Automagic REST is a code generator which builds a full Django app as a Django REST Framework read-only environment for a set of tables in a PostgreSQL database.
This is very much for a specific niche, but we have found it quite powerful for building a RESTful API on top of datasets we receive from other sources through introspection of PostgreSQL's information_schema.
To get started, pip install automagic-rest and add automagic_rest to your INSTALLED_APPS setting in Django.
Setting up a secondary database in Django is recommended. For the following examples, we'll set up one called my_pg_data with the user my_pg_user:
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql',
'NAME': 'pg_web_db',
'USER': 'web_user',
'PASSWORD': '',
'HOST': 'pg-web.domain.com',
},
'my_pg_data': {
'ENGINE': 'django.db.backends.postgresql',
'NAME': 'pg_data_db',
'USER': 'my_pg_user',
'PASSWORD': '',
'HOST': 'pg-data.domain.com',
},
}By default, Automagic REST will create a directory called data_path at the root of your Django project, where manage.py lives. The follow options can be passed to the command:
--database(default:my_pg_data): the name of the Django database as defined in theDATABASESsetting.--owner(default:my_pg_user): the name of the PostgreSQL user which owns the schemata to be processed. This will normally be the same as theUSERin theDATABASESsetting for the database above.--path(default:data_path): the path to write the models and serializers to. This path will be completely deleted and rewritten whenever the command is run, so be careful!
Example: python manage.py build_data_models --database=my_data --owner=my_user --path=my_data_path
Methods are provided which can be overridden to customize the endpoint with your own Django management command.
get_db (default: my_pg_data): the name of the PostgreSQL database in Django's settings that we will introspect to build the API.
get_owner (default: my_pg_user): the name of the PostgreSQL user that owns the schemata we will introspect.
get_allowed_schemata (default: None): if set, returns a list of schemata in the database to be built. If None, selects all schemata for the specific user.
get_extra_sql (default: ""): if set, appends the SQL returned by this method to
the information schema query. Useful for exclusions.
get_root_python_path (default: data_path): a Python path where you would like to write the models, serializers, and routes. IMPORTANT: this path will be wiped and re-written every time the build command is run. It should be a dedicated directory with nothing else in it.
get_view (default: automagic_rest.views.GenericViewSet): the view to use.
get_router (default: rest_framework.routers.DefaultRouter): the router to use.
get_max_digits_default (default: 100): the number of max_digits to provide for NUMERIC field types that are not explicitly set in PostgreSQL.
get_decimal_places_default (default: 25): the number of decimal_places to provide for NUMERIC field types that are not explicitly set in PostgreSQL.
sanitize_sql_identifier: this method takes a string, and sanitizes it for injections into SQL, allowing only alphanumerics and underscores.
metadata_sql: this method returns the SQL used to pull the metadata from PostgreSQL to build the endpoints.
To customize the build command, here is an example:
# my_app/home/management/commands/my_build_data_models.py
from automagic_rest.management.commands import build_data_models
class Command(build_data_models.Command):
"""
My specific overrides for DRF PG Builder command.
"""
def get_db(self, options):
"""
Returns our customized Django DB name.
"""
return "my_data"
def get_owner(self, options):
"""
Returns our customized schema owner.
"""
return "my_user"
def get_root_python_path(self, options):
"""
Returns our customized build path.
"""
return "my_data_path"
def get_view(self):
"""
Returns our customized view path.
"""
return "my_app.views.MyDataViewSet"
def get_allowed_schemata(self, options, cursor):
"""
Return a list of allowed schemata we want to create RESTful
endpoints for. If None, will create endpoints for all schemata
owned by the schema owner user.
"""
allowed_schemata = ['my_data', 'public_data']
return allowed_schemata
def get_extra_sql(self):
"""
Returns SQL to append to the information schema query.
In this example, we exclude any tables ending in "_old".
"""
return """
AND c.table_name NOT LIKE '%%_old'
"""The view has several methods and attributes which can be overridden as well.
index_sql: this attribute defines SQL to return the first column in each index for the current table for the Model. These will be used to dynamically make all indexed fields searchable and filterable.
get_serializer_class_name (default: rest_framework.serializers.ModelSerializer): the full path of the serializer class to use.
get_permission (default: None): returns a permission class to use for the endpoint. When left at the default of None, uses the default permission class set by Django REST Framework.
get_estimate_count_limit (default: 999_999): to prevent long-running SELECT COUNT(*) queries, the view estimates the number of rows in the table by examing the query plan. If greater than this number, it will estimate pagination counts for vastly improved speed.
To follow on the example above, here is an example of an overridden view, which sets the permission type and includes a mixin for naming Excel file downloads:
from rest_framework.permissions import IsAuthenticated
from drf_excel.mixins import XLSXFileMixin
class MyGenericViewSet(XLSXFileMixin, GenericViewSet):
"""
"""
"""
Override the defaults from DRF PG Builder.
"""
filename = 'my_export.xlsx'
def get_permission(self):
return IsAuthenticatedAfter running the build command, you should have a directory created that you defined as path (or overrode with get_root_python_path()) that contains models, serializers, and a urls.py file. Include the urls.py file with a route from your Django project, and you should be able to visit the Django REST Framework browsable API.
- Certain column types are not supported, such as
ts_vectorand others that don't map cleanly to a RESTful type.
This package is maintained by the staff of Wharton Research Data Services. We are thrilled that The Wharton School allows us a certain amount of time to contribute to open-source projects. We add features as they are necessary for our projects, and try to keep up with Issues and Pull Requests as best we can. Due to constraints of time (our full time jobs!), Feature Requests without a Pull Request may not be implemented, but we are always open to new ideas and grateful for contributions and our package users.