Search the Community

Showing results for tags 'python'.



More search options

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


Forums

  • Staff Control
    • Staff Announcements
    • Moderators
    • Staff
    • Administration
  • General doubts | News
    • General doubts
    • News
  • Hacking | Remote Administration | Bugs & Exploits
    • Hacking
    • Remote Administration
    • Bugs & Exploits
  • Programming | Web | SEO | Prefabricated applications
    • General Programming
    • Web Programming
    • Prefabricated Applications
    • SEO
  • Pentesting Zone
  • Security & Anonymity
  • Operating Systems | Hardware | Programs
  • Graphic Design
  • vBCms Comments
  • live stream tv
  • Marketplace
  • Pentesting Premium
  • Modders Section
  • PRIV8-Section
  • Pentesting Zone PRIV8
  • Carding Zone PRIV8
  • Recycle Bin
  • Null3D's Nulled Group

Blogs

There are no results to display.

There are no results to display.


Find results in...

Find results that contain...


Date Created

  • Start

    End


Last Updated

  • Start

    End


Filter by number of...

Joined

  • Start

    End


Group


About Me


Location


Interests


Occupation


TeamViewer


Twitter


Facebook


Youtube


Google+


Tox

Found 121 results

  1. CrackerJack is a Web GUI for Hashcat developed in Python. Architecture This project aims to keep the GUI and Hashcat independent. In a nutshell, here’s how it works: User uploads hashes select wordlist/rules/mask etc, and clicks “start”. Web server spawns a new screen. Generates the hashcat command based on the settings. Runs the command on the screen. Monitors the screen’s output, parses it and displays it in the GUI. This allows CrackerJack to be future-proof as it ties to the input/output of Hashcat. Also, if the GUI is not working for whatever reason, hashcat will keep running. Features Minimal dependencies Uses sqlite3, screen, and hashcat. Complete hashcat session management. Start/stop/pause/restore running sessions. Terminate cracking jobs after a specific date/time. Web interface for mask generation (?a?l?u). Web Push notifications when a password is cracked. Swagger 2.0 API. Create wordlists from already cracked passwords and feedback into the cracking session. Session history to track which attacks you have already performed. Multi-user support (local and/or LDAP). Wordlist/Mask/Rule support. Multiple theme support (Bootswatch). Straight-forward setup. The entire configuration is via the GUI. No need for manually editing config files. Run locally on Linux and Windows (WSL). Install on a server using ansible scripts (Ubuntu 14/16/18 and CentOS 7/8). Easy backups – all user data are in the ./data directory. Troubleshoot sessions via SSH. Limitations Not a solution for queueing jobs – it’s only for on-demand password cracking. Not meant to be a replacement for command-line usage. It’s complimentary and only supports basic and most common cracking tasks. Will not install any GPU drivers. The main assumption is that you have a cracking rig already set up and are looking for a Web GUI. Wordlists and rules should already be present in the system. Changelog v1.1.2 [New] Added “Test Connection” feature to LDAP settings. [hide][Hidden Content]]
  2. Diaphora is a plugin for IDA Pro that aims to help in the typical BinDiffing tasks. It’s similar to other competitor products and open sources projects like Zynamics BinDiff, DarunGrim, or TurboDiff. However, it’s able to perform more actions than any of the previous IDA plugins or projects. Diaphora is distributed as a compressed file with various files and folders inside it. The structure is similar to the following one: diaphora.py: The main IDAPython plugin. It contains all the code of the heuristics, graphs displaying, export interface, etc… jkutils/kfuzzy.py: This is an unmodified version of the kfuzzy.py library, part of the DeepToad project, a tool and a library for performing fuzzy hashing of binary files. It’s included because fuzzy hashes of pseudo-codes are used as part of the various heuristics implemented. jkutils/factor.py: This is a modified version of a private malware clusterization toolkit based on graphs theory. This library offers the ability to factor numbers quickly in Python and, also, to compare arrays of prime factors. Diaphora uses it to compare fuzzy AST hashes and call graph fuzzy hashes based on small-primes-products (an idea coined and implemented by Thomas Dullien and Rolf Rolles first, authors or former authors of the Zynamics BinDiff commercial product, in their “Graph-based comparison of Executable Objects – Zynamics” paper). Pygments/: This directory contains an unmodified distribution of the Python pygments library, a “generic syntax highlighter suitable for use in code hosting, forums, wikis or other applications that need to prettify source code”. [hide][Hidden Content]]
  3. FindYara Use this IDA python plugin to scan your binary with Yara rules. All the Yara rule matches will be listed with their offset so you can quickly hop to them! Using FindYara The plugin can be launched from the menu using Edit->Plugins->FindYara or using the hot-key combination Ctrl-Alt-Y. When launched the FindYara will open a file selection dialogue that allows you to select your Yara rules file. Once the rule file has been selected FindYara will scan the loaded binary for rule matches. All rule matches are displayed in a selection box that allows you to double click the matches and jump to their location in the binary. [hide][Hidden Content]]
  4. james bond

    x7 python iptv

    [Hidden Content]
  5. Fully functional ransomware that uses minimum resources to give maximum output TASK LIST Encrypt all files except system specific ones Encrytion must only be decrypted with a special key Send the credentials of the victim to the attacker via secure tunnel, preferably NGROK Pop up box should appear after encryption asking for ransom Create a server to retrieve information sent by the victim Add custom extension to encrypted files Generate an exe file to be sent to victims Graphical User Interface (Victim side) Graphical User Interface (Attacker side) Create Windows Defender bypass script [hide][Hidden Content]]
  6. Learn to Apply Python and Build many Projects and Programs using Python Programming Language. Code more than 12 Projects. What you'll learn Three Automatic Translation Programs with three Different libraries and tools. Building and Managing different types of data files such as CSV files, pickle files and JSON files using Python How to work and manage PDF files using python programming language libraries. Using object-oriented basics to store the details for many employees. Building a real digital clock using python programming language and libraries to code that digital clock from the Ground Up Creating a game for guessing a number from random numbers depending on three levels we are going to set Creating a music loader using the PyGame library Creating a full Music and audio player using python programming language with the two libraries: PyGame and Tkinter Building a real Video player using python programming language Building a database based on a CSV file we have Course content 9 sections • 26 lectures • 3h 28m total length Requirements The basics of Python Jupyter Notebook or any working environment for Python Description Hello and welcome to this applied Python course “Applied Python: Tiny Python Projects Fast & Effective Course”. This is a powerful training program about creating real programs using the core python programming language. This course is so effective, direct to the point, detailed, and will save your precious time. You will learn how to use python programming language to create and build real life programs step-by-step the right way. This course is so important and special for any intermediate Python developer or anyone who wants to learn how to apply Python in real life. Do you want to write real programs with python programming language quickly? If your answer is Yes, this training course is for you, and will help you a lot to become a professional python developer. By the end of this course you’ll learn to build these programs: Three Automatic Translation Programs with three Different libraries and tools. Building and Managing different types of data files such as CSV files, pickle files and JSON files using Python. how to work and manage PDF files using python programming language libraries. Using object-oriented basics to store the details for many employees. Building a real digital clock using python programming language and libraries to code that digital clock from the Ground Up. Creating a game for guessing a number from random numbers depending on three levels we are going to set. Creating a music loader using the PyGame library. Creating a full Music and audio player using python programming language with the two libraries: PyGame and Tkinter. Building a real Video player using python programming language. Building a database from a CSV file . You'll learn all of that and more practically with Hands-On video Training. Code more than 12 Projects. The training course lessons are easy to follow, understandable and interactive. I am Ahmed Ibrahim, a software engineer and Instructor and I have taught more than 250,000 engineers and developers around the world in topics related to programming languages and their applications. I hope that you will join us in this applied course. We have a lot to cover in this course. Let’s get started! Who this course is for: Intermediate Python developer Python Beginners who know the Python basics Anyone who wants to learn how to apply Python in real life Python developers from all levels [Hidden Content] [hide][Hidden Content]]
  7. Diaphora is a plugin for IDA Pro that aims to help in the typical BinDiffing tasks. It’s similar to other competitor products and open sources projects like Zynamics BinDiff, DarunGrim, or TurboDiff. However, it’s able to perform more actions than any of the previous IDA plugins or projects. Diaphora is distributed as a compressed file with various files and folders inside it. The structure is similar to the following one: diaphora.py: The main IDAPython plugin. It contains all the code of the heuristics, graphs displaying, export interface, etc… jkutils/kfuzzy.py: This is an unmodified version of the kfuzzy.py library, part of the DeepToad project, a tool and a library for performing fuzzy hashing of binary files. It’s included because fuzzy hashes of pseudo-codes are used as part of the various heuristics implemented. jkutils/factor.py: This is a modified version of a private malware clusterization toolkit based on graphs