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Source channel @githubtrending · Post #15103 · Aug 30
#python#blueteam#discovery#emails#information_gathering#osint#python#recon#reconnaissance#redteam#subdomain_enumeration theHarvester is a free, easy-to-use tool that helps you gather public information about a domain, such as emails, subdomains, IPs, and URLs, from many online sources like search engines and databases. It is useful during security testing to understand a company’s external exposure and find potential vulnerabilities. You can run it with Python and it supports features like DNS brute forcing and taking screenshots of found subdomains. Using theHarvester helps you quickly collect valuable data for cybersecurity assessments, making your research more efficient and thorough. https://github.com/laramies/theHarvester
Search: #sequential
@djangoproject · Post #98 · 07/11/2016, 12:22 PM
https://docs.python.org/3/library/asyncio.html #asyncio #Asynchronous programming is more complex than classical “#sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues.
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@djangoproject · Post #153 · 09/03/2016, 08:20 PM
http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.