evan-burke

# One of the fastest ways to insert bulk data into Postgres (at least, aside from COPY) is using the psycopg2 extras function execute_values.
# However, this doesn't return an accurate row count value - instead, it just returns the row count for the last page inserted. 
# This wraps the execute_values function with its own pagination to return an accurate count of rows inserted. 
# Performance is approximately equivalent to underlying execute_values function - within 5-10% or so in my brief tests.

import psycopg2
import psycopg2.extras
import math

db_connection_string = "dbname=EDITME host=EDITME"

oxUnd

## FOR UBUNTU
Dependencies install

1. apt-get install nginx-extras
2. apt-get install lua-zlib

lua file decompress request body
--------------------------------

see  https://gist.github.com/iammehrabalam/30f5402bbcdad139c9eafd3a6f47ce6c

chelming

## Please set the ROOT to the folder your nxlog was installed into,
## otherwise it will not start.

#define ROOT C:\Program Files\nxlog
define ROOT C:\Program Files (x86)\nxlog
define CERTDIR %ROOT%\cert

Moduledir %ROOT%\modules
CacheDir %ROOT%\data
Pidfile %ROOT%\data\nxlog.pid

payloadartist

# ------Instructions---------
# Install (and configure) subfinder, assetfinder, and httprobe
# go get -v github.com/projectdiscovery/subfinder/cmd/subfinder && go get -v github.com/tomnomnom/httprobe && go get -v github.com/tomnomnom/assetfinder
# cat firefox.sh >> ~/.bashrc 
# source ~/.bashrc 
# Usage - subf_ff target.tld
#         asset_ff target.tld

subf_ff () {
subfinder -d $1 -silent -t 100 | httprobe -c 50 | sort -u | while read line; do firefox $line; sleep 10; done

mangecoeur

This small subclass of the Pandas sqlalchemy-based SQL support for reading/storing tables uses the Postgres-specific "COPY FROM" method to insert large amounts of data to the database. It is much faster that using INSERT. To acheive this, the table is created in the normal way using sqlalchemy but no data is inserted. Instead the data is saved to a temporary CSV file (using Pandas' mature CSV support) then read back to Postgres using Psychopg2 support for COPY FROM STDIN.

m00zh33

/2
/graphql-proxy/admin
/3.0/
/3ds_callback
/3ds_update_payment_callback
/accounts
/active
/activity
/actuator
/actuator/auditevents

lanmaster53

# Moved to https://github.com/lanmaster53/pyscripter-er/tree/master/snippets

yspb

#make directories
mkdir /git
mkdir /db
mkdir /db/modules
mkdir /downloads

#update packages, install gcc and redis
add-apt-repository ppa:chris-lea/redis-server -y && \
apt-get update && \
apt-get upgrade -y && \

mwielgoszewski

from java.awt import Font
from javax.swing import JScrollPane, JTextPane
from javax.swing.text import SimpleAttributeSet

from burp import IBurpExtender, IExtensionStateListener, IHttpListener, ITab

import base64
import traceback

scrapehero

from lxml import html
import unicodecsv as csv
import requests
from time import sleep
import re
import argparse
import json


def parse(url):