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 \ |
""" | |
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 |
(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.
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