Parse The Web Using Python+Beautiful Soup
3 likes3,659 views
The document discusses using Python and Beautiful Soup to parse web pages. It provides an overview of Python including common data types like lists, tuples, and dictionaries. It then explains what Beautiful Soup is - a Python module for parsing HTML and XML. It shows examples of how to use Beautiful Soup to navigate, find, and extract data from elements in an HTML document.
1 of 36
Downloaded 157 times
Ad
Recommended
Perlのsmart match演算子
Perlのsmart match演算子ast_j 1. Smart matching allows comparing and matching scalars, arrays and hashes in Perl 5.10 and above.
2. For arrays, smart matching recursively compares corresponding elements and returns true only if all comparisons are true.
3. For hashes, it returns true if they have identical keys with matching values, allowing easy comparison of hashes.
Ruby Language: Array, Hash and Iterators
Ruby Language: Array, Hash and IteratorsSarah Allen The document explains the use of collections and iterators in Ruby, including how to loop using 'while' and 'times'. It covers creating and accessing arrays and hashes, as well as performing operations on them, such as merging hashes and manipulating array values using methods like 'each' and 'map'. Additionally, it showcases examples of conditional loops and various array and hash operations.
WordPress in 30 minutes
WordPress in 30 minutesOwen Winkler The document outlines a presentation on building a WordPress site in 30 minutes, emphasizing practical strategies rather than detailed instructions. It covers the necessary requirements, server setup, local development environment, and customization options for the site. The presentation also touches on deployment strategies, database management, and potential issues to consider during the process.
Ruby's Arrays and Hashes with examples
Ruby's Arrays and Hashes with examplesNiranjan Sarade The document provides information on arrays and hashes in Ruby. It discusses that arrays are ordered lists that can contain objects, and hashes are collections of key-value pairs. It then provides examples of creating, accessing, and modifying arrays and hashes. It also discusses various methods for iterating over arrays and hashes, such as each, collect, and each_pair.
Representing Material Culture Online: Historic Clothing in Omeka
Representing Material Culture Online: Historic Clothing in OmekaArden Kirkland The document discusses the Vassar College Costume Collection and its online presence through historicdress.org, showcasing historical clothing and material culture. It highlights various exhibitions and items available for browsing, including collections related to Vassar students' fashion and wedding wear over the decades. The document also provides links to related resources, databases, and contacts for further engagement.
كتاب ظلال العرش برواية ورش
كتاب ظلال العرش برواية ورشجمعية الإرشاد والإصلاح الخيرية الإسلامية The document contains a complex series of encoded messages and references that appear to focus on various topics, possibly including technical data and communication protocols. It is not structured in a conventional format, making it challenging to extract specific information without decoding the content further. Overall, the document seems to be a compilation of topics that may require specialized knowledge to interpret.
Conditionals, basic list manipulation and pattern matching
Conditionals, basic list manipulation and pattern matchingRich Price This document provides a summary of key concepts around conditionals, lists, and pattern matching in AI programming. It covers conditional statements like if/else and comparison operators. It also covers common list operations such as adding/changing elements, nested lists, and linked lists. Finally, it discusses pattern matching using operators like =, ==, ?, and ?? to flexibly match elements or sequences in lists. The document is intended to teach these fundamental programming concepts.
ゲーム理論BASIC 第13回 -ミニマックス定理-
ゲーム理論BASIC 第13回 -ミニマックス定理-ssusere0a682 The document presents the Minimax Theorem. It establishes that for zero-sum games, the maximum of the minimum payoffs for Player 1 equals the minimum of the maximum payoffs for Player 2. This is proven through a series of steps showing that for any strategies p1 and p2, the minimum payoff for Player 1 is less than or equal to their maximum payoff, and the maximum payoff for Player 2 is greater than or equal to their minimum payoff. Therefore, the optimal strategies for both players are equal and satisfy the Minimax equality.
bioinfolec_5th_20070713
bioinfolec_5th_20070713sesejun This document provides instructions and examples for using the NCBI Entrez API to search biomedical literature and retrieve gene and protein data. It demonstrates how to perform searches, get result summaries, link between data types (gene to protein), and save search histories using a variety of Entrez eUtils and passing parameters via cURL commands. The goal is to programmatically access and work with biomedical data from the NCBI Entrez database.
メタプログラミング入門
メタプログラミング入門Kent Ohashi This document defines a macro called my_macro in Clojure that takes a predicate and list of arguments and conditionally executes the arguments if the predicate returns true. It demonstrates calling my_macro with (= 1 2) which returns false and doesn't print "hello", but with (= 1 1) which returns true and prints "hello". It also shows compiling my_macro into a function that can be called directly later.
