Levenshtein
Scrapy
| Levenshtein | Scrapy | |
|---|---|---|
| 2 | 180 | |
| 1,239 | 50,954 | |
| - | 0.7% | |
| 0.0 | 9.6 | |
| over 2 years ago | 1 day ago | |
| C | Python | |
| GNU General Public License v2.0 or later | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Levenshtein
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Is it possible on Python?
Yeah my hunch is that a combination of nltk, python-Levenshtein, numpy for language processing, pandas for gathering results and scrapy for web scraping should make it possible. Sadly such a project probably requires at least a month or two worth of training in Python to prototype. Good luck OP.
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Four Useful Python Libraries You Don't Know About
I've used fuzzy-wuzzy and it is pretty slow if you can't install python-Levenshtein (which I couldn't, though I don't remember why). I ended up uninstalling it and using a custom matching algorithm for search in my app.
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.
1. https://scrapy.org
- 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?
fuzzywuzzy - Fuzzy String Matching in Python
requests-html - Pythonic HTML Parsing for Humans™
jellyfish - 🪼 a python library for doing approximate and phonetic matching of strings.
pyspider - A Powerful Spider(Web Crawler) System in Python.
TextDistance - 📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
colly - Elegant Scraper and Crawler Framework for Golang
chardet - Python character encoding detector
MechanicalSoup - A Python library for automating interaction with websites.
Charset Normalizer - Truly universal encoding detector in pure Python
playwright-python - Python version of the Playwright testing and automation library.
shortuuid - A generator library for concise, unambiguous and URL-safe UUIDs.
undetected-chromedriver - Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)