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The @springdata JDBC framework does not support schema generation yet: But there is a workaround! Use IntelliJ IDEA to generate schema init scripts for Liquibase and @flywaydb.

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IntelliJ IDEA, a JetBrains IDE

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14,451 просмотров • 4 месяцев назад •via X (Twitter)

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Teams often start model-first, then switch to DB-first (or the other way around) 😅 Syncing both worlds manually is painful. Spring Data JDBC supports both approaches, and IntelliJ IDEA generates DB schema from entities and entities from schema 🔄
0:29

Teams often start model-first, then switch to DB-first (or the other way around) 😅 Syncing both worlds manually is painful. Spring Data JDBC supports both approaches, and IntelliJ IDEA generates DB schema from entities and entities from schema 🔄

IntelliJ IDEA, a JetBrains IDE

14,675 просмотров • 5 месяцев назад

this is super cool. there's a feature in an upcoming JetBrains IntelliJ IDEA, a JetBrains IDE that lets you trivially reverse engineer a schema into JPA entities. I've been assured that they're working on Spring Data Team JDBC support, too! // paging my friend Aleksey Stukalov come and see more today at #intellijideaconf 2025 !
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this is super cool. there's a feature in an upcoming JetBrains IntelliJ IDEA, a JetBrains IDE that lets you trivially reverse engineer a schema into JPA entities. I've been assured that they're working on Spring Data Team JDBC support, too! // paging my friend Aleksey Stukalov come and see more today at #intellijideaconf 2025 !

Josh Long

11,547 просмотров • 1 год назад

Agentic Document Extraction now supports field extraction! Many doc extraction use cases extract specific fields from forms and other structured documents. You can now input a picture or PDF of an invoice, request the vendor name, item list, and prices, and get back the extracted fields. Or input a medical form and specify a schema to extract patient name, patient ID, insurance number, etc. One cool feature: If you don't feel like writing a schema (json specification of what fields to extract) yourself, upload one sample document and write a natural language prompt saying what you want, and we automatically generate a schema for you. See the video for details!
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Agentic Document Extraction now supports field extraction! Many doc extraction use cases extract specific fields from forms and other structured documents. You can now input a picture or PDF of an invoice, request the vendor name, item list, and prices, and get back the extracted fields. Or input a medical form and specify a schema to extract patient name, patient ID, insurance number, etc. One cool feature: If you don't feel like writing a schema (json specification of what fields to extract) yourself, upload one sample document and write a natural language prompt saying what you want, and we automatically generate a schema for you. See the video for details!

Andrew Ng

192,883 просмотров • 1 год назад

CubePart is the latest update to our open-source Cube 3D foundation model. It lets creators pair a text prompt with an open-ended part schema to generate labeled meshes that drop straight into a game engine for physics, animation, and scripting.
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CubePart is the latest update to our open-source Cube 3D foundation model. It lets creators pair a text prompt with an open-ended part schema to generate labeled meshes that drop straight into a game engine for physics, animation, and scripting.

David Baszucki

139,498 просмотров • 1 месяц назад

we wanna have a proper click/jump to definition experience all around drizzle schema, relations and queries and we've spent quite some time tuning it all around and we've found out this weird bug which is last step before 100% DX Is it something to report to TypeScript or is it VSCode intellisense issue? it does not let jump to definition when you cmd+click key of an object which is derived from table in schema. But as soon as you have a wrong key value - it let's you do it straight away for all keys 🥲
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we wanna have a proper click/jump to definition experience all around drizzle schema, relations and queries and we've spent quite some time tuning it all around and we've found out this weird bug which is last step before 100% DX Is it something to report to TypeScript or is it VSCode intellisense issue? it does not let jump to definition when you cmd+click key of an object which is derived from table in schema. But as soon as you have a wrong key value - it let's you do it straight away for all keys 🥲

Drizzle ORM

22,033 просмотров • 10 месяцев назад

I am 14, and I built (not ready to launch) an MVP called Vidmirror. It is a tool for YouTubers to find viral videos, and it can even generate thumbnails, titles, and scripts (coming soon). Not ready to launch yet because I want to do payment verification before launching it. It is still in MVP stage I am trying to add automation features and video generation. It is very easy to use, and here is the demo. i know the voice and video looks bad .don't care it
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I am 14, and I built (not ready to launch) an MVP called Vidmirror. It is a tool for YouTubers to find viral videos, and it can even generate thumbnails, titles, and scripts (coming soon). Not ready to launch yet because I want to do payment verification before launching it. It is still in MVP stage I am trying to add automation features and video generation. It is very easy to use, and here is the demo. i know the voice and video looks bad .don't care it

Shayan C

433,867 просмотров • 1 год назад

Working on roof generation for my little city building game. The idea is that based on how you build your buildings, roofs are automatically formed where it makes sense. The roof generation logic is working fairly well, but lots to do to generate a better looking mesh!
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Working on roof generation for my little city building game. The idea is that based on how you build your buildings, roofs are automatically formed where it makes sense. The roof generation logic is working fairly well, but lots to do to generate a better looking mesh!