theory. This library offers the ability to factor numbers quickly in Python and, also, to compare arrays of prime factors. Diaphora uses it to compare fuzzy AST hashes and call graph fuzzy hashes based on small-primes-products (an idea coined and implemented by Thomas Dullien and Rolf Rolles first, authors or former authors of the Zynamics BinDiff commercial product, in their “Graph-based comparison of Executable Objects – Zynamics” paper). Pygments/: This directory contains an unmodified distribution of the Python pygments library, a “generic syntax highlighter suitable for use in code hosting, forums, wikis or other applications that need to prettify source code”. Changelog v2.0.6 BUG: Do not crash when we cannot analyse one Diaphora SQLite database. BUG: Diaphora was incorrectly searching the pattern ‘{}’ instead of ‘[]’ for empty list field values. Fix for #219. GUI: When a reverser uses the “Diff pseudo-code” option and both codes are equal, show a warning message, but also show the diffing. HEUR: In heuristic “Call Address Sequence” use also the “Partial results” when the function name is the same. HEUR: Added heuristic “Same RVA”. Only matches with a minimum ratio of 0.7 will be considered. HEUR: Removed the “Slow” flag from the heuristic “Same Rare Constant”. HEUR: Use the 3 calculated fuzzy hashes in heuristic “Pseudo-code Fuzzy Hash”. HEUR: Moved heuristic “Similar Pseudo-code and Names” from the probably unreliable category to normal. HEUR: Removed wrong heuristics “Similar Small Pseudo-codes” and “Equal Small Pseudo-codes” because they caused a lot of false positives (heuristics for finding matches tend to fail with small functions, and these were no exception). Also, applied suggestion for issue #220. [hide][Hidden Content]]
  8. Cerbrutus Modular brute force tool written in Python, for very fast password spraying SSH, and FTP and in the near future other network services. COMING SOON: SMB, HTTP(s) POST, HTTP(s) GET, HTTP BASIC AUTH Thanks to @0dayctf, Rondons, Enigma, and 001 for testing and contributing [hide][Hidden Content]]
  9. El lenguaje de programación Python ha ganado una inmensa atención y popularidad en los últimos años. La razón para amar y usar Python es muy simple: la simplicidad y las características versátiles que este maravilloso lenguaje de programación ofrece a los usuarios. ¡Hoy veremos la introducción de Python, algunas de las mejores características que admite y varios factores que hacen que Python sea diferente de la plétora de lenguajes de programación que existen! ¿Qué es Python? Python es un lenguaje de programación de alto nivel, dinámico, interpretado y orientado a objetos, que fue desarrollado por Guido Van Rossum. Python está enriquecido con varias funciones y características útiles para su uso. Funciones de Python Python le brinda al usuario el corte que necesita mientras programa, al admitir varias funciones útiles. Estas funciones incluyen: • Dinámico • Orientado a objetos • Soporte GUI • Multiplataforma • Extensible • Facilidad de uso • Integrado • De uso gratuito y de código abierto • Soporte comunitario • Actualizaciones frecuentes ¿Por qué aprender Python? ¡Las razones para aprender Python son muchas y para no aprender ninguna! Python se ha convertido en la primera opción de los desarrolladores de todo el mundo, debido a su eficiencia y características versátiles. • Las empresas de tecnología más grandes y líderes, incluidas CISCO, IBM, Mozilla, Google, Quora, HP, Dropbox, QUALCOMM, etc., utilizan Python debido a su simplicidad y elegancia. • Los desarrolladores prefieren usar Python sobre la pila de diferentes disponibles en el mercado debido a su énfasis en la legibilidad y la eficiencia. • Python es el lenguaje de programación preferido de la mayoría de los científicos de datos, aprendices de máquinas, científicos de inteligencia artificial, etc. • Python es un lenguaje fácil de aprender y dominar. Esto se debe principalmente a la semejanza de su sintaxis con el idioma inglés. La sintaxis de Python se caracteriza por muy pocas reglas y excepciones. • Es seguro decir que en Python la atención se centra en lo que quiere hacer con el código, no en las complejidades del lenguaje. Cualquiera puede dominar Python fácilmente. • Python es puramente multiplataforma y de código abierto. El mismo código escrito en un sistema Windows se puede ejecutar en máquinas Linux o Mac con cambios mínimos o nulos en el código fuente. • Otro aspecto notable de Python es que está respaldado por décadas de corrección de errores y enderezado de torceduras, lo que garantiza que su código funcione según lo previsto siempre que el usuario lo ejecute. • Python es compatible con PYPI, que tiene más de 85.000 bibliotecas y módulos de Python para los usuarios. • Python se adapta a todos los propósitos de desarrollo, desde desarrollo web, automatización, inteligencia artificial, aprendizaje automático, desarrollo de juegos, aplicaciones de escritorio y mucho más. Python para desarrollo web Python ofrece algunos marcos bien conocidos para desarrolladores web como Django y Flask. Estos marcos se pueden utilizar en el desarrollo de backend para aplicaciones