Getting Started

Installation

Start by installing django-postgres-metrics from PyPI:

$ pip install django-postgres-metrics

You will also need to make sure to have psycopg2 or psycopg2-binary installed which is already a requirement by Django for PostgreSQL support anyway.

Then you need to add postgres_metrics to your INSTALLED_APPS list. Due to the way postgres_metrics works, you need to include it before the admin app:

INSTALLED_APPS = [
    'postgres_metrics.apps.PostgresMetrics',
    'django.contrib.admin',
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.messages',
    'django.contrib.staticfiles',
]

You also need to make sure that the request context processor is included in the TEMPLATES setting. It is included by default for projects that were started on Django 1.8 or later:

TEMPLATES = [
    {
        'BACKEND': 'django.template.backends.django.DjangoTemplates',
        'OPTIONS': {
            'context_processors': [
                ...,
                'django.template.context_processors.request',
                ...,
            ],
        },
    },
]

Lastly, you need to add a URL path to your global urls.py before the admin URL patterns.

For Django 2.0 and up:

from django.urls import include, path
urlpatterns = [
    path('admin/postgres-metrics/', include('postgres_metrics.urls')),
    path('admin/', admin.site.urls),
]

Congratulations, you made it!

When you now browse to the Django Admin with superuser permissions, you’ll see a “PostgreSQL Metrics” section at the bottom left, listing all available metrics.

This is what a metric could look like:

Screenshot of the Detailed Index Usage metric, with help text, and a table with rows for each index

Designing Your Own Metric

First, you need to import a base class that all metrics inherit from. This will take care of fetching the data from the database, implement sorting if you want, and provide per record and per item in a record styling. Furthermore, you need to make your metric know to django-postgres_metrics-metrics:

from django.utils.translation import ugettext_lazy as _

from postgres_metrics.metrics import Metric, registry


class DjangoMigrationStatistics(Metric):
    """
    Count the number of applied Django migrations per app and sort by
    descending count and ascending app name.
    """
    label - _('Migration Statistics')
    slug - 'django-migration-statistics'
    ordering - '-2.1'
    sql - '''
        SELECT
            app, count(*)
        FROM
            django_migrations
        GROUP BY
            app
        {ORDER_BY}
        ;
    '''


registry.register(DjangoMigrationStatistics)

A short explanation of what the metric class attributes do:

docstring

This will be shown above the metric’s output and allow you to give an explanation what you see.

label

This is what you see on the Django Admin index page as a metric name.

slug

A unique identifier for a metric. This will be used as part of the URL.

ordering

The default ordering you want to use in the metric. Use column indexes (one-indexed) and prefix with - for descending sorting.

sql

The actual SQL you want to run. The {ORDER_BY} part is replaced with ORDER BY 2 DESC, 1 in the example.

Styling Metric Output

Styling Records

If you want to highlight some of the output rows you can define a get_record_style method on a metric class:

class MyMetric(Metric):
    ...

    def get_record_style(self, record):
        if record[0]:
            if record[1] > 1000:
                return 'critical'
            if record[1] > 100:
                return 'warning'
            if record[1] == 0:
                return 'info'
            return 'ok'

The record parameter is a tuple with all values of a single row in the output. This method will be called for every single row being outputted. Don’t do any expensive calculations here!

django-postgres-metrics ships four pre-defined styles: ok, warning, critical and info that you can return.

Styling Record Items

Similarly, you can highlight a single value in the metric output by using the get_record_item_style method on a metric class:

class MyMetric(Metric):
    ...

    def get_record_item_style(self, record, itme, index):
        if index == 2 and record[1]:
            if item > 1000:
                return 'critical'
            if item > 100:
                return 'warning'
            if item == 0:
                return 'info'
            return 'ok'

Along with the record you get the current value or item and the (zero- indexed) position of the item in the record. The item is provided for convenience and is defined as item = record[index].