Björn Ottosson - making Island Architect

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Ding Dong the Endangerment Finding (for vehicles) is DEAD! Does that mean the climate scam is dead? Not yet. There is still more to do.
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Ding Dong the Endangerment Finding (for vehicles) is DEAD! Does that mean the climate scam is dead? Not yet. There is still more to do.

Linnea Lueken

30,648 просмотров • 5 месяцев назад

If this post get 400+ reposts. I'll build it for you guys. The best way to validate the idea is to share it with right audience. Check out the app flow below. It can create: ✅ System prompts ✅ PRDs ✅ App flow Docs ✅ Schema Design ✅ v0 System Prompts and so on/
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If this post get 400+ reposts. I'll build it for you guys. The best way to validate the idea is to share it with right audience. Check out the app flow below. It can create: ✅ System prompts ✅ PRDs ✅ App flow Docs ✅ Schema Design ✅ v0 System Prompts and so on/

CJ Zafir

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This was not my idea, but a request for Jimmy by The Rural Juror And, holy shit does it land.
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This was not my idea, but a request for Jimmy by The Rural Juror And, holy shit does it land.

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112,152 просмотров • 1 год назад

Hungary has the right idea. Note how the interviewer tries to move on but she is not allowed to do so and educated. Multiculturalism does not work!
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Hungary has the right idea. Note how the interviewer tries to move on but she is not allowed to do so and educated. Multiculturalism does not work!

James

700,457 просмотров • 3 лет назад

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!
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Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!

Avi Chawla

186,931 просмотров • 6 месяцев назад

🆕 Introducing PrismaGPT, a query helper built on GPT-4 🎉 * Drop in your Prisma schema * Ask for what you want * Get back a Prisma Client query and raw SQL Great for when you know what you need but aren't quite sure how to construct the query 👍
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🆕 Introducing PrismaGPT, a query helper built on GPT-4 🎉 * Drop in your Prisma schema * Ask for what you want * Get back a Prisma Client query and raw SQL Great for when you know what you need but aren't quite sure how to construct the query 👍

Ryan Chenkie

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'We're using this time we have to work through all the different contingencies and different options, for more tailored and targeted support' Chancellor Rachel Reeves tells Lewis Denison support on energy bills is coming - but not yet and not for everyone
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'We're using this time we have to work through all the different contingencies and different options, for more tailored and targeted support' Chancellor Rachel Reeves tells Lewis Denison support on energy bills is coming - but not yet and not for everyone

ITV News

22,474 просмотров • 3 месяцев назад

Goodnight, 𝕏..·˚ ༘ ☾ ⋆｡˚ ☄︎ Here's a fun project you can start with Grok 4. Use Grok-Code-Fast-1 to build your own OS. Below is a prompt that you can give to Grok-Code, and it will set up a solid foundation for a Linux-based Operating system that you can build from the ground up with Grok4. >>> Grok 4 Prompt You are a fully capable AI developer agent with expert-level experience as an embedded Linux systems engineer. You have deep expertise in using automated build systems like Buildroot and Yocto to create custom operating systems from source. You have access to a sandboxed Linux shell environment that allows you to write, execute, and debug code. Your mission is to generate a complete project skeleton for a minimal, custom Linux OS, and then you will execute the build scripts yourself to verify their correctness, automatically fixing any issues that arise. This is NOT a request to follow the Linux From Scratch (LFS) book. You will use the Buildroot build system to automate the entire process. You will follow a two-phase process: Phase 1: Generation and Phase 2: Execution and Iterative Debugging. ------------------------------------------------------------- Phase 1: Code and Script Generation First, you will generate all the necessary files for the project skeleton. All generated shell scripts must be robust and path-aware, executing correctly from any directory [Previous conversation]. Detailed Implementation Steps (using Context-Aware Decomposition): 1. Generate the Project Directory Structure via setup. sh Create a setup. sh script that establishes the following directory structure: • buildroot/ - Where the Buildroot source code will be cloned. • configs/ - To store our custom Buildroot configuration (defconfig). • board/ - For custom board support, including a readme.txt explaining its purpose for filesystem overlays. • output/ - Where all build artifacts will be placed. • scripts/ - A home for our build. sh and test. sh scripts. Crucially, this setup. sh script (and all others) must begin with a preamble to define the project's root directory, making all subsequent paths absolute and robust: #!/bin/bash # Preamble to ensure path robustness and stop on error set -e PROJECT_ROOT="$(cd "$(dirname "${BASH_SOURCE}")" && pwd)" The script must then clone the latest stable branch of Buildroot into $ PROJECT_ROOT/buildroot/. 2. Create the Minimal and Correct Buildroot defconfig Create a file named configs/tiny_linux_defconfig. This configuration must be the absolute bare minimum required to boot to a shell and must contain the exact configuration options listed below to avoid ambiguity and known errors: • Target Architecture: x86_64. • Toolchain: Use the default Buildroot toolchain. • Init System: Use BusyBox init. • System Utilities (BusyBox): ◦ To ensure BusyBox is statically linked without errors, you must include the following line directly in the defconfig file: BR2_PACKAGE_BUSYBOX_STATIC_LINK=y [Previous conversation, 298, 753]. ◦ To prevent the ROJECT_ROOT error, explicitly do NOT use a configuration fragment for BusyBox. Do not generate any lines containing BR2_BUSYBOX_CONFIG_FRAGMENT_FILES [Previous conversation]. • Kernel: ◦ Build the latest stable Linux kernel. ◦ Use tinyconfig as a base. ◦ Ensure the following options are explicitly enabled (=y) to make it bootable in QEMU: CONFIG_64BIT=y, CONFIG_DEVTMPFS=y, CONFIG_DEVTMPFS_MOUNT=y, CONFIG_BINFMT_ELF=y, CONFIG_BLK_DEV_INITRD=y (for initramfs support), CONFIG_TTY=y, CONFIG_PRINTK=y, CONFIG_DRM_FBDEV_EMULATION=y (for UEFI framebuffer console). • Filesystem Image: Configure it to produce a compressed cpio initial ramdisk (initramfs) image. • Bootloader: Do not include GRUB or other bootloaders. We will boot the kernel directly with QEMU. 3. Generate the scripts/build.sh and scripts/test.sh Scripts Generate path-aware build and test scripts, placing them in the scripts/ directory. • scripts/build.sh: This script must use absolute paths derived from a preamble. It must use make -C "$PROJECT_ROOT/buildroot" O="$PROJECT_ROOT/output" ... for a clean, out-of-tree build. It must include the -j$(nproc) flag to maximize build speed on multi-core systems [111, 967, Previous conversation]. • scripts/test.sh: This script must also be path-aware and launch QEMU using absolute paths to the kernel (bzImage) and initramfs (rootfs.cpio.gz) images. 4. Generate a Detailed README. md File Generate a comprehensive README. md file. It must explain prerequisites, "How to Customize Your Linux System" first, and finally, the "Quick Start" instructions for user clarity [Previous conversation]. ------------------------------------------------------------- Phase 2: Execution and Iterative Debugging Now, you will use your sandboxed Linux shell to verify and validate the scripts you just generated. This is a critical self-correction step based on the Recursive Criticism and Improvement (RCI) pattern. You will perform a full build cycle. 1. Execute setup. sh: • Run the setup. sh script you generated. • Capture the standard output and standard error. • If the script fails: Analyze the error, diagnose the root cause, generate the corrected setup. sh code, and then execute the corrected script to confirm it succeeds. 2. Execute build. sh: • After setup. sh completes successfully, run the scripts/build.sh script. This will trigger a full compilation of the Linux system. • Capture all output. • If the build fails: ◦ Analyze: Analyze the compiler error output. ◦ Diagnose: Identify the root cause (e.g., missing dependencies, incorrect configuration flags, pathing errors). ◦ Correct: Based on your analysis, identify which file is responsible for the failure (e.g., configs/tiny_linux_defconfig, scripts/build.sh) and generate the corrected code for that file. ◦ Repeat: Repeat the execution of scripts/build.sh until the build completes successfully without any errors. 3. Final Output: Once you have successfully executed both setup. sh and scripts/build.sh, you will present your final output. • First, provide the final, validated versions of all generated files (setup. sh, configs/tiny_linux_defconfig, scripts/build.sh, scripts/test.sh, and README. md) in separate, clearly labeled markdown code blocks. • Second, follow the code with a brief execution log. This log should summarize your actions, including any errors you encountered and fixed during the iterative debugging phase, demonstrating the self-correction process.
1:05