basadas en web con gran funcionalidad, eficiencia y diseño. Estos marcos no solo son funcionales, sino que también son seguros y estables. Los marcos como Django brindan seguridad contra varios errores de configuración de seguridad en las aplicaciones web. Algunos otros marcos de desarrollo web populares son: Web2Py, TurboGears, CherryPy, Bottle, etc. Python para automatización Python es un gran lenguaje para automatizar las tareas diarias de la computadora. Se pueden programar scripts simples en Python para automatizar las tareas aburridas regulares, lo que puede ahorrar mucho tiempo a los usuarios y aumentar su eficiencia y productividad en el trabajo. Los módulos de Python como PyAutoGUI se pueden usar para automatizar las tareas del teclado y el mouse. Las tareas diarias también se pueden revisar a través de estas tareas. Algunos módulos de Python populares utilizados en la automatización incluyen Selenium, BeautifulSoup, PyAutoGUI, Requests, JSON, etc. Python para aprendizaje automático e inteligencia artificial Python se ha convertido en el principal lenguaje de programación para modelos de aprendizaje automático e inteligencia artificial. Python proporciona la coherencia y la simplicidad necesarias para los modelos de IA y ML, seguidas de algunos de los mejores marcos. La sintaxis de Python es fácil de entender y significativa, lo que la hace ideal para proyectos de Inteligencia Artificial. Algunos marcos de Python populares para aprendizaje automático e inteligencia artificial incluyen TensorFlow, Torch, Skikit-Learn, Apache Singa, etc. Python para desarrollo de juegos Python no es un lenguaje ideal para desarrollar juegos debido a su baja velocidad. Sin embargo, tiene algunas buenas bibliotecas para el desarrollo de juegos como PyGame, Pyglet, Pandas3D, etc. que se pueden usar para desarrollar juegos de escritorio simples basados en GUI. La simplicidad de Python se puede utilizar como una ventaja para aprender los fundamentos del desarrollo de juegos. Después de aprender el desarrollo básico de juegos a través de Python, uno puede saltar a un lenguaje como C o C ++. Python para aplicaciones de escritorio Python es un lenguaje de programación interactivo con soporte para el desarrollo de GUI. Python proporciona varios marcos y módulos que se pueden usar para desarrollar aplicaciones de escritorio interactivas para múltiples sistemas operativos. Algunos de los mejores módulos de Python que brindan asistencia para el desarrollo de aplicaciones de escritorio incluyen PyQt, Tkinter, Kivy, PyGUI, etc. Python para la administración de redes Python también se puede utilizar para tareas de red complejas como administración de redes, automatización de redes, etc. Python es el lenguaje de programación líder para redes definidas por software. Python aumenta la eficiencia y la flexibilidad de los sistemas de red al facilitar su configuración y administración. Socket es uno de los módulos de Python más utilizados para tareas de red. Conclusión Python es un lenguaje de programación fácil de aprender, por eso, si está trabajando en cualquier proyecto en Python, no tiene que crear su propia función grande, puede usar módulos que ya han sido creados por otros desarrolladores. Python facilita el trabajo y la comprensión de Python es tan fácil como leer un párrafo en inglés.
  10. Hands-On Python GUI Programming using tkinter to build desktop applications What you'll learn Create amazing GUIs with Python's built-in Tkinter module Customize the GUIs by using layout managers to arrange the GUI widgets Build a contacts database GUI App Build a Currency Converter GUI App Build a Loan Calculator GUI App Build a Music Player GUI App Build a digital clock GUI App Build a video to mp3 converter GUI App Course content 7 sections • 73 lectures • 6h 39m total length Requirements Computer with internet access required. Basic knowledge of Python is advised. Description Python is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects. Tkinter is the de facto way in Python to create Graphical User interfaces (GUIs) and is included in all standard Python Distributions. In fact, it’s the only framework built into the Python standard library. This Python framework provides an interface to the Tk toolkit and works as a thin object-oriented layer on top of Tk. The Tk toolkit is a cross-platform collection of ‘graphical control elements’, aka widgets, for building application interfaces. Tkinter module provides Python users with a simple way to create GUI elements using the widgets found in the Tk toolkit. Tk widgets can be used to construct buttons, menus, data fields, etc. in a Python application. Once created, these graphical elements can be associated with or interact with features, functionality, methods, data or even other widgets. Tkinter provides various controls, such as buttons, labels and text boxes used in a GUI application. These controls are commonly called widgets. Who this course is for: Beginners to GUI App Development with Python [Hidden Content] [hide][Hidden Content]]
  11. Features Fast bruteforce Low RAM and CPU usage Open-Source Python [hide][Hidden Content]]
  12. itsMe

