Logging HTTP Client

A logging library built on top of the requests library to provide a familiar interface for sending HTTP requests with observability features out-of-the-box.

Table of Contents

• Background
• Usage
  • 1. Drop-in Replacement for requests
  • 2. Using the HTTP Client with reusable Sessions
    • i. Disabling Reusable Sessions For The HTTP Client
    • ii. Adding Shared Headers to the HTTP Client
    • iii. Setting the client's x-source
    • iii. x-request-id is automatically set
    • iv. x-correlation-id can be automatically set
  • 3. Custom Logging Hooks
    • i. Request Logging Hook
    • ii. Response Logging Hook
  • 4. Default Logging Configurations
    • i. Disabling Request or Response Logging
    • ii. Enabling Request or Response Body Logging
  • 5. Obscuring Sensitive Data
    • i. Request Log Record Obscurer
    • ii. Response Log Record Obscurer
• HTTP Log Record Structure
• Contributing
  • Prerequisites
  • Environment Setup
  • Code Quality
  • Versioning Strategy

Background

The requests library is a popular library for sending HTTP requests in Python. However, it does not provide adequate observability features out of the box such as tracing and logging. As such, this library was built to decorate the requests library API to provide these opinionated features for common use cases.

For example, by simply using this library for your requests, the following will be appended to your logs:

import logging
import logging_http_client as requests

# Basic logging configuration for demonstration purposes 
logging.basicConfig(
    level=logging.INFO,
    format='%(message)s - %(http)s'
)

requests.get(
    url="https://www.python.org",
    headers={"x-foo": "bar"},
)

# => Log records will include:
#    message: REQUEST, 
#    http: { 
#       request_id: "6a09ec23-b318-43d2-81a1-8c1fcaf77d05", 
#       request_method: "GET", 
#       request_url: "https://www.python.org", 
#       request_headers: { "x-foo": "bar", "x-request-id": "6a09ec23-b318-43d2-81a1-8c1fcaf77d05", ... } 
#   }
#
#    message: RESPONSE,
#    http: {
#       request_id: "6a09ec23-b318-43d2-81a1-8c1fcaf77d05",
#       response_status: 200,
#       response_headers: { "content-type": "text/html", ... },
#       response_duration_ms: 30
#    }

You have full control over the logging behaviour, and you can customise it to suit your needs. The library provides hooks for custom logging, and you can disable or enable request or response logging as needed. You can also obscure sensitive data in the log records, and set shared headers for the client instances that relies on reusable sessions for better performance by default.

Usage

The quickest way to get started is to install the package from PyPI:

pip install logging-http-client

For poetry users:

poetry add logging-http-client

1. Drop-in Replacement for requests

The library is designed to decorate requests library existing API. Hence, you can use it in the same way you would use the requests library:

import logging_http_client

response = logging_http_client.get('https://www.python.org')
print(response.status_code)
# => 200

Given it's built as a wrapper around the requests library, you can alias the import to requests and use it as drop-in replacement for the requests' library.

import logging_http_client as requests

response = requests.get('https://www.python.org')
print(response.status_code)
# => 200

The other HTTP methods are supported - see requests.api. Full documentation is at: https://requests.readthedocs.io

2. Using the HTTP Client with reusable Sessions

The library provides a LoggingHttpClient class which is essentially a wrapper around the core component of the requests library, the Session object, with additional features such as enabling reusable sessions or not.

import logging_http_client

client = logging_http_client.create()

response = client.get('https://www.python.org')
print(response.status_code)
# => 200

i. Disabling Reusable Sessions For The HTTP Client

By default, the LoggingHttpClient class is created with a reusable session. If you want to disable this behaviour, you can pass the reusable_session=False argument to the create method.

import logging_http_client

client = logging_http_client.create(reusable_session=False)

response = client.get('https://www.python.org')
print(response.status_code)
# => 200

ii. Adding Shared Headers to the HTTP Client

You also have access to the session object headers within the LoggingHttpClient class, so you can add shared headers to the session object just like you would with the requests library.

import logging_http_client

client = logging_http_client.create()

client.shared_headers = {"Authorization": "Bearer <token>"}

# To clear the headers, you can set it to None
client.shared_headers = None
# or delete the attribute
del client.shared_headers

iii. Setting the client's x-source

It's common to set a x-source header to identify the source of the request. You can set this header on the client by passing the source argument to the create method.

