lxml
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lxml | Scrapy | |
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17 | 180 | |
2,567 | 50,824 | |
1.1% | 1.1% | |
9.5 | 9.6 | |
12 days ago | 2 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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lxml
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8 Most Popular Python HTML Web Scraping Packages with Benchmarks
lxml
- Looking for someone to web scrape housing data needed research. Will pay you for your work!!
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13 ways to scrape any public data from any website
Parsel is a library build to extract data from XML/HTML documents with XPath and CSS selectors support, and could be combined with regular expressions. It's usees lxml parser under the hood by default.
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lazy and fast .mpd file parser - for video streaming
So, now that I no longer work in that industry, and I had some free time, I created a lazy parsing package using lxml instead of the xml parser in the standard library, which can help people who want to have a python only parsing solution.
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Guide to working with fancier XML documents with python?
Seriously, use LXML.
- There is framework for everything.
- how to find text in website ?
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Parsing XML file deletes whitespace. How to avoid it?
I got curious about this now so I did some tests on my own, and it appears that the XML parser implementation in Python does indeed strip all newline characters from attributes. Whether this is according to XML standard I do not know; I also briefly tried an alternative XML implementation for Python and it behaves the same, so I would assume that this is standard behavior, but I'm not knowledgable enough about XML to say for certain.
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Use case for ETL over ELT?
I use lxml for the XML parsing and pyodbc as the ODBC library. We have a small team so I just keep it as simple as possible: 1. A cursor yields the XML documents from a SQL query as a stream 2. A generator function parses the XML document and yields the rows (you could parallelize this step) 3. Stream each of the resulting rows to a single CSV file 4. Scoop up the resulting CSV file into the target database (usually with the DB engine's loader; bulk insert isn't so fast over ODBC) It ends up being a straight forward, low-overhead approach.
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CompactLogix: Implementing HTTP requests & XML Data Transfer via TCP/IP
If that sounds too weird maybe take a look at pycomm3, python also has lxml as well as requests. You could write a script that retrieves the data from the clx using the appropriate pycomm3 driver for cplx and then do xml things with the data using lxml and transmit the data over http using requests.
Scrapy
- Scrapy: A Fast and Powerful Scraping and Web Crawling Framework
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Seven Python Projects to Elevate Your Coding Skills
BeautifulSoup4 Scrapy
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What is SERP? Meaning, Use Cases and Approaches
While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects.
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Creating an advanced search engine with PostgreSQL
If you're looking for a turn-key solution, I'd have to dig a little. I generally write a scraper in python that dumps into a database or flat file (depending on number of records I'm hunting).
Scraping is a separate subject, but once you write one you can generally reuse relevant portions for many others. If you can get adept at a scraping framework like Scrapy you can do it fairly quickly, but there aren't many tools that work out of the box for every site you'll encounter.
Once you've written the spider, it's generally able to be rerun for updates unless the site code is dramatically altered. It really comes down to how brittle the spider is coded (i.e. hunting for specific heading sizes or fonts or something) instead of grabbing the underlying JSON/XHR that doesn't usually change frequently.
- Turning webpages into pdf
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Implementing case sensitive headers in Scrapy (not through `_caseMappings`)
Scrapy capitalizes headers for request
- Dicas para projetos usando web scraping
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Best tools to use for web scraping ??
Scrapy is a web scraping toolkit
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What do .NET devs use for web scraping these days?
I know this might not be a good answer, as it's not .NET, but we use https://scrapy.org/ (Python).
- I'm using python to scrape web page content and extract keywords, how can I make it faster to process?
What are some alternatives?
xmltodict - Python module that makes working with XML feel like you are working with JSON
requests-html - Pythonic HTML Parsing for Humans™
selectolax - Python binding to Modest and Lexbor engines (fast HTML5 parser with CSS selectors).
pyspider - A Powerful Spider(Web Crawler) System in Python.
html5lib - Standards-compliant library for parsing and serializing HTML documents and fragments in Python
colly - Elegant Scraper and Crawler Framework for Golang
untangle - Converts XML to Python objects
MechanicalSoup - A Python library for automating interaction with websites.
bleach - Bleach is an allowed-list-based HTML sanitizing library that escapes or strips markup and attributes
playwright-python - Python version of the Playwright testing and automation library.
pyquery - A jquery-like library for python
undetected-chromedriver - Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)