mito
appsmith
mito | appsmith | |
---|---|---|
18 | 233 | |
2,221 | 31,646 | |
1.0% | 1.3% | |
10.0 | 10.0 | |
14 days ago | about 23 hours ago | |
Python | TypeScript | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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mito
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The Design Philosophy of Great Tables (Software Package)
2. The report you're sending out for display is _expected_ in an Excel format. The two main reasons for this are just organizational momentum, or that you want to let the receiver conduct additional ad-hoc analysis (Excel is best for this in almost every org).
The way we've sliced this problem space is by improving the interfaces that users can use to export formatting to Excel. You can see some of our (open-core) code here [2]. TL;DR: Mito gives you an interface in Jupyter that looks like a spreadsheet, where you can apply formatting like Excel (number formatting, conditional formatting, color formatting) - and then Mito automatically generates code that exports this formatting to an Excel. This is one of our more compelling enterprise features, for decision makers that work with non-expert Python programmers - getting formatting into Excel is a big hassle.
[1] https://trymito.io
[2] https://github.com/mito-ds/mito/blob/dev/mitosheet/mitosheet...
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What codegen is (actually) good for
3. So you do want to do code-gen, does it make sense to do it in a chat interface, or can we do better?
As a Figma user, I'd answer these in the following way:
> Why is it necessary to generate code in the first place?
Because mockups aren't your production website, and your production website is written in code. But maybe this is just for now?
I'm sure some high-up PM at Figma has this as their goal - mockup the website in Figma, it generates the code for a website (you don't see this code!), and then you can click deploy _so easily_. Who wants to bet that hosting services like Vercel etc reach out to Figma once a week to try and pitch them...
In the meantime, while we have websites that don't fit neatly inside Figma constraints, while developers are easier to hire than good designers (in my experience), while no-code tools are continually thought of as limiting and a bad long-term solution -- Figma code export is good.
> Why is just writing the code by the hand not the best solution?
For the majority of us full-stack devs who have written >0 CSS but are less than masters, I'll leave this as self-evident.
> So you do want to do code-gen, does it make sense to do it in a chat interface, or can we do better?
In the case of Figma, if they were a new startup with no existing product and they were trying to "automation UI creation" -- v1 of their interface probably would be a "describe your website" and then we'll generate the code for it.
This would probably suck. What if you wanted to easily tweak the output? What if you had trouble describing what you wanted, but you could draw it (ok, OpenAI vision might help on this one)? What if you had experience with existing design tools you could use to augment the AI. A chat interface is not the best interface for design work.
ChatGPT-style code-generation is like v0.1. Github Copilot is an example of next step - it's not just a chat interface, it's something a bit more integrated into an environment that make sense in the context of the work you're doing. For design work, a canvas (literally! [2]) like Figma is well-suited as an environment for code-gen that can augment (and maybe one day replace) the programmers working on frontend. For tabular data work, we think a spreadsheet is the interface where users want to be, and the interface it makes sense to bring code-gen to.
Any thoughts appreciated!
[1] https://trymito.io, https://github.com/mito-ds/mito
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Pandas AI β The Future of Data Analysis
I think the biggest area for growth for LLM based tools for data analysis is around helping users _understand what edits they actually made_.
I'm a co-founder of a non-AI data code-gen tool for data analysis -- but we also have a basic version of an LLM integration. The problem we see with tooling like Pandas AI (in practice! with real users at enterprises!) is that users make an edit like "remove NaN values" and then get a new dataframe -- but they have no way of checking if the edited dataframe is actually what they want. Maybe the LLM removed NaN values. Maybe it just deleted some random rows!
The key here: how can users build an understanding of how their data changed, and confirm that the changes made by the LLM are the changes they wanted. In other words, recon!
We've been experimenting more with this recon step in the AI flow (you can see the final PR here: https://github.com/mito-ds/monorepo/pull/751). It takes a similar approach to the top comment (passing a subset of the data to the LLM), and then really focuses in the UI around "what changes were made." There's a lot of opportunity for growth here, I think!
