google-search-results-python
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google-search-results-python | Scrapy | |
---|---|---|
4 | 180 | |
514 | 50,824 | |
2.9% | 1.1% | |
4.5 | 9.6 | |
3 months ago | 1 day ago | |
Python | Python | |
MIT 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.
google-search-results-python
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Make Direct Async Requests to SerpApi with Python
In this blog post we'll cover on how to make direct requests to serpapi.com/search.json without using SerpApi's google-search-results Python client.
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Using Google Jobs Listing Results API from SerpApi
google-search-results is a SerpApi API package.
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Python Machine Learning
In previous weeks, we have implemented a way to automatically gather preprocessed and labelled data with SerpApi’s Google Images Scraper API, using Python library of SerpApi called Google Search Results in Python. We stored the scraped images in a local N1QL Couchbase Server in order to implement future asynchronous processes. N1QL is a good data model for bringing the power of SQL in JSON form. We store the images with their label names in the server and fetch them automatically whenever a machine learning training or testing process is in place. For now, label names represent the query made on SerpApi’s Google Images Scraper API, one query per each line. In the future we will add automatic gathering of missing queries in the datasets before the training.
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How to Train a Scalable Classifier with FastAPI and SerpApi ?
from multiprocessing.dummy import Array : It's an automatically added library for multiprocessing purposes from serpapi import GoogleSearch : It's SerpApi's library for using various engines SerpApi supports. You may find more information on its Github Repo. Simply install it via pip install google-search-results command. from pydantic import BaseModel : Pydantic allows us to create object models with ease. import mimetypes : Mimetypes is useful for guessing the extension of the downloaded element before you write it into an image. It allows us to guess .jpg, .png etc. extensions of files. import requests : Python's HTTP requests library with the coolest logo ever made for a library. import json : For reading and writing JSON files. It will be useful for storing old links of images we have already downloaded. import os : For writing images in local storage of the server, or creating folders for different queries.
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?
requests-html - Pythonic HTML Parsing for Humans™
pyspider - A Powerful Spider(Web Crawler) System in Python.
portia - Visual scraping for Scrapy
colly - Elegant Scraper and Crawler Framework for Golang
MechanicalSoup - A Python library for automating interaction with websites.
reader - A Python feed reader library.
playwright-python - Python version of the Playwright testing and automation library.
Grab - Web Scraping Framework
undetected-chromedriver - Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)