Python (Flask) + API Metrics

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

Overview

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

  • You install the ReadMe Flask extension and configure it in your Flask application.
  • You write a grouping function, which is used to tie each API request to the user or API key that initiated the request.
  • The extension 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 the API Metrics Dashboard, 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 Flask variant of the readme-metrics package from pypi. You can also add this to your requirements.txt file.
pip install readme-metrics[Flask]
  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 Flask Request 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. Set up the extension wherever you initialize your Flask app.
from flask import Flask
from readme_metrics import MetricsApiConfig
from readme_metrics.flask_readme import ReadMeMetrics

# You already have code to create a Flask app...
app = Flask("Your-App-Name")

# Just add code to create the ReadMeMetrics extension and connect it to your app.
metrics_extension = ReadMeMetrics(
    MetricsApiConfig(
        api_key="<<user>>",
        grouping_function=path.to.your.grouping_function
    )
)
metrics_extension.init_app(app)

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

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.

Field

Usage

api_key

Required API key used to make the request, or another unique identifier of the user who made the request.

label

Display 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.

email

Email 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 an object as the first parameter to ReadMeMetrics extension constructor.

metrics_extension = ReadMeMetrics(
    MetricsApiConfig(
        api_key="<<keys:user>>",
        grouping_function=path.to.your.grouping_function,
        buffer_length=1,
        background_worker_mode=False,
        allowlist=["city", "state", "postal_code", "country"],
        timeout=15
    )
)

Option

Use

buffer_length

default: 10 By 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_mode

default: 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_mode

default: 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.

denylist

default: 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.

allowlist

default: 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_hosts

default: 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.

timeout

default: 3 Timeout (in seconds) for calls back to the ReadMe Metrics API.


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