Pr 1
Pr 1GP G' Gandhinagar The document provides a summary of wastewater treatment processes. It describes how wastewater from mines and quarries is contaminated with high concentrations of particulate matter and dissolved solids. Treatment methods may include sedimentation basins, evaporation ponds, and reverse osmosis to remove contaminants and purify water for reuse or discharge.
Ruby nooks & crannies
Ruby nooks & cranniesKerry Buckley The document discusses Ruby's % notation for string interpolation and formatting. It shows examples of %, %Q, %q, %w, %W, %r, %s, %x, and % notation and what they return. It also discusses substring matching, blocks and procs, tap, and multiple assignment in Ruby.
سیرت مصطفٰی صلّی اللہ تعالٰی علیہ وسلّم_Seerat e Mustafa (saw)
سیرت مصطفٰی صلّی اللہ تعالٰی علیہ وسلّم_Seerat e Mustafa (saw)Ahmed@3604 This document contains contact information for various organizations and individuals, including phone numbers, emails, and addresses. It also includes some numbers, codes, and symbols that are difficult to interpret without more context.
New text document
New text documentAbdul Manan Hamza This document contains the code for a blood bank management system implemented as a doubly linked list in C++. It defines a node struct to store donor data and a blood class to implement linked list functions like insertion, deletion, searching by blood group or age, and displaying the list. The main function contains a menu loop to call the different blood class functions like insert, display, count donors, delete by position, etc. It also includes a logo class to display an intro screen and handle login functionality.
Secrets of a Low Carb Diet
Secrets of a Low Carb DietHtml Rell This document appears to be a Microsoft Word document containing formatted text and headings. It includes numbered lists, tables, and images. The document discusses secrets of a low carb diet and contains sections on contents, headings, body text, and tables. Formatting is applied throughout including different fonts, sizes, and styles.
Five
FiveŁukasz Langa This document discusses six Python packages that are useful to know:
1. First - A utility for selecting the first successful result from a sequence of functions.
2. Parse - A library for parsing Python format strings and extracting values.
3. Filecmp - A module for comparing files and directories.
4. Bitrot - A tool for detecting silent data corruption in files.
5. Docopt - A tool for generating command-line interfaces from a docstring.
6. Six - A library for writing code that is compatible with both Python 2 and Python 3.
cosc 281 hw3
cosc 281 hw3Brian Goggins This document contains C++ code that defines several functions to calculate approximations of mathematical expressions and exponential, trigonometric, and factorial functions using Taylor series up to a given order n. It then calls these functions in a main program to calculate and output specific approximations and errors compared to known values.
Python beautiful soup - bs4
Python beautiful soup - bs4Eueung Mulyana The document discusses Beautiful Soup, a Python library for parsing HTML and XML documents. It provides examples of how to use Beautiful Soup to extract data from HTML, including selecting tags, getting attribute values, and modifying tags. It also shows how to perform web scraping using Beautiful Soup and additional libraries, demonstrating how to scrape video data from a conference website.
Web Scraping is BS
Web Scraping is BSJohn D The document discusses web scraping using Python and the BeautifulSoup library. It provides an example Python script that scrapes news links from Hacker News and saves interesting links to Pocket. It then covers techniques for searching, filtering, and navigating HTML documents with BeautifulSoup.
Web Scraping With Python
Web Scraping With PythonRobert Dempsey This document discusses web scraping using Python. It provides an overview of scraping tools and techniques, including checking terms of service, using libraries like BeautifulSoup and Scrapy, dealing with anti-scraping measures, and exporting data. General steps for scraping are outlined, and specific examples are provided for scraping a website using a browser extension and scraping LinkedIn company pages using Python.
Web Scraping with Python
Web Scraping with PythonPaul Schreiber This document provides examples of web scraping using Python. It discusses fetching web pages using requests, parsing data using techniques like regular expressions and BeautifulSoup, and writing output to files like CSV and JSON. Specific examples demonstrated include scraping WTA tennis rankings, New York election board data, and engineering firm profiles. The document also covers related topics like handling authentication, exceptions, rate limiting and Unicode issues.
Scraping the web with python
Scraping the web with pythonJose Manuel Ortega Candel El documento presenta un taller sobre técnicas de scraping web utilizando Python, abordando bibliotecas como BeautifulSoup, Scrapy, Mechanize y Selenium. Se exploran metodologías para extraer datos de páginas web automáticamente, junto con ejemplos prácticos y el uso de expresiones XPath para la selección de elementos. También se menciona la instalación y configuración de herramientas necesarias para llevar a cabo estos procesos de extracción de datos.
