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@nymous
nymous / README.md
Last active July 9, 2024 20:53
Logging setup for FastAPI, Uvicorn and Structlog (with Datadog integration)

Logging setup for FastAPI

This logging setup configures Structlog to output pretty logs in development, and JSON log lines in production.

Then, you can use Structlog loggers or standard logging loggers, and they both will be processed by the Structlog pipeline (see the hello() endpoint for reference). That way any log generated by your dependencies will also be processed and enriched, even if they know nothing about Structlog!

Requests are assigned a correlation ID with the asgi-correlation-id middleware (either captured from incoming request or generated on the fly). All logs are linked to the correlation ID, and to the Datadog trace/span if instrumented. This data "global to the request" is stored in context vars, and automatically added to all logs produced during the request thanks to Structlog. You can add to these "global local variables" at any point in an endpoint with `structlog.contextvars.bind_contextvars(custom

@samuelcolvin
samuelcolvin / python-people.md
Last active June 23, 2024 19:06
An incomplete list of people in the Python community to follow on Twitter and Mastodon.

Python People

(Updated 2022-11-16 with suggestions from comments below, Twitter and Mastodon)

An incomplete list of people in the Python community to follow on Twitter and Mastodon.

With the risk that Twitter dies, I'd be sad to lose links to interesting people in the community, hence this list.

I would love you to comment below with links to people I've missed.

@nkhitrov
nkhitrov / structlog_fastapi.py
Created March 16, 2023 00:04
Structlog FastAPI example
"""
Structlog example configuration with FastAPI.
Features:
- async bound logger
- contextvars to log request-id and other meta data
- custom format for default logging loggers and structlog loggers
"""
import asyncio
import logging
@chalg
chalg / great_tables_co2.py
Last active May 13, 2024 07:15
Showcase electricity consumption data for 2023 from ElectricityMaps via Python great_tables
from great_tables import GT, md, html, system_fonts
import pandas as pd
power_cie_prepared_tbl = pd.read_csv("./data/2023_cie_power_cons.csv")
# Create a Great Tables object
ciep_gt_tbl = GT(data=power_cie_prepared_tbl)
# Apply wider color ranges & formatting
gt_tbl = ciep_gt_tbl \