Python (Django) Setup

🚧

Any issues?

Integrations can be tricky! Contact support if you have any questions/issues.

Overview

If you're a developer, it takes a few small steps to send your API logs to ReadMe so your team can get deep insights into your API's usage with ReadMe Metrics. Here's an overview of how the integration works:

  • You install the ReadMeMetrics Django Middleware and configure your Django app to use it.
  • You write a grouping function, which is used to tie each API request to the user or API key that initiated the request.
  • The middleware will send to ReadMe the request and response objects that your server generates each time a user makes a request to your API. The entire objects are sent, unless you deny or allow specific keys from the request.
  • ReadMe extracts information to display in Metrics, such as which endpoint is being called, response code, and error messages. It also identifies the customer who called your API, using the data returned by your grouping function.

Steps

  1. From the directory of your codebase, run the following command in your command line to install the Django variant of the readme-metrics package from pypi. You can also add this to your requirements.txt file.
pip install "readme-metrics[Django]"
  1. In your codebase, write a grouping function to inform ReadMe of the user or API key holder that is responsible for a given request. The grouping function receives the current Django WSGIRequest object as input, and should return a data structure describing the current user or API key holder. A basic grouping function would look like this:
def grouping_function(request):
    # You can lookup your user here, pull it off the request object, etc.
    # Your grouping function should return None if you don't want the request
    # to be logged, and otherwise return a structure like the one below.
    if user_is_authenticated:
        return {
            "api_key": "unique api_key of the user",
            "label": "label for us to show for this user (account name, user name, email, etc)",
            "email": "email address for user"
        }
    else:
        return None
  1. Add a README_METRICS_CONFIG setting to your Django settings.py file, using the MetricsApiConfig helper object:
from readme_metrics import MetricsApiConfig

README_METRICS_CONFIG = MetricsApiConfig(
    api_key="<<user>>",
    grouping_function="module.path.to.your.grouping_function"
)

The MetricsApiConfig object takes the following parameters:

  • Your ReadMe API Key. If you're logged in to these docs, this string is automatically populated in the preceeding code.
  • A function that takes the Request object and returns a dict describing the user, or None if the request should not be logged
  • Additional options: see details below
  1. Add our MetricsMiddleware to your list of middleware, also in your app's settings.py file:
MIDDLEWARE = [
    ...,
    "readme_metrics.django.MetricsMiddleware",
    ...
]

Identifying the API Caller

There are three fields that you can use to identify the user making the API call. We recommend passing all three to make API Metrics as useful as possible.

FieldTypeDescription
api_keystringRequired API key used to make the request, or another unique identifier of the user who made the request.
labelstringDisplay name for the user or account holder in the API Metrics Dashboard, since it's much more useful to have names than just unique identifiers or API keys.
emailstringEmail address of the user or account holder that is making the call.

Configuration Options

There are a few options you can pass in to change how the logs are sent to ReadMe. These are passed in as parameters to the MetricsApiConfig constructor.

README_METRICS_CONFIG = MetricsApiConfig(
    api_key="<<user>>",
    grouping_function=path.to.your.grouping_function,
    buffer_length=1,
    background_worker_mode=False,
    allowlist=["city", "state", "postal_code", "country"],
    timeout=15
)
OptionTypeDescription
buffer_lengthintBy default, we only send logs to ReadMe after 10 requests are made. Depending on the usage of your API it make make sense to send logs more or less frequently.
development_modeboolDefaults to False. If True, the log will be separate from normal production logs. This is great for separating staging or test data from data coming from customers.
background_worker_modeboolDefaults to True. Determines whether to issue the call to the ReadMe API in a background thread (True), or in the main thread (False). If the ReadMe API call is issued in the main thread, your application server will block until the API call finishes.
denylistdictDefaults to None. An array of keys from your API requests and responses headers and bodies that you wish to block from being sent to ReadMe.

Both the request and response will be checked for these keys, in their HTTP headers, form fields, URL parameters, and JSON request/response bodies. JSON is only checked at the top level, so a nested field will still be sent even if its key matches one of the keys in denylist.

If you configure a denylist, it will override any allowlist configuration.
allowlistdictDefaults to None. An array of headers and JSON body properties to send to ReadMe. If you configure an allowlist then all other properties will be dropped. Otherwise the semantics are similar to denylist.
allowed_http_hostsdictDefaults to None. A list of HTTP hosts which should be logged to ReadMe. If this is present, requests will only be sent to ReadMe whose Host header matches one of the allowed hosts.
timeoutintDefaults to 3. Timeout (in seconds) for calls back to the ReadMe Metrics API.

Did this page help you?