Web scraping in python
Web scraping in python Viren Rajput This document discusses web scraping using Python, detailing its definition, purpose, and methods for extracting structured data from unstructured web content. It covers practical experience, tools such as BeautifulSoup and Scrapy, and highlights the importance of ethical considerations in scraping practices. The document concludes with a reminder to scrape responsibly and share knowledge, alongside links to the author's personal resources.
Beautiful soup
Beautiful soupmustafa sarac This document provides an introduction and overview of using BeautifulSoup to scrape and extract data from web pages and documents. It begins with an outline of the topics to be covered, which include downloading files, a example using BeautifulSoup to extract election results from an HTML table, using regular expressions, navigating the page structure, and extracting text from PDFs using pdfminer. The document then delves into each topic in more detail, providing code samples and explanations of how to implement various scraping techniques using BeautifulSoup and related Python libraries.
Intro to web scraping with Python
Intro to web scraping with PythonMaris Lemba This document is an introduction to web scraping using Python, presented at a Pyladies meetup. It covers essential considerations such as legal aspects, tools like the urllib and BeautifulSoup libraries for static scraping, and Selenium for dynamically generated content. The presentation includes examples of scraping race results from specific websites, detailing the process of locating data within HTML and handling AJAX-generated content.
Web Scraping Technologies
Web Scraping TechnologiesKrishna Sunuwar This document discusses web scraping technologies, detailing what scraping is and its purposes such as data extraction for business intelligence. It covers essential tools and libraries for web scraping, as well as challenges like server throttling and captcha. The document also provides tips for effective scraping and mentions applications like the Scrapy framework.
PyData: The Next Generation
PyData: The Next GenerationWes McKinney Wes McKinney gave a talk at Data Day Texas 2015 about the past, present, and future of the Python data analysis community and ecosystem, known as PyData. He discussed how Python became a popular language for data analysis due to tools like NumPy, pandas, scikit-learn, and IPython that enabled interactive exploration and modeling of data. However, Python was not initially well-suited for large-scale "big data" problems involving Hadoop and Spark. Recent developments in PySpark and improved integration of Python with big data frameworks have helped address this, but challenges remain in data structures, emerging formats, and open-sourcing of Python big data solutions.
Developing effective data scientists
Developing effective data scientistsErin Shellman The document discusses the essential skills and experiences for developing effective data scientists, emphasizing strong communication, coding practices, and exposure to diverse datasets. It includes advice from various data scientists on the importance of curiosity and interdisciplinary learning. Additionally, it provides actionable to-do's for both students and teachers to enhance data science education.
More Related Content
What's hot (9)
bioinfolec_5th_20070713
bioinfolec_5th_20070713sesejun This document provides instructions and examples for using the NCBI Entrez API to search biomedical literature and retrieve gene and protein data. It demonstrates how to perform searches, get result summaries, link between data types (gene to protein), and save search histories using a variety of Entrez eUtils and passing parameters via cURL commands. The goal is to programmatically access and work with biomedical data from the NCBI Entrez database.
メタプログラミング入門
メタプログラミング入門Kent Ohashi This document defines a macro called my_macro in Clojure that takes a predicate and list of arguments and conditionally executes the arguments if the predicate returns true. It demonstrates calling my_macro with (= 1 2) which returns false and doesn't print "hello", but with (= 1 1) which returns true and prints "hello". It also shows compiling my_macro into a function that can be called directly later.
Pr 1
Pr 1GP G' Gandhinagar The document provides a summary of wastewater treatment processes. It describes how wastewater from mines and quarries is contaminated with high concentrations of particulate matter and dissolved solids. Treatment methods may include sedimentation basins, evaporation ponds, and reverse osmosis to remove contaminants and purify water for reuse or discharge.
Ruby nooks & crannies
Ruby nooks & cranniesKerry Buckley The document discusses Ruby's % notation for string interpolation and formatting. It shows examples of %, %Q, %q, %w, %W, %r, %s, %x, and % notation and what they return. It also discusses substring matching, blocks and procs, tap, and multiple assignment in Ruby.
سیرت مصطفٰی صلّی اللہ تعالٰی علیہ وسلّم_Seerat e Mustafa (saw)
سیرت مصطفٰی صلّی اللہ تعالٰی علیہ وسلّم_Seerat e Mustafa (saw)Ahmed@3604 This document contains contact information for various organizations and individuals, including phone numbers, emails, and addresses. It also includes some numbers, codes, and symbols that are difficult to interpret without more context.
New text document
New text documentAbdul Manan Hamza This document contains the code for a blood bank management system implemented as a doubly linked list in C++. It defines a node struct to store donor data and a blood class to implement linked list functions like insertion, deletion, searching by blood group or age, and displaying the list. The main function contains a menu loop to call the different blood class functions like insert, display, count donors, delete by position, etc. It also includes a logo class to display an intro screen and handle login functionality.
