Python In ancient Greece[edit] In computing[edit] In media and entertainment[edit] In roller coasters[edit] In weaponry[edit] Colt Python, a .357 Magnum caliber revolverPython missile, a series of Israeli air-to-air missiles In other uses[edit] See also[edit] Pyton, a Norwegian adult humour magazine Announcements — IPython Books — IPython Install · Docs · Videos · News · Cite · Sponsors · Donate Versions Stable 2.3 – October 2014 Install Development 3.0.dev Github Notebook Viewer Share your notebooks Community Book For developers Support IPython Find out more... Books¶ IPython Cookbook¶ IPython Interactive Computing and Visualization Cookbookby Cyrille Rossant512 pagesPackt PublishingSeptember 25 2014 This is an advanced-level guide to IPython for data science, and the sequel of the IPython minibook. IPython Minibook¶ Learning IPython for Interactive Computing and Data Visualizationby Cyrille Rossant134 pagesPackt PublishingApril 25 2013 This is a beginner-level introduction to IPython for data analysis and numerical computing, covering NumPy, pandas, SciPy, and matplotlib. © Copyright the IPython development team.
IPython Books - IPython Cookbook IPython Interactive Computing and Visualization Cookbook This advanced-level book covers a wide range of methods for data science with Python: Interactive computing in the IPython notebook High-performance computing with Python Statistics, machine learning, data mining Signal processing and mathematical modeling Highlights 500+ pages100+ recipes15 chaptersEach recipe illustrates one method on one real-world exampleCode for Python 3 (but works fine on Python 2.7)All of the code freely available on GitHubContribute with issues and pull requests on GitHub This is an advanced-level book: basic knowledge of IPython, NumPy, pandas, matplotlib is required. Featured recipes A selection of free recipes from the book: Part I: Advanced High-Performance Interactive Computing Part I (chapters 1-6) covers advanced methods in interactive numerical computing, high-performance computing, and data visualization. Chapter 1: A Tour of Interactive Computing with IPython 2.1. Chapter 3: Mastering the Notebook
How to Download Files in Python - Python Code There is now a comment section below, check it out! Abdou Rockikz · 3 min read · Updated oct 2019 · General Python Topics Downloading files from the Internet is one of the most common daily tasks to perform on the Web. Also, it is important due to the fact that a lot of successful softwares allow their users to download files from the Internet. In this tutorial, you will learn how you can download files over HTTP in Python using requests library. Let's get started, installing required dependencies: pip3 install requests tqdm We gonna use tqdm module here just to print a good looking progress bar in the downloading process. Open up a new Python file and import: from tqdm import tqdm import requests Choose any file from the internet to download, just make sure it ends with a file (.exe, .pdf, .png, etc url = " buffer_size = 1024 res = requests.get(url, stream=True) Content-Length header parameter is the total size of the file in bytes.
