cheatsheets
Scrapy
cheatsheets | Scrapy | |
---|---|---|
126 | 180 | |
7,245 | 50,954 | |
0.2% | 0.7% | |
7.0 | 9.6 | |
14 days ago | 5 days ago | |
Python | Python | |
BSD 2-clause "Simplified" License | 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
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How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information.
- Matplotlib
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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Getting visual studio code to work with imported library
Name: matplotlib Version: 3.7.1 Summary: Python plotting package Home-page: https://matplotlib.org Author: John D. Hunter, Michael Droettboom Author-email: [email protected] License: PSFLocation: /home/huinker/.local/lib/python3.10/site-packages
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
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?
finplot - Performant and effortless finance plotting for Python
requests-html - Pythonic HTML Parsing for Humans™
manim - A community-maintained Python framework for creating mathematical animations.
pyspider - A Powerful Spider(Web Crawler) System in Python.
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
colly - Elegant Scraper and Crawler Framework for Golang
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
MechanicalSoup - A Python library for automating interaction with websites.
Keras - Deep Learning for humans
playwright-python - Python version of the Playwright testing and automation library.
geogebra - GeoGebra apps (mirror)
undetected-chromedriver - Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)