Secrets of a Low Carb Diet
Secrets of a Low Carb DietHtml Rell This document appears to be a Microsoft Word document containing formatted text and headings. It includes numbered lists, tables, and images. The document discusses secrets of a low carb diet and contains sections on contents, headings, body text, and tables. Formatting is applied throughout including different fonts, sizes, and styles.
Five
FiveŁukasz Langa This document discusses six Python packages that are useful to know:
1. First - A utility for selecting the first successful result from a sequence of functions.
2. Parse - A library for parsing Python format strings and extracting values.
3. Filecmp - A module for comparing files and directories.
4. Bitrot - A tool for detecting silent data corruption in files.
5. Docopt - A tool for generating command-line interfaces from a docstring.
6. Six - A library for writing code that is compatible with both Python 2 and Python 3.
cosc 281 hw3
cosc 281 hw3Brian Goggins This document contains C++ code that defines several functions to calculate approximations of mathematical expressions and exponential, trigonometric, and factorial functions using Taylor series up to a given order n. It then calls these functions in a main program to calculate and output specific approximations and errors compared to known values.
Viewers also liked (20)
Python beautiful soup - bs4
Python beautiful soup - bs4Eueung Mulyana The document discusses Beautiful Soup, a Python library for parsing HTML and XML documents. It provides examples of how to use Beautiful Soup to extract data from HTML, including selecting tags, getting attribute values, and modifying tags. It also shows how to perform web scraping using Beautiful Soup and additional libraries, demonstrating how to scrape video data from a conference website.
Web Scraping is BS
Web Scraping is BSJohn D The document discusses web scraping using Python and the BeautifulSoup library. It provides an example Python script that scrapes news links from Hacker News and saves interesting links to Pocket. It then covers techniques for searching, filtering, and navigating HTML documents with BeautifulSoup.
Web Scraping With Python
Web Scraping With PythonRobert Dempsey This document discusses web scraping using Python. It provides an overview of scraping tools and techniques, including checking terms of service, using libraries like BeautifulSoup and Scrapy, dealing with anti-scraping measures, and exporting data. General steps for scraping are outlined, and specific examples are provided for scraping a website using a browser extension and scraping LinkedIn company pages using Python.
Web Scraping with Python
Web Scraping with PythonPaul Schreiber This document provides examples of web scraping using Python. It discusses fetching web pages using requests, parsing data using techniques like regular expressions and BeautifulSoup, and writing output to files like CSV and JSON. Specific examples demonstrated include scraping WTA tennis rankings, New York election board data, and engineering firm profiles. The document also covers related topics like handling authentication, exceptions, rate limiting and Unicode issues.
Scraping the web with python
Scraping the web with pythonJose Manuel Ortega Candel El documento presenta un taller sobre técnicas de scraping web utilizando Python, abordando bibliotecas como BeautifulSoup, Scrapy, Mechanize y Selenium. Se exploran metodologías para extraer datos de páginas web automáticamente, junto con ejemplos prácticos y el uso de expresiones XPath para la selección de elementos. También se menciona la instalación y configuración de herramientas necesarias para llevar a cabo estos procesos de extracción de datos.
Web scraping in python
Web scraping in python Viren Rajput This document discusses web scraping using Python, detailing its definition, purpose, and methods for extracting structured data from unstructured web content. It covers practical experience, tools such as BeautifulSoup and Scrapy, and highlights the importance of ethical considerations in scraping practices. The document concludes with a reminder to scrape responsibly and share knowledge, alongside links to the author's personal resources.
Beautiful soup
Beautiful soupmustafa sarac This document provides an introduction and overview of using BeautifulSoup to scrape and extract data from web pages and documents. It begins with an outline of the topics to be covered, which include downloading files, a example using BeautifulSoup to extract election results from an HTML table, using regular expressions, navigating the page structure, and extracting text from PDFs using pdfminer. The document then delves into each topic in more detail, providing code samples and explanations of how to implement various scraping techniques using BeautifulSoup and related Python libraries.
Intro to web scraping with Python
Intro to web scraping with PythonMaris Lemba This document is an introduction to web scraping using Python, presented at a Pyladies meetup. It covers essential considerations such as legal aspects, tools like the urllib and BeautifulSoup libraries for static scraping, and Selenium for dynamically generated content. The presentation includes examples of scraping race results from specific websites, detailing the process of locating data within HTML and handling AJAX-generated content.
Web Scraping Technologies
Web Scraping TechnologiesKrishna Sunuwar This document discusses web scraping technologies, detailing what scraping is and its purposes such as data extraction for business intelligence. It covers essential tools and libraries for web scraping, as well as challenges like server throttling and captcha. The document also provides tips for effective scraping and mentions applications like the Scrapy framework.