    Free Python Books

    A list of Python books in English that are free to read online or download. Table of Contents How the list got started What's in the list Why free books? Acknowledgments How to contribute List of free Python books Introductory Intermediate Advanced AI and Machine Learning Computer Science Software Engineering and best practices GUI Tools Web development Data science Science Jupiter Notebook Engineering Cryptography Games Lists of free Python books License [hide][Hidden Content]]
  13. Learn advanced Django concepts to build better & more resilient web applications. What you'll learn Django Proxy Models UnitTesting Models & Proxy Models Techniques for building the fundamentals of a Netflix-like service (except the actual video streaming) Implementing a 5-Star Rating in Django alone Generic Foreign Keys & Generic Relations for flexible model relations Implementing Tagged Items & Categories for Improved Content Discovery Creating the conditions for a machine learning model (the way the data is structured) Course content 14 sections • 56 lectures • 9h 33m total length Requirements 30 Days of Python (or equivalent python experience) Try Django (or equivalent Django experience) You know how to implement classes, functions, variables, iterators, and more in Python Description This is not a Netflix clone and not even close. Why? Netflix is a complex system of engineer that no one class could ever fully cover. If I told you that you could build a Netflix clone in less than 40 hours, I would be lying to you. Instead, this is a foundation of what a Netflix-like service could be. This foundation only matters as it serves a roadmap to understanding Django on a whole new level. Django is the most popular web framework in the world written in Python and for good reason: Django is incredibly simple and incredibly complex. Models, Views, Forms, User Auth and Templates are fundament to Django. After completing one of my Try Django series, you'll see that creating rich web applications is, well, pretty simple. Models map to database tables. Views essentially handle a url and render templates. Forms help validate data and templates are essentially HTML with a little programming built it. If the paragraph above is unclear, this course is not for you. Django's complexity comes with the layers of abstraction you can start to build within your projects. To me, these layers come from Generic Foreign Keys & Proxy Models. The complexity on the surface might be intimating (it was for me) but after you get familiar with them you'll come to find their complexity to be less daunting and potentially, no longer complex. The goal of this course is to introduce your to a number of concepts you may have never seen before while building the foundation for a service that could potentially grow into Netflix. Here's some topics we'll cover: Proxy Models Generic Foreign Keys Generic Relations Automated Unit Testing ManyToMany Fields vs Foreign Keys vs Generic Foreign Keys Through models for ManyToMany Reverse Relationships Creating a Rating System (user ratings) Complex Search Lookups with Q Lookups Re-usuable model receiver functions Custom template tag for rending a rating form and much more Who this course is for: Django Developers looking for a deeper dive into Django Model Capabilities Beginner Django Developers needing to better understand Testing in a practical use case. [Hidden Content] [hide][Hidden Content]]
  14. Description Setting up Python is the first step to becoming a Python programmer. In this course, you’ll learn how to download and install Python for Windows, macOS, and Ubuntu Linux and how to open Python’s Integrated Development and Learning Environment, IDLE. There are many ways to install Python. You can download official Python distributions from Python.org, install from a package manager, and even install specialized distributions for scientific computing, Internet of Things, and embedded systems. This course focuses on official distributions, as they’re generally the best option for getting started with learning to program in Python. This course can be enjoyed alone or as an accompaniment to Python Basics: A Practical Introduction to Python 3. In this course, you’ll learn how to: Install Python on Windows, macOS, and Linux Open IDLE, Python’s integrated development and learning environment [hide][Hidden Content]]
  15. Description The incredible amount of data on the Internet is a rich resource for any field of research or personal interest. To effectively harvest that data, you’ll need to become skilled at web scraping. The Python libraries requests and Beautiful Soup are powerful tools for the job. If you like to learn with hands-on examples and you have a basic understanding of Python and HTML, then this course is for you. Use requests and Beautiful Soup for scraping and parsing data from the Web Walk through a web scraping pipeline from start to finish Build a script that fetches job offers from the Web and displays relevant information in your console [Hidden Content] [hide][Hidden Content]]
  16. [Hidden Content]