import logging

import logging_http_client

root_logger = logging.getLogger()
root_logger.setLevel(level=logging.INFO)

client = logging_http_client.create(source="my-system-name", logger=root_logger)

response = client.get('https://www.python.org')
# => Log record will include: 
#    { http { request_source: "my-system-name", ... } }

iii. x-request-id is automatically set

The library automatically sets a x-request-id header on the request, and is logged within the response as well. The x-request-id is a UUID that is generated for each request, and it's attached on both the request and the response logs.

import logging

import logging_http_client

root_logger = logging.getLogger()
root_logger.setLevel(level=logging.INFO)

client = logging_http_client.create(source="my-system-name", logger=root_logger)

response = client.get('https://www.python.org')
# => The client will append the `x-request-id` header to the request
#
# => Both request and response log records will include: 
#    { http { request_id: "<uuid>", ... } }
# => The reqeust log record will also attach it as a header: 
#    { http { request_headers: { "x-request-id": "<uuid>", ... }, ... } }

iv. x-correlation-id can be automatically set

It's common to set a x-correlation-id header to identify the correlation of the request within a distributed system. Instead of having to set this header manually every single request you make, you can pass a correlation ID generator function to the client, and it will automatically set the x-correlation-id header for each request.

Warning

Be aware that x-request-id is not the same as x-correlation-id.

The x-request-id is unique to each request, while the x-correlation-id is used to correlate requests within a chain of events that can span multiple services, this is common in a microservice architecture. Please ensure you understand the difference between the two whilst using them with this library.

import uuid
import logging_http_client 

def correlation_id_provider() -> str:
    return str(uuid.uuid4())

logging_http_client.set_correlation_id_provider(correlation_id_provider)

logging_http_client.create().get('https://www.python.org')
# => The client will append the `x-correlation-id` header to the request 
#
# => The request log records will include:
#    { http { request_headers: { "x-correlation-id": "<uuid>", ... }, ... } }

Do note we do NOT set the x-correlation-id header on the response, it's the responsibility of the server to set it back on the response, if they don't, then you need to rely on your logging setup to append the correlation_id as an extra log record attribute on the client side by other means.

3. Custom Logging Hooks

The library provides a way to attach custom logging hooks at the global level. They're intended to REPLACE the default logging behaviour with your own logging logic. Here is how you can apply:

i. Request Logging Hook

The request logging hook is called before the request is sent. It gives you access to the client logger, and the prepared request object. You can use this hook to log the request before it's sent.

import logging

from requests import PreparedRequest

import logging_http_client


def custom_request_logging_hook(logger: logging.Logger, request: PreparedRequest):
    logger.debug("Custom request logging for %s", request.url)


logging_http_client.set_custom_request_logging_hook(custom_request_logging_hook)

logging_http_client.create().get('https://www.python.org')

# => Log record will include:
#    { message { "Custom request logging for https://www.python.org" } }

ii. Response Logging Hook

The response logging hook is called after the response is received. It gives you access to the client logger, and the response object. You can use this hook to log the response after it's received.

import logging

from requests import Response

import logging_http_client


def custom_response_logging_hook(logger: logging.Logger, response: Response):
    logger.debug("Custom response logging for %s", response.url)


logging_http_client.set_custom_response_logging_hook(custom_response_logging_hook)

logging_http_client.create().get('https://www.python.org')

# => Log record will include:
#    { message { "Custom response logging for https://www.python.org" } }

4. Default Logging Configurations

The default logging comes with a set of configurations that can be customised to suit your needs.

i. Disabling Request or Response Logging

You can disable request or response logging by calling the disable_request_logging or disable_response_logging methods respectively. This will prevent the library from generating log records for requests or responses UNLESS you have custom logging hooks set.

import logging_http_client

logging_http_client.disable_request_logging()
logging_http_client.disable_response_logging()

logging_http_client.create().get('https://www.python.org')
# => No request log record will be generated
# => No response log record will be generated

ii. Enabling Request or Response Body Logging

By default, the library does not log the request or response body. You can enable this by calling the enable_request_body_logging or enable_response_body_logging methods respectively. This will log the request or response body in the log record.

import logging_http_client

logging_http_client.enable_request_body_logging()
logging_http_client.enable_response_body_logging()

logging_http_client.create().get('https://www.python.org')
# => Log record will include the request or response body (if present)

iii. Customizing the logging level

By default, the library logs at the 'INFO' level. To adjust this, use the set_logging_level method. You can specify the desired level as either an integer (10, 20, 30, 40, 50) or a string ("INFO", "DEBUG", etc.).

import logging_http_client

logging_http_client.set_logging_level(logging_http_client.LogLevel.DEBUG)

logging_http_client.create().get('https://www.python.org')
# => Logs will be recorded at the DEBUG level now.