Goodnight, 𝕏..·˚ ༘ ☾ ⋆｡˚ ☄︎ Here's a fun project you can start with Grok 4. Use Grok-Code-Fast-1 to build your own OS. Below is a prompt that you can give to Grok-Code, and it will set up a solid foundation for a Linux-based Operating system that you can build from the ground up with Grok4. >>> Grok 4 Prompt You are a fully capable AI developer agent with expert-level experience as an embedded Linux systems engineer. You have deep expertise in using automated build systems like Buildroot and Yocto to create custom operating systems from source. You have access to a sandboxed Linux shell environment that allows you to write, execute, and debug code. Your mission is to generate a complete project skeleton for a minimal, custom Linux OS, and then you will execute the build scripts yourself to verify their correctness, automatically fixing any issues that arise. This is NOT a request to follow the Linux From Scratch (LFS) book. You will use the Buildroot build system to automate the entire process. You will follow a two-phase process: Phase 1: Generation and Phase 2: Execution and Iterative Debugging. ------------------------------------------------------------- Phase 1: Code and Script Generation First, you will generate all the necessary files for the project skeleton. All generated shell scripts must be robust and path-aware, executing correctly from any directory [Previous conversation]. Detailed Implementation Steps (using Context-Aware Decomposition): 1. Generate the Project Directory Structure via setup. sh Create a setup. sh script that establishes the following directory structure: • buildroot/ - Where the Buildroot source code will be cloned. • configs/ - To store our custom Buildroot configuration (defconfig). • board/ - For custom board support, including a readme.txt explaining its purpose for filesystem overlays. • output/ - Where all build artifacts will be placed. • scripts/ - A home for our build. sh and test. sh scripts. Crucially, this setup. sh script (and all others) must begin with a preamble to define the project's root directory, making all subsequent paths absolute and robust: #!/bin/bash # Preamble to ensure path robustness and stop on error set -e PROJECT_ROOT="$(cd "$(dirname "${BASH_SOURCE}")" && pwd)" The script must then clone the latest stable branch of Buildroot into $ PROJECT_ROOT/buildroot/. 2. Create the Minimal and Correct Buildroot defconfig Create a file named configs/tiny_linux_defconfig. This configuration must be the absolute bare minimum required to boot to a shell and must contain the exact configuration options listed below to avoid ambiguity and known errors: • Target Architecture: x86_64. • Toolchain: Use the default Buildroot toolchain. • Init System: Use BusyBox init. • System Utilities (BusyBox): ◦ To ensure BusyBox is statically linked without errors, you must include the following line directly in the defconfig file: BR2_PACKAGE_BUSYBOX_STATIC_LINK=y [Previous conversation, 298, 753]. ◦ To prevent the ROJECT_ROOT error, explicitly do NOT use a configuration fragment for BusyBox. Do not generate any lines containing BR2_BUSYBOX_CONFIG_FRAGMENT_FILES [Previous conversation]. • Kernel: ◦ Build the latest stable Linux kernel. ◦ Use tinyconfig as a base. ◦ Ensure the following options are explicitly enabled (=y) to make it bootable in QEMU: CONFIG_64BIT=y, CONFIG_DEVTMPFS=y, CONFIG_DEVTMPFS_MOUNT=y, CONFIG_BINFMT_ELF=y, CONFIG_BLK_DEV_INITRD=y (for initramfs support), CONFIG_TTY=y, CONFIG_PRINTK=y, CONFIG_DRM_FBDEV_EMULATION=y (for UEFI framebuffer console). • Filesystem Image: Configure it to produce a compressed cpio initial ramdisk (initramfs) image. • Bootloader: Do not include GRUB or other bootloaders. We will boot the kernel directly with QEMU. 3. Generate the scripts/build.sh and scripts/test.sh Scripts Generate path-aware build and test scripts, placing them in the scripts/ directory. • scripts/build.sh: This script must use absolute paths derived from a preamble. It must use make -C "$PROJECT_ROOT/buildroot" O="$PROJECT_ROOT/output" ... for a clean, out-of-tree build. It must include the -j$(nproc) flag to maximize build speed on multi-core systems [111, 967, Previous conversation]. • scripts/test.sh: This script must also be path-aware and launch QEMU using absolute paths to the kernel (bzImage) and initramfs (rootfs.cpio.gz) images. 4. Generate a Detailed README. md File Generate a comprehensive README. md file. It must explain prerequisites, "How to Customize Your Linux System" first, and finally, the "Quick Start" instructions for user clarity [Previous conversation]. ------------------------------------------------------------- Phase 2: Execution and Iterative Debugging Now, you will use your sandboxed Linux shell to verify and validate the scripts you just generated. This is a critical self-correction step based on the Recursive Criticism and Improvement (RCI) pattern. You will perform a full build cycle. 1. Execute setup. sh: • Run the setup. sh script you generated. • Capture the standard output and standard error. • If the script fails: Analyze the error, diagnose the root cause, generate the corrected setup. sh code, and then execute the corrected script to confirm it succeeds. 2. Execute build. sh: • After setup. sh completes successfully, run the scripts/build.sh script. This will trigger a full compilation of the Linux system. • Capture all output. • If the build fails: ◦ Analyze: Analyze the compiler error output. ◦ Diagnose: Identify the root cause (e.g., missing dependencies, incorrect configuration flags, pathing errors). ◦ Correct: Based on your analysis, identify which file is responsible for the failure (e.g., configs/tiny_linux_defconfig, scripts/build.sh) and generate the corrected code for that file. ◦ Repeat: Repeat the execution of scripts/build.sh until the build completes successfully without any errors. 3. Final Output: Once you have successfully executed both setup. sh and scripts/build.sh, you will present your final output. • First, provide the final, validated versions of all generated files (setup. sh, configs/tiny_linux_defconfig, scripts/build.sh, scripts/test.sh, and README. md) in separate, clearly labeled markdown code blocks. • Second, follow the code with a brief execution log. This log should summarize your actions, including any errors you encountered and fixed during the iterative debugging phase, demonstrating the self-correction process.

Tetsuo

2,840,991 просмотров • 9 месяцев назад

JSON columns in Postgres can be flexible, but too much flexibility can be risky as you might accidentally end up with malformed data. You can prevent this using the pg_jsonschema extension to easily define a schema for your JSON and JSONB columns!
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JSON columns in Postgres can be flexible, but too much flexibility can be risky as you might accidentally end up with malformed data. You can prevent this using the pg_jsonschema extension to easily define a schema for your JSON and JSONB columns!

Tyler Shukert

17,480 просмотров • 1 год назад

🚨INTERVIEW: “CHINA'S NUCLEAR AMBITIONS RISING, BUT IT’S NOT THERE YET” “China, thanks to whose support the Russian economy is still functioning, and Russia is able to conduct this war, is also not ready for international politics going nuclear. China is a world economic superpower, the largest economy in the world. But it is a mid-power when it comes to nuclear arsenal. China is now the most dynamic nuclear power in terms of developing its nuclear and increasing its nuclear arsenal and its nuclear capabilities. But it is not there yet. China's nuclear arsenal is roughly 10% of what Russia and the United States have in terms of the warheads.” Serhii Plokhy, Harvard Professor of Ukrainian History.
4:26

🚨INTERVIEW: “CHINA'S NUCLEAR AMBITIONS RISING, BUT IT’S NOT THERE YET” “China, thanks to whose support the Russian economy is still functioning, and Russia is able to conduct this war, is also not ready for international politics going nuclear. China is a world economic superpower, the largest economy in the world. But it is a mid-power when it comes to nuclear arsenal. China is now the most dynamic nuclear power in terms of developing its nuclear and increasing its nuclear arsenal and its nuclear capabilities. But it is not there yet. China's nuclear arsenal is roughly 10% of what Russia and the United States have in terms of the warheads.” Serhii Plokhy, Harvard Professor of Ukrainian History.

Mario Nawfal

19,076 просмотров • 7 месяцев назад

BREAKING: Sec. Pete Hegseth on Iran: “This is not Iraq, this is not endless. I was there for both. Our generation knows better, and so does this president. This is the opposite. This operation is a clear devastating decisive mission.”
0:55

BREAKING: Sec. Pete Hegseth on Iran: “This is not Iraq, this is not endless. I was there for both. Our generation knows better, and so does this president. This is the opposite. This operation is a clear devastating decisive mission.”

Leading Report

265,557 просмотров • 4 месяцев назад