mito
mathesar
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mito | mathesar | |
---|---|---|
18 | 53 | |
2,215 | 2,209 | |
3.1% | 5.6% | |
10.0 | 9.9 | |
9 days ago | about 21 hours ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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.
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 – 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 — 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
mathesar
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Show HN: Teable – Open-Source No-Code Database Fusion of Postgres and Airtable
Congratulations on launching, it's nice to see more open source products in this area (I work on https://mathesar.org/). Feel free to reach out if you'd like to talk and compare notes.
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A modern, open-source spreadsheet that goes beyond the grid
This is what we're trying to do with [Mathesar](https://github.com/centerofci/mathesar). We probably don't meet your needs yet because we don't support real-time concurrent editing, but we're actively working on the project and it is early days.
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Show HN: Visual DB – Airtable alternative for your own database
I'm an engineer on the Mathesar core team and I'd just like to clarify that Mathesar does support grouping to some extent. Here is a screenshot[1] that demonstrates the grouping functionality. Grouping levels are unlimited. You can play with this functionality on our live demo[2]. It's worth mentioning that Mathesar does not yet have the capability to expand and collapse groups, but that feature is planned[3].
Best of luck building Visual DB! Nice to see more innovation in this space!
[1]: https://mathesar.org/assets/crm-table-zoomed.png
[2]: https://demo.mathesar.org/
[3]: https://github.com/centerofci/mathesar/issues/475
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Ask HN: What’s the best GUI you’ve ever used for managing/querying databases?
I’m not sure if it’s okay to plug my project, but I work on Mathesar (https://github.com/centerofci/mathesar) which can be used as a Postgres GUI. We’re putting a lot of product/design effort into making it nice to use for non technical users.
Otherwise, I just use the command line.
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I'm So Frustrated Finding a NocoDB Alternative (Need a Postgres / SQL-Based Spreadsheet)
We're trying to do this with Mathesar: https://github.com/centerofci/mathesar. Some feedback would be great!
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Undb – open-source airtable alternative
We're trying to build a community driven project in this space - https://github.com/centerofci/mathesar. We just did our alpha release a couple of months ago.
I'm philosophically opposed to open core (Mathesar is run out of a non-profit), but I can see why other projects do it – finding funding for a big project like this is difficult without VCs (who expect returns).
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MS Access alternative?
I'm working on https://mathesar.org/ – it's an open source database solution built on Postgres, you can import data, connect to multiple databases, edit data and build reports. It can't connect to non-Postgres databases, so it may not work for you.
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Release announcement: Mathesar v0.1.2
We've just released Mathesar v0.1.2. Major new features are support for multiple databases in the UI and more options for installing Mathesar. We also made a bunch of smaller UX improvements and fixed a few bugs. Our full release notes are here: https://github.com/centerofci/mathesar/releases/tag/0.1.2
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I want to create sheets that work like Airtable (www.airtable.com) and use it in my django application any suggestions on how it can be done.
We did this for our open source project, Mathesar (https://github.com/centerofci/mathesar), which also uses Django. It's a lot of work. You can take a look at our code if it's helpful.
- Ask HN: What are Airtable alternatives with higher rate limits?
What are some alternatives?
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
nocodb - 🔥 🔥 🔥 Open Source Airtable Alternative
Mage - 🧙 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
Mattermost - Mattermost is an open source platform for secure collaboration across the entire software development lifecycle..
appsmith - Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.
apitable - 🚀🎉📚 APITable, an API-oriented low-code platform for building collaborative apps and better than all other Airtable open-source alternatives.
dtale - Visualizer for pandas data structures
budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes 🚀
trivy - Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
cost-model - Cross-cloud cost allocation models for Kubernetes workloads [Moved to: https://github.com/kubecost/opencost]