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Google Charts VS FastAPI

Compare Google Charts VS FastAPI and see what are their differences

Grapple
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google Charts logo Google Charts

Interactive charts for browsers and mobile devices.

FastAPI logo FastAPI

FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.
  • Google Charts Landing page
    Landing page //
    2023-05-10
  • FastAPI Landing page
    Landing page //
    2023-05-14

Google Charts features and specs

  • Easy Integration
    Google Charts can be easily integrated with web applications by adding a simple script tag and using JavaScript for customization.
  • Wide Variety of Chart Types
    Google Charts supports a wide range of chart types including line charts, bar charts, pie charts, and more, allowing for comprehensive data visualization.
  • Dynamic Data Handling
    The library allows for dynamic data handling and real-time updates, enabling interactive and responsive charts.
  • Cross-Browser Compatibility
    Google Charts is compatible with most modern browsers, ensuring a consistent experience across different platforms.
  • Customizable
    Offers extensive customization options such as modifying colors, labels, and tooltips, which allows developers to tailor visualizations to their specific needs.
  • Free to Use
    Google Charts is free to use, making it an appealing choice for developers looking for cost-effective data visualization solutions.
  • Comprehensive Documentation
    Provides extensive documentation and tutorials, which helps developers to quickly get started and resolve issues efficiently.

Possible disadvantages of Google Charts

  • Dependency on Google
    Requires an internet connection to fetch the Google Charts library, and performance can be affected if there are connectivity issues.
  • Limited Customization Compared to Alternatives
    Though customizable, it has fewer options and flexibility compared to other libraries like D3.js, which might be a limitation for advanced users.
  • Load Time
    The initial loading time of Google Charts can be slower compared to lightweight charting libraries due to the need to retrieve data from Google's servers.
  • Security Concerns
    As it relies on loading scripts from Google's servers, there might be security concerns in highly sensitive applications.
  • Not Open Source
    Google Charts is not open source, which might be a barrier for developers who prefer open-source solutions for greater control and transparency.
  • Limited Offline Support
    Static charts cannot be easily generated without an internet connection, limiting its use in offline applications.

FastAPI features and specs

  • High Performance
    Built on Starlette and Pydantic, FastAPI is one of the fastest frameworks for Python, providing high performance due to its asynchronous request handling.
  • Automatic Interactive API Documentation
    FastAPI automatically generates interactive API documentation via Swagger UI and ReDoc, which are very helpful for development and testing.
  • Type Checking and Validation
    With Pydantic models and Python type hints, FastAPI provides automatic data validation and type checking, reducing the chance of runtime errors.
  • Ease of Use
    Its syntax and design make it easy to learn for Python developers, offering a smooth development experience while reducing boilerplate code.
  • Asynchronous Support
    FastAPI supports asynchronous programming, allowing for better performance for I/O-bound operations, making it optimal for handling many simultaneous connections.
  • Extensive Documentation
    It has comprehensive and well-structured documentation, which is very useful for both beginners and advanced users.
  • Community and Ecosystem
    FastAPI has a growing community and ecosystem, with many plugins and integrations available to extend its functionality.

Possible disadvantages of FastAPI

  • Learning Curve for Asynchronous Programming
    Although FastAPI itself is easy to learn, grasping the concepts of asynchronous programming in Python can be challenging for beginners.
  • Complex Dependencies
    Using Pydantic for advanced validation can make the request models complex, requiring a deeper understanding of Pydantic and its functionalities.
  • Early Stage Libraries
    Some third-party libraries and extensions specifically tailored for FastAPI might still be in early stages of development and lack long-term stability.
  • Limited Real-World Examples
    Although the documentation is extensive, there might be limited real-world examples and case studies readily available compared to more mature frameworks.
  • Deployment Complexity
    Deploying FastAPI applications might be more complex in comparison to traditional synchronous frameworks, mainly due to the need for asynchronous server setups.

Analysis of Google Charts

Overall verdict

  • Google Charts is a highly recommended option for anyone seeking a robust, versatile, and free charting library. It combines ease of use with advanced capabilities, making it suitable for both beginners and experienced developers.

Why this product is good

  • Google Charts is a powerful and flexible tool for creating a variety of charts and graphs easily. It is well-suited for both simple and complex data visualizations, offering a wide selection of chart types. Moreover, it integrates smoothly with web applications and is highly customizable, allowing users to adjust the look and functionality to fit specific needs. The documentation provided by Google is extensive and helps users to quickly set up and utilize the tool effectively.