Any/all feedback appreciated :)
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The hand-picked selection of the best Python libraries and tools of 2022
Mito β spreadsheet inside notebooks
- I made an open source spreadsheet that turns your edits into Python
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I made a tool that turns Excel into Python
You can see the open source code here.
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I made a Spreadsheet for Python beginners that writes Python for you
Here is the Github again.
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Learn Python through your Spreadsheet Skills
Mito is an open source Python package that allows the user to call an interactive spreadsheet into their Python environment. Each edit made in the spreadsheet generates the equivalent Python.
- A Spreadsheet for Data Science that Writes Python for Every Edit
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Mito lets you write Python by editing a spreadsheet
Mito is an open source Python tool that allows you to call a spreadsheet into your Python environment. Each edit you make in the spreadsheet generates the equivalent Python for you. This allows users to access Python with the spreadsheet skills they already have. Here is the Github
appsmith
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
appsmith β Low code project to build admin panels, internal tools, and dashboards. Integrates with 15+ databases and any API.
- Why I'm skeptical of low-code
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Building a signature capture widget with an Appsmith Iframe and SignaturePad.js
For instance, although we don't have a native signature capture widget (yet), you can easily build one with just a few lines of JavaScript, and the signaturePad.js library.
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How to build a Google Meet AI assistant app in 10 minutes without coding
Effective communication and efficient meeting management are key to a team's success in the modern workplace. Recognizing this, we will develop an AI-powered meeting assistant app to transform Google Meet recordings into automatically generated meeting notes with key takeaways and action items. The blog post is tailored for every creator from developers to no-coders who are interested in the intersection of AI and productivity tools. It's particularly useful for those with limited AI-development experience and who want to build AI applications by using simple low-code tools like Unbody and Appsmith.
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NoCode Newbie: Restaurant hoping to consolidate and reduce overhead
And if you don't need a mobile app and can get by with web only, check out Appsmith. It's open-source, can connect to Google Sheets, Airtable, and any API or database, and is free for unlimited users and apps. Feel free to DM me if you need a hand getting started with either one. I'm Joseph from the Appsmith Developer Relations team, and GreenFlux on the AppSheet forums.
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π₯π₯ Our awesome OSS friends π
Appsmith- Build build custom software on top of your data.
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Git in Appsmith: Every Developer Has Been Saved by Git β So, Why Isnβt it a Feature of App Platforms?
This wasn't an easy journey. While this functionality was in high demand, early versions were frustrating to use. In our earliest implementations, it wasn't even possible to pinpoint where the conflicts were in a file. Even members of the Appsmith development team would avoid using our early Git implementations. We even had a rule for our internal βHackathonsβ that using the Git feature was banned because it kept breaking! So we know why other app platforms had avoided fully implementing Git: it really was a challenge to get it working right.
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The Ultimate Guide to Building Internal Tools in 2024
Suggest features and help to guide Appsmithβs future: Appsmith's community keeps us at the forefront of internal tools with feature requests for the latest third-party integrations and robust community support.
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Asian hornet detector with Baserow and AppSmith! π
Ever tried building a responsive web application using AppSmith as the frontend and Baserow as the backend? Well, Frederik Duchi created a new set of videos showcasing the entire process! The videos include an interesting use case: reporting a nest of Asian hornets in an area. π€―
- Ask HN: Why did Visual Basic die?
What are some alternatives?
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
ToolJet - Low-code platform for building business applications. Connect to databases, cloud storages, GraphQL, API endpoints, Airtable, Google sheets, OpenAI, etc and build apps using drag and drop application builder. Built using JavaScript/TypeScript. π
Mage - π§ The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes π
dtale - Visualizer for pandas data structures
react-admin - A frontend Framework for building data-driven applications running on top of REST/GraphQL APIs, using TypeScript, React and Material Design
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
lux - Automatically visualize your pandas dataframe via a single print! π π‘
Directus - The Modern Data Stack π° β Directus is an instant REST+GraphQL API and intuitive no-code data collaboration app for any SQL database.
gradio - Build and share delightful machine learning apps, all in Python. π Star to support our work!
Strapi - π Strapi is the leading open-source headless CMS. Itβs 100% JavaScript/TypeScript, fully customizable and developer-first.