liviaerxin

FastAPI and Uvicorn Logging

When running FastAPI app, all the logs in console are from Uvicorn and they do not have timestamp and other useful information. As Uvicorn applies python logging module, we can override Uvicorn logging formatter by applying a new logging configuration.

Meanwhile, it's able to unify the your endpoints logging with the Uvicorn logging by configuring all of them in the config file log_conf.yaml.

Before overriding:

uvicorn main:app --reload

hursh-desai

import os
import re
import faiss
from langchain import FAISS
import obsidiantools.api as otools
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.chains.qa_with_sources import load_qa_with_sources_chain
from langchain.llms import OpenAI

os.environ["OPENAI_API_KEY"] = 'sk-********'

kilianplapp

import requests
from lxml import html

def getPastes():
    for link in html.fromstring(requests.get("https://pastebin.com/archive").text).xpath('//tr//a'):
        if str(link.get('href')).startswith('/archive/'): continue
        yield (str(link.get('href')).replace('/', ''))
        
for i in getPastes():
    print(i)

vpnwall-services

Hacking With cURL

A list of examples and references of hacking with Bash and the Curl command.

What the heck is cURL?

cURL is short for "Client URL" and is a computer software project providing a library (libcurl) and command-line tool (curl) first released in 1997. It is a free client-side URL transfer library that supports the following protocols: Cookies, DICT, FTP, FTPS, Gopher, HTTP/1, HTTP/2, HTTP POST, HTTP PUT, HTTP proxy tunneling, HTTPS, IMAP, Kerberos, LDAP, POP3, RTSP, SCP, and SMTP Although attack proxies like BurpSuitePro are very handy tools, cURL allows you to get a bit closer to the protocol level, leverage bash scripting and provides a bit more flexibility when you are working on a complex vulnerability.

cURL GET parameters

HTTP GET variables can be set by adding them to the URL.

Aditya1001001

def tagged_document(list_of_list_of_words):
   for i, list_of_words in enumerate(list_of_list_of_words):
      yield gensim.models.doc2vec.TaggedDocument(list_of_words, [i])
 
training_data = list(tagged_document(data))
model = gensim.models.doc2vec.Doc2Vec(vector_size=40, min_count=2, epochs=30)
 
model.build_vocab(training_data)
model.train(training_data, total_examples=model.corpus_count, epochs=model.epochs)

bgoonz

Everything You Need To Become A Machine Learner

Part 1:

---

Everything You Need To Become A Machine Learner

Part 1:

prof3ssorSt3v3

File Details

• webpack.config.js goes in the root folder of your project
• package.json goes in the root folder of your project

Run this command to install all the dependecies from the package.json file

npm install

alanjones2

from flask import Flask, render_template
import pandas as pd
import json
import plotly
import plotly.express as px

app = Flask(__name__)

@app.route('/')
def index():

devamitranjan

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd 
import math

class UpperConfidenceBound:
  def __init__(self,path,  N, m):
    self.__dataset = pd.read_csv(path)
    self.__N = N
    self.__m = m

oofnikj

KEYMAPOPTS="us us"
HOSTNAMEOPTS="-n alpine"
INTERFACESOPTS="auto lo
iface lo inet loopback

auto eth0
iface eth0 inet dhcp
    hostname alpine
"
TIMEZONEOPTS="-z UTC"