How to Extract Weather Data from Google in Python - Python Code There is now a comment section below, check it out! Abdou Rockikz · 8 min read · Web Scraping As you may know, Web scraping is essentially extracting data from websites. Although, this is not the perfect and official way to get the actual weather for a specific location, because there are hundreds of weather APIs out there to use. Alright, let's get started, installing the required dependencies: pip3 install requests bs4 First, let's experiment a little bit, open up a Google search bar and type for instance: "weather london", you'll see the official weather, let's right click and inspect HTML code as shown in the following figure: Note: Google does not have its appropriate weather API, as it also scrapes weather data from weather.com, so we are essentially scraping from it. You'll be forwarded to HTML code that is responsible for displaying the region, day and hour, and the actual weather: Great, let's try to extract these information in a Python interactive shell quickly: Happy Scraping ♥
How to Encrypt and Decrypt Files in Python - Python Code There is now a comment section below, check it out! Abdou Rockikz · 5 min read · Updated oct 2019 · Ethical Hacking Encryption is the process of encoding an information in such a way that only authorized parties can access it. It is critically important because it allows you to securely protect data that you don't want anyone to see or access. In this tutorial, you will learn how to use Python to encrypt files or any byte object (also string objects) using cryptography library. We will be using symmetric encryption, which means the same key we used to encrypt data, is also usable for decryption. Let's start off by installing cryptography: pip3 install cryptography Open up a new Python file and let's get started: from cryptography.fernet import Fernet import os Fernet is an implementation of symmetric authenticated cryptography, let's start by generating that key and write it to a file: Generating and writing the key to a file: write_key() Let's load that key: key = load_key() Some message:
How to Build a Text Generator using Keras in Python - Python Code There is now a comment section below, check it out! Abdou Rockikz · 9 min read · Machine Learning · Natural Language Processing Recurrent Neural Networks (RNNs) are very powerful sequence models for classification problems. However, in this tutorial, we will use RNNs as generative models, which means they can learn the sequences of a problem and then generate entirely a new sequence for the problem domain. After reading this tutorial, you will learn how to build a LSTM model that can generate text (character by character) using Keras in Python. In text generation, we show the model many training examples so it can learn a pattern between the input and output. Getting Started Let's install the required dependencies for this tutorial: pip3 install tensorflow==1.13.1 keras numpy requests Importing everything: Preparing the Dataset We are going to use a free downloadable book as the dataset: Alice’s Adventures in Wonderland by Lewis Carroll. Now let's try to clean this dataset: Output: Conclusion
NumPy — NumPy Top 8 Python Libraries For Data Scientists and Machine Learning Engineers - Python Code There is now a comment section below, check it out! Abdou Rockikz · 7 min read · Updated sep 2019 · Machine Learning As you may already know, Python is a programming language that lets you work quickly and integrate systems more effectively. PandasMatplotlibNumpyScipySci-kit LearnTensorFlowTheanoKeras So, let's start with the first library, Pandas. 8. Pandas is a powerful python data analysis toolkit providing high-performance, easy to use library, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. Here are some main features of pandas: Definitely check it out! For more information, here is the official github page. 7. Matplotlib is a Python plotting library which produces figures in a variety of hardcopy formats and interactive environments across platforms. For simple plotting, the pyplot module provides a MATLAB-like interface, particularly when combined with IPython. 6. Check out the official github page. 5. 4.
How to Access Wikipedia in Python - Python Code There is now a comment section below, check it out! Abdou Rockikz · 3 min read · Web Scraping Wikipedia is no doubt the largest and most popular general reference work on the internet, it is one of the most popular websites. It features exclusively free content. I need to mention that we are not going to web scrap wikipedia pages manually, wikipedia module already did the tough work for us. pip3 install wikipedia Open up a Python interactive shell or an empty file and follow along. Let's get the summary of what Python programming language is: import wikipedia print(wikipedia.summary("Python Programming Language")) This will print some first sentences, we can specify the number of sentences to extract: In [2]: wikipedia.summary("Python programming languag", sentences=2) Out[2]: "Python is an interpreted, high-level, general-purpose programming language. Notice that I misspelled the query intentionally, it still gives me an accurate result. Search for a term in wikipedia search: All links:
How to Make a Network Scanner using Scapy in 5 Minutes - Python Code There is now a comment section below, check it out! Abdou Rockikz · 4 min read · Updated oct 2019 · Ethical Hacking · Packet Manipulation Using Scapy A network scanner is an important element for a network administrator as well as a penetration tester. It allows the user to map the network to find devices that are connected to the same network. In this tutorial, you will learn how to build a simple network scanner using scapy library in Python. I will assume you already have it installed, If it isn't the case, feel free to check my previous tutorial, or check the scapy's official documentation for installation. There are many ways out there to scan computers in a single network, but we are going to use one of the popular ways which is using ARP requests. First, we gonna need to import essential methods from scapy: from scapy.all import ARP, Ether, srp Second, we gonna need to make an ARP request as shown in the following image: The ARP response is demonstrated in the following figure: