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SQL-in-JS formatting 😍 This is possible thanks to prettier-plugin-embed by Sec-ant (Ze-Zheng Wu), prettier-plugin-sql by JounQin, sql-formatter by Rene Saarsoo Setup Guide:

Karl Horky

2,013 subscribers

45,068 просмотров • 2 лет назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 6

Фото профиля Karl Horky 🦋 @karlhorky.com

Karl Horky 🦋 @karlhorky.com2 лет назад

Give these projects a star 🌟 prettier-plugin-embed by Sec-ant (Ze-Zheng Wu)

Фото профиля Karl Horky 🦋 @karlhorky.com

Karl Horky 🦋 @karlhorky.com2 лет назад

prettier-plugin-sql by @JounQin

Фото профиля Karl Horky 🦋 @karlhorky.com

Karl Horky 🦋 @karlhorky.com2 лет назад

sql-formatter by @renku

Фото профиля Karl Horky 🦋 @karlhorky.com

Karl Horky 🦋 @karlhorky.com2 лет назад

More great SQL tooling here:

Фото профиля Anton Revyako

Anton Revyako2 лет назад

@JounQin @renku Why are you storing sql in js? Put it in a separate file, it will bring many benefits

Фото профиля Karl Horky 🦋 @karlhorky.com

Karl Horky 🦋 @karlhorky.com2 лет назад

@JounQin @renku SQL-in-JS allows you to integrate with JavaScript and TypeScript: 1. Interpolation of runtime JavaScript values (eg. function parameters) 2. SQL closer to your logic (colocation) 3. Checking against TypeScript types Etc. Lots of benefits of having it in your JS/TS

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Dear Friend, I wrote this book for you. For the past year, I have labored to create a product that will help you learn and master SQL. I have been there. I have felt the frustration of trying to learn SQL and not knowing where to begin. I have lived through the struggle of setting up a platform to run SQL queries. Most platforms require sign-ups and logins that create a headache for learners. I also know the challenge of finding proper SQL exercises that mirror the real-world experience of a data analyst. Yes, I have been in your shoes. That’s why I created SQL Essentials for Data Analysis: A 50-Day Hands-on Challenge Book (Go From Beginner to Pro). Yes, to give you a clear, practical path from beginner to confident SQL user. ✅Why SQL Still Matters You may be wondering if SQL still matters in 2025. The answer: it has never mattered more. SQL is the lingua franca of data. Data still lives in databases, and the only language it truly understands is SQL. 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Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 просмотров • 9 месяцев назад

SQL has levels to it: - level 1 SELECT, FROM, WHERE, GROUP BY, HAVING, LIMIT Master these basic keywords and you’ll be well on your way to mastering SQL. - level 2 Mastering JOINs: Most common JOINs: INNER and LEFT Less common JOINs: FULL OUTER Joins you should avoid almost always: RIGHT and CROSS JOIN Mastering common table expressions (CTEs). The WITH keyword defines a CTE which you can imagine as a “variable” that you can query later. Using variables like this you can master algorithm techniques like recursion, breadth first search and more! CTEs also make your SQL much more readable and make your coworkers hate you less compared to nested sub queries. - level 3 Mastering window functions Window functions have 3 pieces: The function (i.e. SUM, RANK, AVG) The over clause to start the window The window definition which has 3 pieces: - how to split the window up with PARTITION BY - how to order the window with ORDER BY - how to restrict the window size with ROWS clause (useful for rolling monthly averages) Understand RANK vs DENSE_RANK vs ROW_NUMBER, I have been asked this in interviews a million times. - level 4 You understand table scans, b-tree indexes, and partitioning schemes to increase performance. Doing something like COUNT(CASE WHEN) is much better than doing multiple queries with a UNION ALL. UNION ALL is terrible for all sorts of reasons that I don’t want to get into in this post. B-trees indexes allow for efficient scanning of data in the WHERE clause. Use explain plans to understand if an index is actually being used or not! Partitioning is similar to indexes except it’s a “poor mans” index. It just keeps data in specific folders and skips the folders that don’t include the data I question. What else did I miss for mastering SQL?

SQL has levels to it: - level 1 SELECT, FROM, WHERE, GROUP BY, HAVING, LIMIT Master these basic keywords and you’ll be well on your way to mastering SQL. - level 2 Mastering JOINs: Most common JOINs: INNER and LEFT Less common JOINs: FULL OUTER Joins you should avoid almost always: RIGHT and CROSS JOIN Mastering common table expressions (CTEs). The WITH keyword defines a CTE which you can imagine as a “variable” that you can query later. Using variables like this you can master algorithm techniques like recursion, breadth first search and more! CTEs also make your SQL much more readable and make your coworkers hate you less compared to nested sub queries. - level 3 Mastering window functions Window functions have 3 pieces: The function (i.e. SUM, RANK, AVG) The over clause to start the window The window definition which has 3 pieces: - how to split the window up with PARTITION BY - how to order the window with ORDER BY - how to restrict the window size with ROWS clause (useful for rolling monthly averages) Understand RANK vs DENSE_RANK vs ROW_NUMBER, I have been asked this in interviews a million times. - level 4 You understand table scans, b-tree indexes, and partitioning schemes to increase performance. Doing something like COUNT(CASE WHEN) is much better than doing multiple queries with a UNION ALL. UNION ALL is terrible for all sorts of reasons that I don’t want to get into in this post. B-trees indexes allow for efficient scanning of data in the WHERE clause. Use explain plans to understand if an index is actually being used or not! Partitioning is similar to indexes except it’s a “poor mans” index. It just keeps data in specific folders and skips the folders that don’t include the data I question. What else did I miss for mastering SQL?