  17. Learn Complete Practical Python Programming Language From Scratch, With Quizzes, Exercises, Projects What you'll learn Basics of Python Variables and Functions in Python Strings in Python Lists and Tuples in Python Dictionaries in Python Conditionals in Python Loops in Python Exceptions in Python Methods and Properties in Python GUI in Python API in Python Course content 1 section • 75 lectures • 5h 45m total length Requirements No Description Technology is progressing day by day and we have developed an unconscious dependency on it. With every passing day, we require the need for a new invention. This behavior induces humans to study computers, understand the language, develop programs, discover their unique features and, invent new things. With the developing programs, there is a need for programming language. Programming language consists of a set of instructions to produce output. These languages are basically used to implement algorithms. There are various types of programming languages like Java, SQL, JavaScript, C++, Python, etc. Today we are going to discuss Python programming language. Python is a general-purpose, high-level programming language with dynamic semantics and easy to learn syntax which is open for everyone to use. Python was made by a programmer named Guido Van Rossum in 1991. It got inspiration from other programming languages; however, it is convenient to use than any other programming language which makes learning feasible for beginners. Python is designed with code readability as its major priority. This allows the program to define its concepts in fewer lines. Its unique framework allows you to work speedily and efficiently. Reasons to choose Python? 1. Readable code Python has its major emphasis on code readability. The learnable syntax allows the program to write concepts without adding additional codes. Even if you are not a trained programmer, you can begin to start working on it. Practice and patience can lead you to become skillful. It is also easy to work in large development teams. Its readability allows you to work quickly without putting in the extra effort. 2. Machine learning Due to using its readability, applications written in other languages require easy to use scripting. Therefore, Python is considered a perfect choice for machine learning. 3. Open-source Python is an open-source programing language. Due to this feature, it has huge support as numerous people are working with the language on a regular basis. Being an open-source also benefits in cutting the cost significantly. There are several Python frameworks and tools that help in decreasing development time without increasing its cost. You can choose the tool according to your requirement. 4. Web development Python makes web development a lot easier and faster. A lot of websites are made based on the frameworks of Python e.g. Instagram, Pinterest, etc. This technology is designed for data visualization and data analysis. You can process data with the help of Python without putting in a lot of time and effort. 5. Productive coding environment This technology provides a more productive coding environment than any other programming language. Skilled coders and programmers are more organized and efficient while working with Python. 6. Beneficial in artificial intelligence Artificial intelligence is a massive development, it is designed to make the machines mimic the human brain that is capable of analyzing and making decisions. Python is used widely in artificial science for example, for image and vision recognition. 7. Popular Python has a well-defined career that is highly demanded in the industry today. The programmers can pursue their careers in a programming language as it is one of the most popular and highly-paid careers in the world. According to pay websites, a Python developer earns $76,526 on average per year, ranging from $58,000 to $107,000. Applications of Python Web applications Python is used to develop web applications. It provides libraries to deal with internet protocols such as HTML, XML, JSON, etc. it consists of frameworks and tools such as Pyramid, Flask, etc. to develop web designs. Software development It is used in software development by being a support language. It proves to be useful to build control, testing, etc. Business applications It has a huge rule in the field of business. This technology is used to build business models. They use it to build apps, analyze data, and create reliable applications. Graphics applications Python is an efficient programming language and is capable of creating user-friendly, unique, and creative UI designs. Numeric and scientific applications It can also build numeric and scientific applications on the basis of algorithms, logic, and Python’s frameworks and tools. Astropy, Pandas, and BioPython are some of the most popular scientific libraries. Images The technology is extremely beneficial in building web applications that can read images and edit them. Applications such as VPython, imgSeek are built using Python. Advantages and disadvantages of Python Before learning a new language it’s better to be aware of all of its advantages and disadvantages. Python has a couple of both, but let’s discuss the pros first. · Easy to learn Python is highly recommendable to beginners because of its easy to learn nature. Its syntax is much more similar to English which is why it’s very easy to use and does not require additional codes to express the concepts. · Increases productivity This is an extremely efficient technology as due to this; the programmers do not have to focus on understanding the code, and can directly solve the problem. As there is less code to input, there is less work to do. · Dynamic As soon as we run the code, Python detects the variables. The programmer does not have to deal with assigning the variables and their data types as the program is automatically designed to do so. · Interpreted language Python is an interpreted language; therefore, it can execute the codes. In case of any error, it stops the execution and reports the occurred error. · Open source Python has an open-source license. This allows the program to be downloaded, modified, and distributed all for free. This