MechanicalSoup
cheatsheets
MechanicalSoup | cheatsheets | |
---|---|---|
4 | 126 | |
4,555 | 7,238 | |
0.5% | 0.1% | |
5.9 | 7.0 | |
4 months ago | 11 days ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
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MechanicalSoup
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How to scrape a website with Python (Beginner tutorial)
MechanicalSoup is a Python library for web scraping that combines the simplicity of Requests with the convenience of BeautifulSoup. It's particularly useful for interacting with web forms, like login pages. Here's a basic example to illustrate how you can use MechanicalSoup for web scraping:
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Alternatives to Selenium?
Try with Mechanicalsoup https://mechanicalsoup.readthedocs.io/en/stable/
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What is the best library for website scraping?
You should try MechanicalSoup it uses Beautifulsoup but provides a simpler API using its StatefulBrowser filling forms and doing some other stuff is easier than just directly using requests and Beautifulsoup.
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Python for everyone : Mastering Python The Right Way
MechanicalSoup
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.
What are some alternatives?
Scrapy - Scrapy, a fast high-level web crawling & scraping framework for Python.
finplot - Performant and effortless finance plotting for Python
RoboBrowser
manim - A community-maintained Python framework for creating mathematical animations.
requests-html - Pythonic HTML Parsing for Humans™
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
pyspider - A Powerful Spider(Web Crawler) System in Python.
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
feedparser - Parse feeds in Python
Keras - Deep Learning for humans
portia - Visual scraping for Scrapy
geogebra - GeoGebra apps (mirror)