PyData: The Next Generation
PyData: The Next GenerationWes McKinney Wes McKinney gave a talk at Data Day Texas 2015 about the past, present, and future of the Python data analysis community and ecosystem, known as PyData. He discussed how Python became a popular language for data analysis due to tools like NumPy, pandas, scikit-learn, and IPython that enabled interactive exploration and modeling of data. However, Python was not initially well-suited for large-scale "big data" problems involving Hadoop and Spark. Recent developments in PySpark and improved integration of Python with big data frameworks have helped address this, but challenges remain in data structures, emerging formats, and open-sourcing of Python big data solutions.
Developing effective data scientists
Developing effective data scientistsErin Shellman The document discusses the essential skills and experiences for developing effective data scientists, emphasizing strong communication, coding practices, and exposure to diverse datasets. It includes advice from various data scientists on the importance of curiosity and interdisciplinary learning. Additionally, it provides actionable to-do's for both students and teachers to enhance data science education.
Scraping with Python for Fun and Profit - PyCon India 2010
Scraping with Python for Fun and Profit - PyCon India 2010Abhishek Mishra The document discusses web scraping using Python, specifically through tools like urllib2, BeautifulSoup, and Scrapy. It provides examples of scraping data, extracting information from HTML, and emphasizes the importance of making data available on the web. The presentation illustrates the challenges of obtaining consumable data online and offers solutions for efficient data extraction.
Bot or Not
Bot or NotErin Shellman The document details a workshop on data analysis using Python and PySpark, focusing on classifying bot behavior in Twitter data. It outlines an experimental design involving data ingestion, preprocessing, classification with various models, and evaluation metrics. Important results include the identification of bot patterns and the effectiveness of machine learning algorithms in distinguishing between human and bot accounts.
Learning Python from Data
Learning Python from DataMosky Liu The document provides a comprehensive guide to learning Python, including resources, fundamental concepts, and practical examples. It covers installation procedures, essential libraries, web scraping, and database interactions using SQLite, along with code samples for hands-on learning. Additionally, it offers recommendations for books and online documentation to enhance learners' understanding of Python programming.
Pyladies Tokyo meet up #6
Pyladies Tokyo meet up #6Katayanagi Nobuko PyLadies Tokyo meetup #6 「Python + Data = PyData ! PyLadies Tokyo データ祭！」 (http://pyladies-tokyo.connpass.com/event/15114/) の発表で用いた資料です。
Python, web scraping and content management: Scrapy and Django
Python, web scraping and content management: Scrapy and DjangoSammy Fung This document discusses using Python, Scrapy, and Django for web scraping and content management. It provides an overview of open data principles and describes how Scrapy can be used to extract structured data from websites. Scrapy spiders can be defined to scrape specific sites and output extracted data. Django is introduced as a web framework for building content management systems. The document demonstrates how Scrapy and Django can be integrated, with Scrapy scraping data and Django providing data models and administration. It also describes the hk0weather project on GitHub as an example that scrapes Hong Kong weather data using these tools.
2 5 1.一般化線形モデル色々_CPUE標準化
2 5 1.一般化線形モデル色々_CPUE標準化logics-of-blue 2013年8月10～11日にかけて北大函館キャンパス内で行われた統計勉強会の投影資料です。
2日目
2-5-1.一般化線形モデル色々～CPUE標準化～
ポアソン回帰を使ってCPUEを標準化する方法を解説します。
offset項やas.factorの使い方も解説。
サイト作ってます
http://logics-of-blue.com/
Ad
Similar to Parse The Web Using Python+Beautiful Soup (16)
Web Scrapping with Python
Web Scrapping with PythonMiguel Miranda de Mattos The document provides an overview of web scraping using Python, specifically through the BeautifulSoup and Mechanize libraries. BeautifulSoup is described as a tool for parsing HTML/XML, allowing for easy navigation and searching of tags, while Mechanize is used for stateful web browsing and form handling. The document includes code examples demonstrating how to use both libraries for web scraping tasks.
Python FDP self learning presentations..
Python FDP self learning presentations..chaitra742243 The document provides an overview of web scraping using Python, detailing essential libraries like Requests and BeautifulSoup for data extraction. It covers the processes of making HTTP requests, parsing HTML content, and using tools to automate data collection, with examples of form submissions and time series analysis. Additionally, it introduces regression techniques such as linear and logistic regression for data analysis.
Beautiful soup
Beautiful soupDeepakRaghavan4 Beautiful Soup is a Python library that allows users to parse HTML and XML documents, extract data from them, and modify the parse tree. It transforms complex documents into a tree of Python objects representing the document structure, including tags, strings, comments, and the document itself. The main objects are tags, strings, BeautifulSoup, and comments.