proves to be significant for the organizations as they can change the software according to their requirement and then use it as they suffice. · Extensive This technology is applied widely all over. It is vastly used by scientists, engineers, and mathematicians. It is used in most of the industries that require machine learning, data analyzing, data science, prototyping, etc. · Vast support Python’s standard library is massive and includes all the functions you might need. The rest can be imported from the Python package index. It consists of more than 200,000 packages. Disadvantages are as follows: · Slow speed As discussed before, Python is designed to execute the code line by line automatically. This makes the program to run slowly. Its dynamic feature also leads to slow speed. Therefore, Python can not be used where speed is an important factor. · Unsuitable for mobile development Python is not suitable for game development or mobile development as few mobile applications are built using Python. Weak memory efficiency is another cause of this disadvantage. · Runtime error It is designed in a way that does not require the programmer to define the variables. During this time, several bugs may occur and the program shows only one bug at a time. The programmer has to keep running additional tests in order to prevent errors during runtime. · Less memory efficient This program uses a large amount of memory which can become a hindrance in building web applications that require memory optimization. · Database access The program is easy to use and user-friendly but it does not work the same way when it comes to the database. The enterprises need good interaction with complex data and Python is not advanced in such a way and thus, is not used in large enterprises. Python vs C++ Python and C++ are one of the top two programming languages. Python is easier and more user-friendly, while C++ is far more complex. Python imitates English while C++ has a lot of syntax rules which makes Python easy for beginners to work on. Python is the best option to be considered for data science and machine learning while C++ is great for game development. The language used in Python is dynamically typed and is high-level while the latter has a statistically typed language which is more low-level. The former type has a small-sized code which makes rapid prototyping easier while the latter has a large-sized code and does not support rapid prototyping. Python vs JavaScript Differentiating between the two most popular languages, Python is much easier to read and learn due to its approachable syntax. JavaScript is quite a complex language in comparison. JavaScript has more capacity to handle multiple users than Python. Instagram and YouTube are popular examples of applications built on Python. In the future, fields like AI, ML, and data science are going to be more in demand and all of these fields have extensive use of Python which makes it more versatile than JavaScript. JavaScript is faster out of the two which makes it more performance-oriented. Moreover, Python is more of a scripting language while the latter is a web programming language. Former has a wider standard library while the latter is quite limited. All the programming languages have made their place in the technology world and each one of them has played their role in advancing the use and benefits of it. A lot of social media and web applications are based on these. The past has proven to be very useful that mad ways for new languages to enter with more benefits and applications which present a different future. If we look at the future of the popularity of these programming languages, then several platforms predict with reasonable statistics and facts that Python will continue to gain popularity in the coming years. Java will gain some popularity and then remain constant. JavaScript, C#, and C++ will lose popularity significantly. Conclusion Python is a widely used language in several fields. It is extremely beneficial and recommendable for learning for beginners. Python provides various decent career opportunities and a promising future. Viewing its pros and cons, it is logical to state that it is wise to pursue. Who this course is for: Students who want to learn Python Students who are starting into Programming Students who want to learn Python from Scratch Students who want to Master Python [Hidden Content] [hide][Hidden Content]]
  18. Python Obfuscator for FUD Python Code. Obfuscation Method List Obfustucators ( * = May cause Syntax Errors ) -=============- 0 /one_line/hex 1 /one_line/base64 2 /one_line/base32 3 /one_line/gunzip* 4 /one_line/rot13* 5 /cmd/command 6 /cmd/powershell 7 /cmd/powershellhidden [hide][Hidden Content]]
  19. Pycrate is a French word for qualifying bad wine. The present software library has nothing to do with bad wine, it is simply a Python library for manipulating various digital formats in an easy way. It is the glorious successor of libmich, which was started 8 years ago and served well. Changelog v0.5 beta1 Many additional support, mostly targeting telecom and core network signaling protocols: – pycrate_asn1rt: support of OER and COER thanks to Josef Nevrly, – pycrate_crypto: basic support for EAP and IKEv2, – pycrate_ether: support for MPLS and SCTP, – pycrate_mobile: support for the NAS 5G, ISUP, GTP-U, GTP-C, PFCP, SIM card protocols, – pycrate_diameter: basic support for IETF and 3GPP Diameter protocols. Integration of a testing and packaging CI/CD thanks to Ben Maddison. Many bug fixes and enhancements, including contributions from Ariel Tempelhof, andyvan-trabus, p1-ra, Ken Whitesell, Vadim Yanitskiy, Catena cyber, Gary Coulbourne, and l-we. [hide][Hidden Content]]
  20. pyMalleableC2 A Python interpreter for Cobalt Strike Malleable C2 profiles that allows you to parse, modify, build them programmatically and validate syntax. Supports all of the Cobalt Strike Malleable C2 Profile grammar starting from Cobalt Strike version 4.3. It’s not backwards compatible with previous Cobalt Strike releases. What are the differences between pyMalleableC2 and other projects of this nature? Parses profiles with Lark using eBNF notation. This approach is a lot more robust then user-defined regexes, templating engines, or similar methods. Turns profiles into an Abstract Syntax Tree (AST) which can then be reconstructed back into source code. Because of the above, pyMalleableC2 allows you to build profiles programmatically or modify them on the fly. Allows you to validate the syntax of Malleable C2 profiles (Does not perform runtime checks, see the warning below.) It has AI in the form of a lot of if statements. [hide][Hidden Content]]
  21. For Linux and Windows Email_with_attachment (For Gmail) [hide][Hidden Content]]
  22. peda PEDA – Python Exploit Development Assistance for GDB Key Features: Enhance the display of gdb: colorize and display disassembly codes, registers, memory information during debugging. Add commands to support debugging and exploit development (for a full list of commands use peda help): aslr — Show/set ASLR setting of GDB checksec — Check for various security options of binary dumpargs — Display arguments passed to a function when stopped at a call instruction dumprop — Dump all ROP gadgets in the specific memory range elfheader — Get headers information from debugged ELF file elfsymbol — Get non-debugging symbol information from an ELF file lookup — Search for all addresses/references to addresses which belong to a memory range patch — Patch memory start at an address with string/hexstring/int pattern — Generate, search or write a cyclic pattern to memory procinfo — Display various info from /proc/pid/ pshow — Show various PEDA options and other settings pset — Set various PEDA options and other settings readelf — Get headers information from an ELF file ropgadget — Get common ROP gadgets of binary or library ropsearch — Search for ROP gadgets in memory searchmem|find — Search for a pattern in memory; support regex search shellcode — Generate or download common shellcodes. skeleton — Generate python exploit code template vmmap — Get virtual mapping address ranges of section(s) in debugged process xormem — XOR a memory region with a key Changelog v1.2 Bug fixes [hide][Hidden Content]]
  23. What you'll learn Get tweets including content, username, date, url ... from Twitter without Api We will make Twitter Bot. With this bot you can tweet everytime automatically. We will send any kind of message ( text, image ...) to Telegram Application with Python. We will download playlists formated mp4 or mp3 from Youtube We will download videos formated mp4 or mp3 from Youtube Course content 4 sections • 24 lectures • 1h 59m total length Requirements Just basic level Python Knowledge You should be interested in coding Description We will scrape tweets on Twitter We will download more than the 3200 tweets that Twitter current limits. Including Date, Time, Number of Retweets, Number of Likes, Direct link to the Tweet, Tweet content and direct link to IMAGE or VIDEO file if that's what the content contains. We will download tweets to Csv file and Sql Server databases system. Maybe you can improve this code block and get users all tweets and analyzing him. Or you do basic application to some users this users interesting about cyryptocurrency and this users follow several twitter users. When these twitter users send a tweets about cyryptocurrency our users immadiately buy this cyryptocurrency. Your application may help this users. We will send message to Telegram with Python We will create a telegram bot using botFather. With this telegram bot we are going to enter any kind of chat platform then we will send text messages, image or document. Finally you can create a python script then you can get a message from remote. Maybe you can improve this code block and getting every change of blockchain and immediately you can information using telegram application. Or you can filter some famous twitter user like Elan Musk and if Elan Musk send tweet about dogy or bitcoin you can get information in seconds We will send tweets with Twitter Bot In this video series you will automatically signin and tweet about everything and than you can sing out from twitter. Maybe you can improve this code block and retweet every tweets or you like many tweets or delete users liked tweets or delete users all tweets. We will download videos and playlist from Youtube with Python We will download videos on format mp4 and format mp3 and also we will download playlist on format mp4 and format mp3. Maybe you can improve this code block and get all videos comments and also you can get videos description or like and unlike count. Who this course is for: Anyone interested in coding Anyone who wants to develop a project with Python [Hidden Content] Content: [hide][Hidden Content]]
  24. Obfustucators ( * = May cause Syntax Errors ) -=============- 0 /one_line/hex 1 /one_line/base64 2 /one_line/base32 3 /one_line/gunzip* 4 /one_line/rot13* 5 /cmd/command 6 /cmd/powershell 7 /cmd/powershellhidden [hide][Hidden Content]]
  25. This ia an simple and powerful stealer that steals victim credentials and send to your discord server... This File Steals: 1. Ip address 2. Screenshot 3. Discord token 4. Mac Address 5. System Information [hide][Hidden Content]]