qiankun
Pandas
qiankun | Pandas | |
---|---|---|
6 | 399 | |
15,458 | 42,159 | |
0.8% | 1.0% | |
7.0 | 10.0 | |
14 days ago | 4 days ago | |
TypeScript | Python | |
MIT License | BSD 3-clause "New" or "Revised" License |
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qiankun
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Micro frontend frameworks in 2024
qiankun - enables you and your teams to build next-generation and enterprise-ready web applications leveraging Micro Frontends. It is inspired by and based on single-spa. Ref- https://github.com/umijs/qiankun
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There is framework for everything.
https://bit.dev/ https://piral.io/ https://github.com/umijs/qiankun https://github.com/single-spa/single-spa
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[AskJS] How to import React npm into Vue project
github qiankun
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Choosing a Micro Frontend Framework
Others: FrintJS, qiankun, Berial, and Nuz
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Let's Create A Web Application With Micro Frontends And Firebase
We will be using the package Qiankun (This is a micro frontend framework)
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Micro Frontends Patterns#14: Reading List
umijs/qiankun: 📦 🚀 Blazing fast, simple and completed solution for micro frontends.
Pandas
- The Birth of Parquet
- PDEP-13: The Pandas Logical Type System
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
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Pandas reset_index(): How To Reset Indexes in Pandas
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method.
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Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
What are some alternatives?
single-spa - The router for easy microfrontends
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
Next.js - The React Framework
tensorflow - An Open Source Machine Learning Framework for Everyone
icestark - :tiger: Micro Frontends solution for large application(面向大型应用的微前端解决方案),站点国内镜像:https://icestark.gitee.io
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Bit - A build system for development of composable software.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
luigi - Micro frontend framework
Keras - Deep Learning for humans
ilc - Enterprise-ready framework for Micro Frontends composition into SPA with SSR & i18n support
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration