cobanov

(()=>{"use strict";var e={100:(e,t,n)=>{n.d(t,{A:()=>i});var r=n(601),o=n.n(r),a=n(314),l=n.n(a)()(o());l.push([e.id,".with-app-header,html .iu .app-sidebar,html .iu .results-container,html .iu .unfollow-log-container{padding-top:4rem !important}.flex,html .iu .app-header,html .iu .app-header-content,html .iu .app-sidebar,html .iu .results-container .result-item,html .iu .tabs-container{display:flex}.flex.align-center,html .iu .align-center.app-header,html .iu .align-center.app-sidebar,html .iu .align-center.tabs-container,html .iu .app-header-content,html .iu .results-container .result-item{align-items:center}.flex.justify-center,html .iu .justify-center.app-header,html .iu .justify-center.app-header-content,html .iu .justify-center.app-sidebar,html .iu .results-container .justify-center.result-item,html .iu .justify-center.tabs-container{justify-content:center}.flex.column,html .iu .column.app-header,html .iu .column.app-header-content,html .iu .results-container .column.result-item,html .iu .column.tabs-co

virattt

nymous

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

tajnymag

// ==UserScript==
// @name        Tinder Deblur
// @namespace   Violentmonkey Scripts
// @match       https://tinder.com/*
// @grant       none
// @version     1.4
// @author      Tajnymag
// @downloadURL https://raw.githubusercontent.com/tajnymag/tinder-deblur/main/tinder.user.js
// @description Simple script using the official Tinder API to get clean photos of the users who liked you
// ==/UserScript==

MuhammadSaim

RAR registration data
WinRAR
Unlimited Company License
UID=4b914fb772c8376bf571
6412212250f5711ad072cf351cfa39e2851192daf8a362681bbb1d
cd48da1d14d995f0bbf960fce6cb5ffde62890079861be57638717
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6e6fb824bcf25f155547b5fc41901ad58c0992f570be1cf5608ba9

bshishov

import numpy as np

EPSILON = 1e-10


def _error(actual: np.ndarray, predicted: np.ndarray):
    """ Simple error """
    return actual - predicted

cvan

var canvas = document.createElement('canvas');
var gl;
var debugInfo;
var vendor;
var renderer;

try {
  gl = canvas.getContext('webgl') || canvas.getContext('experimental-webgl');
} catch (e) {
}

marekrei

import numpy as np
import os, sys, getopt

# Main path to your caffe installation
caffe_root = '/path/to/your/caffe/'

# Model prototxt file
model_prototxt = caffe_root + 'models/bvlc_googlenet/deploy.prototxt'

# Model caffemodel file

fperez