Recommended for

  • Web developers looking to add charts to their websites
  • Data analysts needing to visualize complex datasets
  • Business users seeking to create interactive dashboards
  • Educators and students who require data visualization for projects and presentations

Analysis of FastAPI

Overall verdict

  • FastAPI is widely regarded as a good choice, especially for applications that require high performance, scalability, and modern Python features. It is suitable for both simple and complex projects, making it a versatile tool in the web development ecosystem.

Why this product is good

  • FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. It is built on top of Starlette for web framework capabilities and Pydantic for data validation and settings management. FastAPI is known for its excellent performance, automatic generation of interactive API documentation (with Swagger and Redoc), and support for asynchronous programming. Developers appreciate its ease of use, detailed documentation, and helpful error messages.

Recommended for

  • Developers building RESTful APIs
  • Teams looking for a high-performance ASGI-based web framework
  • Projects that require asynchronous programming capabilities
  • Applications needing automatic generation of interactive API documentation
  • Python developers who prefer utilizing type hints for code clarity and validation

Google Charts videos

+ Add

Data Visualization for the Web Using Google Charts

More videos:

  • Review - Incorporating Google Charts in a FileMaker Solution | FileMaker Training
  • Review - Google Charts for Native Android Apps

FastAPI videos

+ Add

FastAPI from the ground up

More videos:

  • Tutorial - 30 Days of Python - Day 14 - Web App with Flask, FastAPI, ngrok, and Invictify - Python TUTORIAL
  • Review - [PT] Python - API com FastAPI - Chat | twitch.tv/codeshow

Category Popularity

0-100% (relative to Google Charts and FastAPI)

Google Charts

FastAPI

Data Dashboard
100 100%
Data Dashboard
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
API Tools
0 0%
API Tools
100% 100

User comments

Share your experience with using Google Charts and FastAPI. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Charts and FastAPI

Google Charts Reviews

15 JavaScript Libraries for Creating Beautiful Charts
Google Charts also comes with various customization options that help in changing the look of the graph. Charts are rendered using HTML5/SVG to provide cross-browser compatibility and cross-platform portability to iPhones, iPads, and Android. It also includes VML for supporting older IE versions.
Source: www.sitepoint.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Google Charts is an excellent choice for projects that do not require complicated customization and prefer simplicity and stability.
Source: hackernoon.com
A Complete Overview of the Best Data Visualization Tools
Google Charts is a powerful, free data visualization tool that is specifically for creating interactive charts for embedding online. It works with dynamic data and the outputs are based purely on HTML5 and SVG, so they work in browsers without the use of additional plugins. Data sources include Google Spreadsheets, Google Fusion Tables, Salesforce, and other SQL databases.
Source: www.toptal.com
The Best Data Visualization Tools - Top 30 BI Software
Google Charts runs on SVG and HTML5, aiming for Android, iOS and total cross-browser compatibility, including older versions of Internet Explorer. All of the charts you can create are interactive and you may be able zoom in on some of them. The site offers a fairly comprehensive gallery where you can find a variety of types of visualizations and interactions that you can use.
Source: improvado.io

FastAPI Reviews

  1. Kurslog team
    ยท Working at Kurslog ยท

    When our backend team needs to build services for data parsing, aggregators, or high-load APIs, FastAPI is our absolute go-to choice. It completely lives up to its name-development speed is outstanding.

    The combination of Pydantic for data validation and built-in async support keeps our shared codebase clean, strictly typed, and reliable. But the biggest highlight for our cross-functional team is the automatic generation of interactive OpenAPI (Swagger) documentation. Our frontend and mobile developers no longer have to wait for backend engineers to manually update API docs; everything stays perfectly in sync automatically. It has drastically improved our team's communication and delivery speed.