Python Crawler
Python CrawlerCheng-Yi Yu This document provides an overview of Python web crawling from beginner to intermediate level. It introduces Python basics like conditional statements, loops, arrays and dictionaries. It also covers built-in modules for handling JSON, XML, URLs, regular expressions. Popular web crawling packages like Requests, PyQuery, Beautiful Soup are demonstrated. Selenium for controlling browsers is explained. The document contains code examples and suggests hands-on workshops on scraping news sites and social media pages.
Sesi 8_Scraping & API for really bnegineer.pptx
Sesi 8_Scraping & API for really bnegineer.pptxKevinLeo32 The document discusses web scraping, a technique for automatically extracting data from websites, detailing its workflow and the useful libraries available such as BeautifulSoup, lxml, and Selenium. It highlights the legal considerations surrounding web scraping, emphasizing that while the action itself isn't illegal, extracting non-public data is against the law. Additionally, it explores the pros and cons of different parsing libraries, providing benchmarks on their performance.
From Writing to Publishing makesite.py - Sunaina Pai - PyCon UK 2018
From Writing to Publishing makesite.py - Sunaina Pai - PyCon UK 2018Sunaina Pai The document is a presentation about how the speaker wrote a static site generator called makesite.py in 120 lines of Python code. It then trended on Hacker News and GitHub after posting it as a "Show HN". The presentation walks through the code, including how it parses content and templates to generate pages and blogs. It achieved popularity by writing tests, documentation, and sharing it on GitHub and Hacker News, where it trended and received contributions from other developers.
Stupid Awesome Python Tricks
Stupid Awesome Python TricksBryan Helmig The document contains numerous creative Python tricks and examples showcasing various programming techniques, including custom encodings, magic methods, and peculiarities of the language. It highlights advanced features like slicing, indexing, and even constructing a mini Lisp interpreter. Overall, it serves as a humorous and insightful exploration into the capabilities and quirks of Python programming.
Prezdev parsing & crawling libs
Prezdev parsing & crawling libsadrienpad This document discusses and compares several Python libraries for web scraping and parsing HTML documents, including Beautiful Soup, html5lib, Scrapy, and Scrapy Shell. It notes that Beautiful Soup builds on lxml and html5lib, handles encoding, and provides methods to navigate and extract data from HTML. html5lib implements the WHATWG HTML5 specification. Scrapy allows writing rules to scrape sites and has built-in functionality for handling various aspects of crawling. Scrapy Shell provides an interactive shell for testing scrapers. The document questions why it isn't using some of these libraries and asks how Scrapy could be integrated with MRQ and how to implement proxy rotation.
Fun with Python
Fun with PythonNarong Intiruk This document discusses using Python to access and process web data. It covers using the Requests library to make HTTP requests and get web content, parsing web content with Beautiful Soup and JSON, and accessing web services using REST. Example code is provided for making GET and POST requests, extracting data from HTML and JSON responses, and creating a simple Flask web service.
Module-5 Ppt.pptx
Module-5 Ppt.pptxssuser44f56b1 This document discusses various techniques for working with networked programs in Python including sockets, HTTP, web scraping, parsing HTML and XML, and working with web services. It provides examples of writing a basic web browser, retrieving web pages and images over HTTP, parsing HTML using regular expressions and BeautifulSoup, reading binary files over HTTP, and parsing JSON. It explains concepts like sockets, web scraping, and using APIs to access data over the network from Python programs.
Crawler 2
Crawler 2Cheng-Yi Yu This document provides an overview of crawling from beginner to intermediate level. It covers topics such as installing Python and Node.js, basic syntax for Python and JavaScript, XML and JSON parsing, making HTTP requests, DOM parsing with libraries like Beautiful Soup and PyQuery, and using Selenium for browser automation. The document is intended as a tutorial and includes code examples for each topic. It also recommends some useful packages and provides links for installing additional tools and fonts.
TurboGears2 Pluggable Applications
TurboGears2 Pluggable ApplicationsAlessandro Molina This document discusses using pluggable applications with TurboGears2. It provides an overview of TurboGears2 features like object dispatch, declarative models, and XML template engines. It then demonstrates how to quickly start an application and explore options to add photo galleries, blogs, and wiki pages by plugging in additional applications and customizing templates and models.
Meta Buscadores
Meta Buscadorespechever The document discusses metasearch engines, which combine search queries across multiple search engines using their indices. It provides examples of code in Python for implementing a basic web search engine that crawls web pages, indexes keywords and URLs, looks up keywords in the index, and gets links from pages. It also includes links to resources about information retrieval systems and metasearch engines.
Unit 2_Crawling a website data collection, search engine indexing, and cybers...
