google-search-results-python
fastapi
google-search-results-python | fastapi | |
---|---|---|
4 | 470 | |
524 | 71,223 | |
3.8% | - | |
4.5 | 9.8 | |
3 months ago | 4 days ago | |
Python | Python | |
MIT License | MIT 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.
fastapi
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Github Sponsor Sebastián Ramírez Python programmer
He is probably most well know for creating FastAPI that I taught to some of my clients and Typer that I've never used.
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Python: A SQLAlchemy Wrapper Component That Works With Both Flask and FastAPI Frameworks
It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always.
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FastAPI Best Practices: A Condensed Guide with Examples
FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.
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Building an Email Assistant Application with Burr
In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.
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FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
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LangChain, Python, and Heroku
An API application framework (such as FastAPI)
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Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
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AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
What are some alternatives?
Scrapy - Scrapy, a fast high-level web crawling & scraping framework for Python.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
requests-html - Pythonic HTML Parsing for Humans™
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
pyspider - A Powerful Spider(Web Crawler) System in Python.
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
portia - Visual scraping for Scrapy
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
MechanicalSoup - A Python library for automating interaction with websites.
Flask - The Python micro framework for building web applications.
reader - A Python feed reader library.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.