      • login
      • branch
      • switch
      • set-origin
      • push
      • environments:create
      • environments:reset
      • deploy
  • Under the hood
    • .forestadmin-schema.json
    • Data Model
      • Typing
      • Relationships
    • Security & Privacy
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  1. Data Sources
  2. Provided data sources

SQLAlchemy

This is the official documentation of the forestadmin-agent-django and forestadmin-agent-flask Python agents.

The SQLAlchemy data source allows importing collections from all models class that extends the class build with declarative_base or that inherit from sqlalchemy.orm.DeclarativeBase.

To make everything work as expected, you need to install the package sqlalchemy.

Note that:

  • SQLAlchemy relationships will be respected

from forestadmin.datasource_sqlalchemy.datasource import SqlAlchemyDatasource

from sqlalchemy.orm import DeclarativeBase
class Base(DeclarativeBase):
    pass
# or
from sqlalchemy.orm import declarative_base
Base = declarative_base()

agent.add_datasource(
    SqlAlchemyDatasource(
        Base,
        db_uri="postgres://user:pass@localhost:5432/myDatabase",
    )
)

the db_uri is mandatory only in the cases when the engine cannot be found in the base class.

engine = create_engine("postgres://user:pass@localhost:5432/myDatabase", echo=False)
Base = declarative_base(engine)
agent.add_datasource(SqlAlchemyDatasource(Base))

When using the package Flask-SQLAlchemy, the setup is a bit different. In most of the case, the db_uri is not needed

from forestadmin.datasource_sqlalchemy.datasource import SqlAlchemyDatasource
from flask_sqlalchemy import SQLAlchemy

db = SQLAlchemy()
class Address(db.Model):
    __tablename__ = "address"
    id = Column(Integer, primary_key=True)
    # ...

agent.add_datasource(SqlAlchemyDatasource(db))

Enable support of live queries

You can enable this feature by setting a connection name (works as an identifier) when creating your datasource. This connection name will be reflected on the UI when configuring a LiveQuery component, it should have a clear meaning for your Forest users.


agent.add_datasource(
    SqlAlchemyDatasource(
        Base, db_uri="postgres://user:pass@localhost:5432/mainDatabase", live_query_connection="main_database"
    ),
)
agent.add_datasource(
    SqlAlchemyDatasource(
        OtherBase, db_uri="postgres://user:pass@localhost:5432/secondaryDatabase", live_query_connection="secondary_database"
    ),
)

After this point you should see on ForestAdmin an input asking for the connection next to the live query text input.

PreviousProvided data sourcesNextDjango

Last updated 4 months ago

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By enabling this feature, users with the required permission level can create Live Query components (, and ), allowing them to create more sophisticated requests to your database, by leveraging the underlying query language, SQL in this case.

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