5. Obscuring Sensitive Data

The library provides a way to obscure sensitive data in the request or response log records. This is useful when you want to log the request or response body but want to obscure sensitive data such as passwords, tokens, etc.

i. Request Log Record Obscurer

You can set a request log record obscurer by calling the set_request_log_record_obscurer method. The obscurer function should take a HttpLogRecord object and expects to return a modified HttpLogRecord object. The obscurer function will be called JUST BEFORE the request is logged.

import logging_http_client
from logging_http_client import HttpLogRecord


def request_log_record_obscurer(record: HttpLogRecord) -> HttpLogRecord:
    record.request_method = "REDACTED"
    if record.request_headers.get("Authorization") is not None:
        record.request_headers["Authorization"] = "****"
    return record


logging_http_client.set_request_log_record_obscurer(request_log_record_obscurer)

logging_http_client.create().get(
    url='https://www.python.org',
    headers={"Authorization": "Bearer SOME-SECRET-TOKEN"}
)

# => Log record will include:
#    { http { request_headers: { "Authorization ": "****", ... }, ... } }

ii. Response Log Record Obscurer

Likewise, you can set a response log record obscurer by calling the set_response_log_record_obscurer method. The obscurer function should take a HttpLogRecord object and expects to return a modified HttpLogRecord object.

import logging_http_client
from logging_http_client import HttpLogRecord


def response_log_record_obscurer(record: HttpLogRecord) -> HttpLogRecord:
    record.response_status = 999
    if record.response_body is not None:
        record.response_body = record.response_body.replace("SENSITIVE", "****")
    return record


logging_http_client.set_response_log_record_obscurer(response_log_record_obscurer)
logging_http_client.enable_response_body_logging()

logging_http_client.create().get('https://www.python.org')
# Assume the response body contains "some response body with SENSITIVE information" 

# => Log record will include:
#    { http { response_status: 999, response_body: "some response body with **** information", ... } }

HTTP Log Record Structure

The library logs HTTP requests and responses as structured log records. The log records are structured as JSON object passed to the logger's extra keyword argument. The log records are structured as follows:

{
  "http": {
    "request_id": "<uuid>",
    "request_source": "<source>",
    "request_method": "<method>",
    "request_url": "<url>",
    "request_query_params": "<query_params>",
    "request_headers": "<headers>",
    "request_body": "<body>",
    "response_status": "<status>",
    "response_headers": "<headers>",
    "response_duration_ms": "<duration>",
    "response_body": "<body>"
  }
}

If any of those top-level fields are None, {}, [], "", 0, or 0.0, they will be omitted from the log record for brevity purposes.

The actual data class used to represent the log record is HttpLogRecord and is available in the logging_http_client.

Contributing

If you have any suggestions or improvements, feel free to open a PR or an issue. The build and development process has been made to be as seamless as possible, so you can easily run and test your changes locally before submitting a PR.

Prerequisites

• Python: The project is built with Python 3.12.
• Poetry: The dependency management tool of choice for this project.
• Docker: For containerisation support, so it can be completely built and run in an isolated environment.
• Make: For running common tasks such as installing dependencies, building the project, running tests, etc.

Environment Setup

Before opening the project in your IDE, I highly recommend running the following recipe:

make setup

This will create your Poetry's virtual environment, install the project's dependencies, set up the code quality pre-commit hook, and configure your IDE (VSCode and PyCharm) as appropriate.

Code Quality

We ask for adequate test coverage and adherence to the project's code quality standards. This includes running the tests, formatter, and linter before submitting a PR. You can run the following command to ensure your changes are in line with the project standards:

make check-code-quality

Versioning Strategy

Since this project is tightly coupled with the requests library, we will follow the versioning strategy of the requests' library. This means that the major, minor, and patch versions of this library will be the same as the requests' library version it currently decorates. On top of that, an extra versioning suffix will be added to the end of the version to indicate the iteration of this library.

So for example, if the requests library is at version 1.2.3, then this library will be at version 1.2.3.X, where X is the iteration of this library, which will be numerical increments starting from 0.

We have no intention to follow Semantic Versioning strategy to version this library, as I've made a design decision to keep the features of this library's as small as possible, i.e.

"Do few things, but do them well..."

So for the most part, the maintenance of this library will be keeping it up-to-date with newer versions of the the requests library, whilist ensuring everything still works as expeceted. Therefore, maintaining our high test coverage is crucial for long-term useability.

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