    ๐Ÿ Competitors: Django, Flask, ExpressJS, Nest.js, Spring Boot
    ๐Ÿ‘ Pros:    Blazing fast performance (on par with nodejs and go)|Native asynchronous support out of the box|Automatic, interactive documentation generation (swagger/redoc)|Strict typing and data validation with pydantic
    ๐Ÿ‘Ž Cons:    Smaller plug-and-play ecosystem compared to older frameworks like django|Requires our architects to design the project structure and directory layout from scratch
The 20 Best Laravel Alternatives for Web Development
FastAPI, as the name hints, is a swift mover. Built on Starlette, itโ€™s all about speed and performance with Python. Crafting API masterpieces at the speed of light, now thatโ€™s something.
Source: tms-outsource.com
25 Python Frameworks to Master
Since its release in 2018, it has rapidly gained popularity due to its great performance and simplicity. In fact, according to PyPi Stats, FastAPI has over 9 million monthly downloads, surpassing even full-stack frameworks like Django.
Source: kinsta.com
3 Web Frameworks to Use With Python
myapp/ is the main directory of your FastAPI application. It includes all the other files and directories needed for the application.static/ is a directory used to store static assets such as CSS, JavaScript, and image files. These assets are served directly by the web server and are typically used to add visual styling and interactivity to the application.css/, img/, js/...
Source: www.stratascratch.com
Best Alternatives to FastAPI App Free for Windows (2021)
FastAPI Alternative โ€“ So many alternatives app to FastAPI that you must to know out there. And, looking for an ideal software was not easy matter. Lucky you, at this page you can find the best replacement app for FastAPI. So what you are waiting for, get the latest FastAPI alternative app for Windows 10 from this page.
Source: alternativetoapp.com
Top 5 Back-End Frameworks to Consider for Web Development in 2021
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It is fast when compared to other major Python frameworks like Flask and Django. FastAPI gives great flexibility to fulfill businessesโ€™ API needs in todayโ€™s evolving world.
Source: www.fissionlabs.com

Social recommendations and mentions

Based on our record, FastAPI seems to be a lot more popular than Google Charts. While we know about 311 links to FastAPI, we've tracked only 10 mentions of Google Charts. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google Charts mentions (10)

  • The top 11 React chart libraries for data visualization
    This library leverages the robustness of Googleโ€™s chart tools combined with a React-friendly experience. It is ideal for developers familiar with Googleโ€™s visualization ecosystem. - Source: dev.to / almost 3 years ago
  • Using Images in a chart?
    I tried adding the images as labels and it didn't work. If this is possible at all, it would probably require Google Charts. Source: over 3 years ago
  • What are some good graph visualization libraries?
    Google's is a bit simpler to work with but more basic in terms of features https://developers.google.com/chart. Source: over 3 years ago
  • 5 Best Free JS Chart Libraries
    Google charts Https://developers.google.com/chart. - Source: dev.to / over 3 years ago
  • Suggestions for super simple QR code generator
    I did find a nice solution for Access forms where you can use a web browser control and developers.google.com/chart to render a QR code in that control based on the contents of other controls (textboxes, comboboxes, etc.,.). This would be perfect if it didn't a) rely on an active WAN connection and b) rely on that specific URL being active indefinitely. Source: about 4 years ago
View more

FastAPI mentions (311)

  • Shipping Sovereign SDK: Cryptographic Forensic Receipts and the End of the AI "Prose Tax"
    The Sovereign SDK is a Python-native framework designed to minimize prose overhead while generating ironclad, cryptographic execution receipts for AI agents, complete with drop-in FastAPI/Starlette ASGI middleware. - Source: dev.to / about 1 month ago
  • 5-Minute AI Jobs and Closed Tabs โ€” Why We Built Replay-Then-Tail SSE
    We had a feature in production where a single user request could run for five-plus minutes โ€” fetch documents, chunk them, hit an LLM per chunk, synthesize a final answer. We did the obvious thing first: a FastAPI handler that ran the pipeline and streamed progress back to the browser over Server-Sent Events. - Source: dev.to / 2 months ago
  • FastAPI With LangChain and MongoDB
    FastAPI is a Python framework for building APIs quickly, efficiently, and with very little code. - Source: dev.to / 3 months ago
  • I Built A " CrowdSense AI " : A Scalable, Context-Aware Platform for Smart Stadiums
    Backend: Python-based FastAPI for its asynchronous I/O capabilities and rapid JSON serialization. - Source: dev.to / 3 months ago
  • Async PyMongo in FastAPI
    FastAPI is a high-performance web framework that is production-ready and designed for building APIs in python, with roots embedded in asynchronous programming. It embraces Pythonโ€™s asyncio model as its core principle rather than treating it as optional. This design choice gives FastAPI leverage for I/O bound workloads such as db access, external API calls and real-time data streaming. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Google Charts and FastAPI, you can also consider the following products

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Flask - a microframework for Python based on Werkzeug, Jinja 2 and good intentions.

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

ExpressJS - Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Django - The Web framework for perfectionists with deadlines

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