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Take any Python code and build a dynamic GUI on top of it by dragging and dropping components. Python is already the most popular language in the world. This makes it even better! The attached video is only 45 seconds. It will show you how it works. Here is... show more

Santiago

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155,179 görüntüleme • 1 yıl önce •via X (Twitter)

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Roman B. 🇺🇦 profil fotoğrafı

Roman B. 🇺🇦1 yıl önce

I bookmark way to many of your post 😁

Santiago profil fotoğrafı

Santiago1 yıl önce

That's good. It means I'm doing a good job of bringing you things that you think are useful 😉

DatJot profil fotoğrafı

DatJot1 yıl önce

When you have Tableau + Power BI at the fraction of the cost, IMHO, it is not worth the price tag. Don't get me wrong, it looks nice, but I am trying to figure out why someone would switch from Tableau to Taipy with that type of price tag. Does the Community Edition have the designer? Does not appear to have the designer. Maybe there is something I am missing but I don't see a WOW factor compared to software like Tableau that would make me switch products.

whynesspower ⟠ profil fotoğrafı

whynesspower ⟠1 yıl önce

From the looks of it Rip streamlit and gradio

JoJo Ventures profil fotoğrafı

JoJo Ventures1 yıl önce

Nice share, this is really good. It would be amazing if the drag-and-drop GUI feature could be applied to @streamlit and @Gradio too, so data scientists could focus on the ML model and dataset instead.

Tomer Nosrati profil fotoğrafı

Tomer Nosrati1 yıl önce

Have you seen @anvil_works ? It appears to be a more robust implementation of a GUI designer for Python.

Haider. profil fotoğrafı

Haider.1 yıl önce

you think this kind of tool could be used to create more user-friendly interfaces for complex Python libraries or frameworks?

Santiago profil fotoğrafı

Santiago1 yıl önce

Yes, that's exactly the goal. You have some Python code that you want to make accessible through an interface. Instead of having to learn HTML/CSS, etc, you can use Taipy Designer to build an interface for it.

MasterChief profil fotoğrafı

MasterChief1 yıl önce

Machine learning apps

Hesam profil fotoğrafı

Hesam1 yıl önce

This is a killer data science tool! Already there are amazing libraries to add visuals to the data but this is fascinating 🔥

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Forget about HTML, JavaScript, and CSS. You can build AI and data applications using Python alone! Python is the best programming language out there. You can now use it across the stack. Take a look at Taipy, an open-source Python library to build end-to-end production applications. Star their repository: I recorded a quick video showing how to build a simple chat interface to talk to OpenAI GPT-3.5 using Taipy alone. Something important to keep in mind: Taipy's goal is not to replace web developers but to provide an alternative to those who need to build applications without web experience. If you are a data scientist or someone dealing with data, Taipy will simplify your life considerably. Thanks to the team behind Taipy for collaborating with me on this post. Here is a link to the full demo. Download this code and run it. It takes 30 seconds:

Forget about HTML, JavaScript, and CSS. You can build AI and data applications using Python alone! Python is the best programming language out there. You can now use it across the stack. Take a look at Taipy, an open-source Python library to build end-to-end production applications. Star their repository: I recorded a quick video showing how to build a simple chat interface to talk to OpenAI GPT-3.5 using Taipy alone. Something important to keep in mind: Taipy's goal is not to replace web developers but to provide an alternative to those who need to build applications without web experience. If you are a data scientist or someone dealing with data, Taipy will simplify your life considerably. Thanks to the team behind Taipy for collaborating with me on this post. Here is a link to the full demo. Download this code and run it. It takes 30 seconds:

Santiago

233,866 görüntüleme • 2 yıl önce

Python is the best language in the world. Today, you can build AI and data applications using Python alone! No HTML or JavaScript necessary. Take a look at Taipy, an open-source Python library to build end-to-end production applications. Star their repository: I recorded a quick video showing how to build a simple chat interface to talk to OpenAI GPT-3.5 using Taipy alone. Something important to keep in mind: Taipy's goal is not to replace web developers but to provide an alternative to those who need to build applications without web experience. If you are a data scientist or someone dealing with data, Taipy will simplify your life considerably. Thanks to the team behind Taipy for collaborating with me on this post. Here is a link to the full demo. Download this code and run it. It takes 30 seconds:

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Santiago

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Bindu Reddy

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Santiago

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Santiago

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Santiago

43,931 görüntüleme • 7 ay önce

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Santiago

107,878 görüntüleme • 3 ay önce

Are interactive essays the future of education? I asked Claude Code to build an interactive essay for PCA + SVD that works client side. Notice how python code executes and graphs are generated WITHOUT any backend! Play with it yourself 👇

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Paras Chopra

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Markdown was doomed from the start. It's just a format with low information density. HTML is better for humans, and agents can now consume and produce it without issues. But nobody wants to type HTML, so here is an alternative: This is an open-source tool for generating dashboards from data without writing a single HTML tag. You define your dashboard in YAML or TSK, and the tool will serve the HTML file for you. It comes with skills for Claude Code and Codex, so they know how to build these dashboards. And you can connect this to Postgres, MySQL, Snowflake, BigQuery, Redshift, Databricks, and many other databases. Repo link below.

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Santiago

86,275 görüntüleme • 1 ay önce

The hard part of building is no longer writing code. Code is easy. Nobody wins by writing more code or doing it faster. If you want to win, you need better thinking. There are a ton of startups focusing on using AI to write more code. I think they are missing the plot. We need a mental shift. We need tools that help us think faster, make better decisions, and focus on the right problems. I want you to check out Atoms because they are doing exactly this. They don't focus on the code, but on helping you build the right structure: 1. It starts by deep-researching marketing insights 2. It turns that into an execution plan 3. It builds both frontend and backend 4. It helps with deployment, SEO, growth, and analytics More importantly, it specializes in the core components you need to build and sell software online: • Authentication flows • Stripe payments • Infrastructure Their goal here is not to be another autocomplete tool or a copilot to help you write software. Their goal is to become a "vibe business team" that helps you build a business from the ground up. Here is a link for you to check them out: Thanks to the team for helping me onboard on the platform and collaborating with me on the post.

The hard part of building is no longer writing code. Code is easy. Nobody wins by writing more code or doing it faster. If you want to win, you need better thinking. There are a ton of startups focusing on using AI to write more code. I think they are missing the plot. We need a mental shift. We need tools that help us think faster, make better decisions, and focus on the right problems. I want you to check out Atoms because they are doing exactly this. They don't focus on the code, but on helping you build the right structure: 1. It starts by deep-researching marketing insights 2. It turns that into an execution plan 3. It builds both frontend and backend 4. It helps with deployment, SEO, growth, and analytics More importantly, it specializes in the core components you need to build and sell software online: • Authentication flows • Stripe payments • Infrastructure Their goal here is not to be another autocomplete tool or a copilot to help you write software. Their goal is to become a "vibe business team" that helps you build a business from the ground up. Here is a link for you to check them out: Thanks to the team for helping me onboard on the platform and collaborating with me on the post.

Santiago

78,872 görüntüleme • 5 ay önce

If you could only learn one thing that will be relevant for the next 10-20 years, focus on learning how to deal with data. The future is not about faster hardware, smarter algorithms, or better ideas. The future is about DATA, and those who know how to deal with it will stay relevant much longer than anyone else. I recorded a video to show you how easy it is to get started. In the video, I'm using Kestra. For a long time, I was a fan of AirFlow. Then, I moved to AWS Step Functions. Today, I only use Kestra. Kestra is open-source (repo link below) and kind enough to sponsor my work. The video will show you how easy it is to do the following: 1. Run Kestra locally (literally, one command) 2. Build a simple flow 3. Run Python scripts as part of your flow 4. Connect to HuggingFace models If you have never built a data pipeline, open Kestra's Quick Start Guide and follow their examples. (I think it will take you one weekend to feel comfortable with the application and build the courage you need to get into more serious work.)

If you could only learn one thing that will be relevant for the next 10-20 years, focus on learning how to deal with data. The future is not about faster hardware, smarter algorithms, or better ideas. The future is about DATA, and those who know how to deal with it will stay relevant much longer than anyone else. I recorded a video to show you how easy it is to get started. In the video, I'm using Kestra. For a long time, I was a fan of AirFlow. Then, I moved to AWS Step Functions. Today, I only use Kestra. Kestra is open-source (repo link below) and kind enough to sponsor my work. The video will show you how easy it is to do the following: 1. Run Kestra locally (literally, one command) 2. Build a simple flow 3. Run Python scripts as part of your flow 4. Connect to HuggingFace models If you have never built a data pipeline, open Kestra's Quick Start Guide and follow their examples. (I think it will take you one weekend to feel comfortable with the application and build the courage you need to get into more serious work.)

Santiago

51,012 görüntüleme • 1 yıl önce

English is the most powerful language in the world. MongoDB just added support for MCP, and literally anyone can now query data without knowing anything about databases. If you know English, you are all set. I recorded a quick video to show you how I connect to a sample Airbnb database and run different queries: • How many listings? • How many listings in the US? • What's the list of countries in these listings? It takes 10 seconds to configure Claude, Cursor, WindSurf, or any other AI assistant to connect to MongoDB's MCP Server. By the way, the server supports much more than queries: • You can explore your collections • You can fetch schema information • You can generate app code snippets • You can manage your databases • You can handle cluster/user/admin tasks Here is a link to the MCP server GitHub repository: This is huge for developers. It's even bigger for non-developers. Thanks to the MongoDB team for collaborating with me on this post.

English is the most powerful language in the world. MongoDB just added support for MCP, and literally anyone can now query data without knowing anything about databases. If you know English, you are all set. I recorded a quick video to show you how I connect to a sample Airbnb database and run different queries: • How many listings? • How many listings in the US? • What's the list of countries in these listings? It takes 10 seconds to configure Claude, Cursor, WindSurf, or any other AI assistant to connect to MongoDB's MCP Server. By the way, the server supports much more than queries: • You can explore your collections • You can fetch schema information • You can generate app code snippets • You can manage your databases • You can handle cluster/user/admin tasks Here is a link to the MCP server GitHub repository: This is huge for developers. It's even bigger for non-developers. Thanks to the MongoDB team for collaborating with me on this post.

Santiago

44,818 görüntüleme • 11 ay önce

An LLM with native access to find and run agents is a huge thing! This large language model (called ASI:One and developed by Fetch.ai) can do this natively when you show it a problem: • Reason about the problem • Identify live agents and tools that can help solve it • Dynamically invoke these agents and tools Honestly, this is pretty nuts! You don't need to set up anything beforehand. You don't need to write any code. Here is the best part: ASI:One has access to any agent published on Agentverse, an open directory of agents! This gives the model access to *millions* of tools it can execute dynamically when solving a task. Here is a simple example (the one in the attached video): • I went to Google Maps • I copied the latitude and longitude of a location • I asked ASI:One about relevant places around that location • ASI:One went to the marketplace • It identified and called the Google Places agent • It returned a list of museums, restaurants, and landmarks near my location Pretty awesome! You can try this now by going to You don't need to pay or register to test it out. If you want to get ideas of what's possible, check Agentverse, the agent marketplace: The model will have access to all of those tools. This is pretty awesome and opens up a whole new world of possibilities! Thanks to the team for partnering with me on this post!

An LLM with native access to find and run agents is a huge thing! This large language model (called ASI:One and developed by Fetch.ai) can do this natively when you show it a problem: • Reason about the problem • Identify live agents and tools that can help solve it • Dynamically invoke these agents and tools Honestly, this is pretty nuts! You don't need to set up anything beforehand. You don't need to write any code. Here is the best part: ASI:One has access to any agent published on Agentverse, an open directory of agents! This gives the model access to millions of tools it can execute dynamically when solving a task. Here is a simple example (the one in the attached video): • I went to Google Maps • I copied the latitude and longitude of a location • I asked ASI:One about relevant places around that location • ASI:One went to the marketplace • It identified and called the Google Places agent • It returned a list of museums, restaurants, and landmarks near my location Pretty awesome! You can try this now by going to You don't need to pay or register to test it out. If you want to get ideas of what's possible, check Agentverse, the agent marketplace: The model will have access to all of those tools. This is pretty awesome and opens up a whole new world of possibilities! Thanks to the team for partnering with me on this post!

Santiago

43,782 görüntüleme • 1 yıl önce