piral
Pandas
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piral | Pandas | |
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18 | 393 | |
1,622 | 41,923 | |
2.0% | 1.4% | |
9.5 | 10.0 | |
3 days ago | 5 days ago | |
TypeScript | Python | |
MIT License | BSD 3-clause "New" or "Revised" License |
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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.
piral
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Micro frontend frameworks in 2024
Piral Framework - Focused on developer experience with features like a visual UI editor, live previews and hot module replacement. Ref - https://piral.io/
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Building a Large Scale Micro-frontend Application.
Micro-frontend applications have become increasingly popular among developers thanks to their many advantages. It helps create modular and maintainable applications capable of handling complex business needs. As with any technology, implementing micro-frontends poses challenges, such as ensuring consistent APIs. But, with tools like Piral, developers can easily create and scale micro-frontend applications.
- Micro frontend
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Microfrontends: Microservices for the Frontend
Piral: implements isolated components called pilets. Pilets are modules that bundle content and behavior.
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Versioning Web Components
I've prepared a demo project on the basis of Piral. The running demo can be found at the Piral samples organization on GitHub. Running the demo locally does not look very spectacular.
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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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Getting Started with Micro Frontends
3) Piral: Piral is a framework for next-gen portal applications.
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How we wrote our CLI integration tests
For the command line tooling of our micro frontend framework Piral we needed to be sure that it properly runs. This includes
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Writing "The Art Of Micro Frontends"
The idea of writing a book about micro frontends was born in mid 2019 when Piral was born out of smapiot's open-source efforts. We've been leading and assisting to micro frontend implementations for a while, and our intention was to put together an (almost) ideal pattern into an open-source framework.
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Donald Trump Hates It: Distributed Development Using Micro Frontends
Therefore, for the example, I've picked a rather fancy way to "loosely" get the micro frontends at runtime using a file called feed.json, which is created at build-time using the information which micro frontends (called pilets in this case, because I am using the Piral framework) are actually available. Therefore, just adding, e.g., a third micro frontend easily works without touching the app-shell package.
Pandas
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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.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
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What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
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How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
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10 Github repositories to achieve Python mastery
Explore here.
What are some alternatives?
single-spa - The router for easy microfrontends
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
Bit - A build system for development of composable software.
tensorflow - An Open Source Machine Learning Framework for Everyone
pixiv.moe - 😘 A pinterest-style layout site, shows illusts on pixiv.net order by popularity.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
luigi - Micro frontend framework
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Next.js - The React Framework
Keras - Deep Learning for humans
puzzle-js - ⚡ Micro frontend framework for scalable and blazing fast websites.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration