| #!/usr/bin/env python3 | |
| """Easily put time restrictions on things | |
| Note: Requires Python 3.x | |
| Usage as a context manager: | |
| ``` | |
| with timeout(10): | |
| something_that_should_not_exceed_ten_seconds() | |
| ``` |
| """ | |
| Response to | |
| http://stackoverflow.com/a/22904200/1320237 | |
| """ | |
| import json.scanner | |
| import json.decoder | |
| from json.decoder import JSONDecoder | |
| class FileString(object): |
| #!/usr/bin/env python3 | |
| import os | |
| import json | |
| import random | |
| import zipfile | |
| config = { | |
| "color": "red", | |
| "amount": 42.24, |
| import boto3 | |
| from PIL import Image | |
| from io import BytesIO | |
| import os | |
| class S3ImagesInvalidExtension(Exception): | |
| pass | |
| class S3ImagesUploadFailed(Exception): | |
| pass |
This was tested on MacOS 10.14.5 on 2019-07-16
schemacrawler is a free and open-source database schema discovery and comprehension tool. It can be invoked from the command-line to produce, using GraphViz, images/pdfs from a SQLite (or other database type) file. It can be used from the command-line to generate schema diagrams like these:
| from functools import lru_cache | |
| from datetime import datetime | |
| @lru_cache(maxsize=None) | |
| def fib_cache(n): | |
| if n < 2: | |
| return n | |
| return fib_cache(n-1) + fib_cache(n-2) | |
| def fib_no_cache(n): |
Python script to clone an existing VPC route table. Script output is a series of AWS CLI calls to create the route table and assign routes.
Update AWS_TARGET_REGION and SOURCE_ROUTE_TABLE_ID to suit.
Note: does not currently support NAT Gateways routes due to Boto 2 API limitation.
$ ./clone-route-table.py
| # https://hakibenita.com/fast-load-data-python-postgresql | |
| from typing import Iterator, Dict, Any, Optional | |
| from urllib.parse import urlencode | |
| import datetime | |
| #------------------------ Profile | |
| import time |
RDBMS-based job queues have been criticized recently for being unable to handle heavy loads. And they deserve it, to some extent, because the queries used to safely lock a job have been pretty hairy. SELECT FOR UPDATE followed by an UPDATE works fine at first, but then you add more workers, and each is trying to SELECT FOR UPDATE the same row (and maybe throwing NOWAIT in there, then catching the errors and retrying), and things slow down.
On top of that, they have to actually update the row to mark it as locked, so the rest of your workers are sitting there waiting while one of them propagates its lock to disk (and the disks of however many servers you're replicating to). QueueClassic got some mileage out of the novel idea of randomly picking a row near the front of the queue to lock, but I can't still seem to get more than an an extra few hundred jobs per second out of it under heavy load.
So, many developers have started going straight t
| #!/bin/sh | |
| # Darkify Slack on Mac OS or Linux. | |
| # curl https://gist.githubusercontent.com/ryanpcmcquen/8a7ddc72460eca0dc1f2dc389674dde1/raw/darkify_slack.sh | sh | |
| if [ "`uname -s`" = "Darwin" ]; then | |
| SLACK_INTEROP_JS="/Applications/Slack.app/Contents/Resources/app.asar.unpacked/src/static/ssb-interop.js" | |
| else | |
| SLACK_INTEROP_JS="/usr/lib/slack/resources/app.asar.unpacked/src/static/ssb-interop.js" | |
| fi |