Unit 2_Crawling a website data collection, search engine indexing, and cybers...ChatanBawankar Website crawling is the process of systematically navigating and extracting data from web pages using automated scripts, known as web crawlers (spiders or bots). Crawlers are widely used for data collection, search engine indexing, and cybersecurity testing.
HTML files in python.pptx
HTML files in python.pptxRamakrishna Reddy Bijjam This document discusses how to use the Beautiful Soup library in Python to parse HTML files and extract tag values. It covers installing Beautiful Soup, reading HTML files, extracting values from specific tags, extracting values from all instances of a tag, creating HTML files in Python, and viewing HTML files and web pages. Functions of the glob module like iglob(), glob(), and escape() are also discussed for filename pattern matching.
PART 3: THE SCRIPTING COMPOSER AND PYTHON
PART 3: THE SCRIPTING COMPOSER AND PYTHONAndrea Antonello The document provides a detailed guide on scripting in gvSIG using Python, aimed at users who are not developers. It covers various Python concepts, including variables, lists, dictionaries, string manipulation, file handling, and how to extract data from the web. The material is designed to empower users to create GIS automation scripts through the gvSIG scripting composer.
Ad
Recently uploaded (20)
Security Tips for Enterprise Azure Solutions
Security Tips for Enterprise Azure SolutionsMichele Leroux Bustamante Delivering solutions to Azure may involve a variety of architecture patterns involving your applications, APIs data and associated Azure resources that comprise the solution. This session will use reference architectures to illustrate the security considerations to protect your Azure resources and data, how to achieve Zero Trust, and why it matters. Topics covered will include specific security recommendations for types Azure resources and related network security practices. The goal is to give you a breadth of understanding as to typical security requirements to meet compliance and security controls in an enterprise solution.
10 Key Challenges for AI within the EU Data Protection Framework.pdf
10 Key Challenges for AI within the EU Data Protection Framework.pdfPriyanka Aash 10 Key Challenges for AI within the EU Data Protection Framework
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdfPriyanka Aash A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy
UserCon Belgium: Honey, VMware increased my bill
UserCon Belgium: Honey, VMware increased my billstijn40 VMware’s pricing changes have forced organizations to rethink their datacenter cost management strategies. While FinOps is commonly associated with cloud environments, the FinOps Foundation has recently expanded its framework to include Scopes—and Datacenter is now officially part of the equation. In this session, we’ll map the FinOps Framework to a VMware-based datacenter, focusing on cost visibility, optimization, and automation. You’ll learn how to track costs more effectively, rightsize workloads, optimize licensing, and drive efficiency—all without migrating to the cloud. We’ll also explore how to align IT teams, finance, and leadership around cost-aware decision-making for on-prem environments. If your VMware bill keeps increasing and you need a new approach to cost management, this session is for you!
PyCon SG 25 - Firecracker Made Easy with Python.pdf
PyCon SG 25 - Firecracker Made Easy with Python.pdfMuhammad Yuga Nugraha Explore the ease of managing Firecracker microVM with the firecracker-python. In this session, I will introduce the basics of Firecracker microVM and demonstrate how this custom SDK facilitates microVM operations easily. We will delve into the design and development process behind the SDK, providing a behind-the-scenes look at its creation and features. While traditional Firecracker SDKs were primarily available in Go, this module brings a simplicity of Python to the table.
Using the SQLExecutor for Data Quality Management: aka One man's love for the...
Using the SQLExecutor for Data Quality Management: aka One man's love for the...Safe Software The SQLExecutor is one of FME’s most powerful and flexible transformers. Pivvot maintains a robust internal metadata hierarchy used to support ingestion and curation of thousands of external data sources that must be managed for quality before entering our platform. By using the SQLExecutor, Pivvot can efficiently detect problems and perform analysis before data is extracted from our staging environment, removing the need for rollbacks or cycles waisted on a failed job. This presentation will walk through three distinct examples of how Pivvot uses the SQLExecutor to engage its metadata hierarchy and integrate with its Data Quality Management workflows efficiently and within the source postgres database. Spatial Validation –Validating spatial prerequisites before entering a production environment. Reference Data Validation - Dynamically validate domain-ed columns across any table and multiple columns per table. Practical De-duplication - Removing identical or near-identical well point locations from two distinct source datasets in the same table.
Coordinated Disclosure for ML - What's Different and What's the Same.pdf
Coordinated Disclosure for ML - What's Different and What's the Same.pdfPriyanka Aash Coordinated Disclosure for ML - What's Different and What's the Same
The Future of Technology: 2025-2125 by Saikat Basu.pdf
The Future of Technology: 2025-2125 by Saikat Basu.pdfSaikat Basu A peek into the next 100 years of technology. From Generative AI to Global AI networks to Martian Colonisation to Interstellar exploration to Industrial Nanotechnology to Artificial Consciousness, this is a journey you don't want to miss. Which ones excite you the most? Which ones are you apprehensive about? Feel free to comment! Let the conversation begin!
