Django app for building dashboards using raw SQL queries
Project description
django-sql-dashboard
Django app for building dashboards using raw SQL queries
Brings a useful subset of Datasette to Django.
Currently only works with PostgreSQL.
This is very early alpha. You should not yet trust this code, especially with regards to security. Do not run this in production (yet)!
Screenshot
Installation
Install this library using pip
:
$ pip install django-sql-dashboard
Usage
Add "django_sql_dashboard"
to your INSTALLED_APPS
in settings.py
.
Define a "dashboard"
database alias in settings.py
. It should look something like this:
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql_psycopg2",
"NAME": "mydb",
},
"dashboard": {
"ENGINE": "django.db.backends.postgresql_psycopg2",
"NAME": "mydb",
"OPTIONS": {"options": "-c default_transaction_read_only=on -c statement_timeout=100"},
},
}
Even better: create a new PostgreSQL role that is limited to read-only SELECT access to a list of tables, following these instructions.
Add the following to your urls.py
:
from django.urls import path, inclued
import django_sql_dashboard
urlpatterns = [
# ...
path("dashboard/", include(django_sql_dashboard.urls)),
]
Now visit /dashboard/
as a staff user to start trying out the dashboard.
SQL parameters
If your SQL query contains %(name)s
parameters, django-sql-dashboard
will convert those into form fields on the page and allow users to submit values for them. These will be correctly quoted and escaped in the SQL query.
Given the following SQL query:
select * from blog_entry where slug = %(slug)s
A form field called slug
will be displayed, and the user will be able to use that to search for blog entries with that given slug.
Here's a more advanced example:
select * from location
where state_id = cast(%(state_id)s as integer)
and name ilike '%%' || %(search)s || '%%';
Here a form will be displayed with state_id
and search
fields.
The values provided by the user will always be treated like strings - so in this example the state_id
is cast to integer in order to be matched with an integer column.
Any %
characters - for example in the ilike
query above - need to be escaped by providing them twice: %%
.
Widgets
SQL queries default to displaying as a table. Other forms of display - called widgets - are also available, and are selected based on the names of the columns returned by the query.
Big number: big_namber, label
If you want to display the results as a big number accompanied by a label, you can do so by returning big_number
and label
columns from your query, for example.
select 'Number of states' as label, count(*) as big_number from state;
Custom widgets
You can define your own custom widgets by creating templates with special names.
Decide on the column names that you wish to customize for, then sort them alphabetically and join them with hyphens to create your template name.
For example, you could define a widget that handles results returned as placename
, geojson
by creating a template called geojson-label.html
.
Save that in one of your template directories as django_sql_dashboard/widgets/geojson-label.html
.
Any SQL query that returns exactly the columns placename
and geojson
will now be rendered by your custom template file.
Within your custom template you will have access to a template variable called result
with the following keys:
result.sql
- the SQL query that is being displayedrows
- a list of rows, where each row is an object that can be accessed by index or by column name, e.g.{{ row.big_number }}
.description
- the psycopg2 cursor descriptiontruncated
- boolean, specifying whether the results were truncated (at 100 items) or notduration_ms
- how long the query took, in floating point millisecondstemplates
- a list of templates that were considered for rendering this widget
You can find examples of widget templates in the templates/django_sql_dashboard/widgets directory.
Development
To contribute to this library, first checkout the code. Then create a new virtual environment:
cd django-sql-dashboard
python -mvenv venv
source venv/bin/activate
Or if you are using pipenv
:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
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