AI VIDEO MAGAZINE - June 2025 - r/aivideo
AI VIDEO MAGAZINE - June 2025 - r/aivideo1pcity Studios, Inc AI VIDEO MAGAZINE - r/aivideo community newsletter – Exclusive Tutorials: How to make an AI VIDEO from scratch, PLUS: How to make AI MUSIC, Hottest ai videos of 2025, Exclusive Interviews, New Tools, Previews, and MORE - JUNE 2025 ISSUE -
9-1-1 Addressing: End-to-End Automation Using FME
9-1-1 Addressing: End-to-End Automation Using FMESafe Software This session will cover a common use case for local and state/provincial governments who create and/or maintain their 9-1-1 addressing data, particularly address points and road centerlines. In this session, you'll learn how FME has helped Shelby County 9-1-1 (TN) automate the 9-1-1 addressing process; including automatically assigning attributes from disparate sources, on-the-fly QAQC of said data, and reporting. The FME logic that this presentation will cover includes: Table joins using attributes and geometry, Looping in custom transformers, Working with lists and Change detection.
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdfEarley Information Science As AI reshapes expectations in retail and B2B commerce, organizations are recognizing a critical reality: meaningful AI outcomes depend on well-structured, adaptable infrastructure. In this session, Seth Earley is joined by Phil Ryan - AI strategist, search technologist, and founder of Glass Leopard Technologies - for a candid conversation on what it truly means to engineer systems for scale, agility, and intelligence.
Phil draws on more than two decades of experience leading search and AI initiatives for enterprise organizations. Together, he and Seth explore the challenges businesses face when legacy architectures limit personalization, agility, and real-time decisioning - and what needs to change to support agentic technologies and next-best-action capabilities.
Key themes from the webinar include:
Composability as a prerequisite for AI - Why modular, loosely coupled systems are essential for adapting to rapid innovation and evolving business needs
Search and relevance as foundational to AI - How techniques honed-in enterprise search have laid the groundwork for more responsive and intelligent customer experiences
From MDM and CDP to agentic systems - How data platforms are evolving to support richer customer context and dynamic orchestration
Engineering for business alignment - Why successful AI programs require architectural decisions grounded in measurable outcomes
The conversation is practical and forward-looking, connecting deep technical understanding with real-world business needs. Whether you’re modernizing your commerce stack or exploring how AI can enhance product discovery, personalization, or customer journeys, this session provides a clear-eyed view of the capabilities, constraints, and priorities that matter most.
You are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to productionMichele Leroux Bustamante We live in an ever evolving landscape for cyber threats creating security risk for your production systems. Mitigating these risks requires participation throughout all stages from development through production delivery - and by every role including architects, developers QA and DevOps engineers, product owners and leadership. No one is excused! This session will cover examples of common mistakes or missed opportunities that can lead to vulnerabilities in production - and ways to do better throughout the development lifecycle.
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdfFwdays Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself.
In this talk, I’ll share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks.
Wenn alles versagt - IBM Tape schützt, was zählt! Und besonders mit dem neust...
Wenn alles versagt - IBM Tape schützt, was zählt! Und besonders mit dem neust...Josef Weingand IBM LTO10
Mastering AI Workflows with FME by Mark Döring
Mastering AI Workflows with FME by Mark DöringSafe Software Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FME’s powerful tools for training, optimization, and seamless integration
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...Fwdays Let's talk about our history. How we started the project with a small vector database of less than 2 million records. Later, we received a request for +100 million records, then another +100... And so gradually we reached almost 1 billion. Standard tools were quickly running out of steam - we were running into performance, index size, and very limited resources. After a long series of trials and errors, we built our own low-cost cluster, which today stably processes thousands of queries to more than 1B vectors.
Raman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech EnthusiastRaman Bhaumik A Junior Software Developer with a flair for innovation, Raman Bhaumik excels in delivering scalable web solutions. With three years of experience and a solid foundation in Java, Python, JavaScript, and SQL, she has streamlined task tracking by 20% and improved application stability.
Techniques for Automatic Device Identification and Network Assignment.pdf
Techniques for Automatic Device Identification and Network Assignment.pdfPriyanka Aash Techniques for Automatic Device Identification and Network Assignment
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdf
GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdfPriyanka Aash GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now
You are not excused! How to avoid security blind spots on the way to production
You are not excused! How to avoid security blind spots on the way to productionMichele Leroux Bustamante