Zach Wilson

79,625 просмотров • 1 год назад

Mesa County, Colorado Dominion System Was WIDE OPEN, any computer in the WORLD could connect to the EMS server and flip votes with a few clicks in the 2020 Election. 36 wireless devices, global SQL access via port 1433, uncertified software, and live vote manipulation DEMONSTRATED. Certification was illegal. System should have been decertified immediately. This is the 2nd forensic report to Mesa County, Colorado, connected to Tina Peters. The most significant findings allowed unrestricted global SQL access. The EMS server was configured so any computer in the world could connect directly to the SQL databases via port 1433, default SQL port. Windows Firewall allowed inbound connections from any IP address with no restrictions. All SQL protocols were enabled. Shared Memory, Named Pipes, and TCP/IP, making remote access trivial. 36 wireless devices identified built into the DVS D-Suite system, 35 in voting components like Dell Latitude/Optiplex ICVA/ICC machines and ICX tablets + 1 Dell E3DW wireless printer on the EMS server. These were vulnerable to known attacks (KRACK). Self-signed certificate used for encryption, vulnerable to man-in-the-middle attacks. Shared/default passwords for administrative accounts, violating user accountability requirements. Audit logs overwritten/deleted by design and configuration, building on Report #1 findings. Uncertified software, Microsoft SQL Server Management Studio (SSMS) was installed on the server, May 7, 2017, but not listed in the official certification application or test report for DVS D-Suite 5.1-CO. Live vote manipulation was demonstrated using SSMS, changing just two values in the dbo.Choice table, internalMachineId for candidates, flipped vote totals between candidates, one example altered tens of thousands of votes in the demo. Multiple election databases, including 2020 General, municipal, etc., were fully accessible and modifiable. Anyone at a logged-in EMS server could alter databases in seconds with SSMS. From any non-Dominion computer on the same subnet. From a cell phone/iPhone connected to the network using a free SQL app, successfully identified the server and modified data. These are HUGE security risks of enormous proportions, compromising the 2020 Election in multiple ways with multiple attack vectors.

Mesa County, Colorado Dominion System Was WIDE OPEN, any computer in the WORLD could connect to the EMS server and flip votes with a few clicks in the 2020 Election. 36 wireless devices, global SQL access via port 1433, uncertified software, and live vote manipulation DEMONSTRATED. Certification was illegal. System should have been decertified immediately. This is the 2nd forensic report to Mesa County, Colorado, connected to Tina Peters. The most significant findings allowed unrestricted global SQL access. The EMS server was configured so any computer in the world could connect directly to the SQL databases via port 1433, default SQL port. Windows Firewall allowed inbound connections from any IP address with no restrictions. All SQL protocols were enabled. Shared Memory, Named Pipes, and TCP/IP, making remote access trivial. 36 wireless devices identified built into the DVS D-Suite system, 35 in voting components like Dell Latitude/Optiplex ICVA/ICC machines and ICX tablets + 1 Dell E3DW wireless printer on the EMS server. These were vulnerable to known attacks (KRACK). Self-signed certificate used for encryption, vulnerable to man-in-the-middle attacks. Shared/default passwords for administrative accounts, violating user accountability requirements. Audit logs overwritten/deleted by design and configuration, building on Report #1 findings. Uncertified software, Microsoft SQL Server Management Studio (SSMS) was installed on the server, May 7, 2017, but not listed in the official certification application or test report for DVS D-Suite 5.1-CO. Live vote manipulation was demonstrated using SSMS, changing just two values in the dbo.Choice table, internalMachineId for candidates, flipped vote totals between candidates, one example altered tens of thousands of votes in the demo. Multiple election databases, including 2020 General, municipal, etc., were fully accessible and modifiable. Anyone at a logged-in EMS server could alter databases in seconds with SSMS. From any non-Dominion computer on the same subnet. From a cell phone/iPhone connected to the network using a free SQL app, successfully identified the server and modified data. These are HUGE security risks of enormous proportions, compromising the 2020 Election in multiple ways with multiple attack vectors.

The SCIF

51,936 просмотров • 1 месяц назад

Document Querying with Qwen2-VL-7B and JSON Output Complete video: I demonstrate how to perform document queries using Qwen2-VL-7B. By simplifying field names, we streamline the prompts, making them more efficient and reusable across different documents. This approach is similar to running SQL queries on a database, but tailored for language models like Qwen2-VL-7B, with results returned in JSON format. Qwen #MultimodalLLM #OCR

Document Querying with Qwen2-VL-7B and JSON Output Complete video: I demonstrate how to perform document queries using Qwen2-VL-7B. By simplifying field names, we streamline the prompts, making them more efficient and reusable across different documents. This approach is similar to running SQL queries on a database, but tailored for language models like Qwen2-VL-7B, with results returned in JSON format. Qwen #MultimodalLLM #OCR

Andrej Baranovskij

15,976 просмотров • 1 год назад

SQL has levels to it: - level 1 SELECT, FROM, WHERE, GROUP BY, HAVING, LIMIT Master these basic keywords and you’ll be well on your way to mastering SQL. - level 2 Mastering JOINs: Most common JOINs: INNER and LEFT Less common JOINs: FULL OUTER Joins you should avoid almost always: RIGHT and CROSS JOIN Mastering common table expressions (CTEs). The WITH keyword defines a CTE which you can imagine as a “variable” that you can query later. Using variables like this you can master algorithm techniques like recursion, breadth first search and more! CTEs also make your SQL much more readable and make your coworkers hate you less compared to nested sub queries. - level 3 Mastering window functions Window functions have 3 pieces: The function (i.e. SUM, RANK, AVG) The over clause to start the window The window definition which has 3 pieces: - how to split the window up with PARTITION BY - how to order the window with ORDER BY - how to restrict the window size with ROWS clause (useful for rolling monthly averages) Understand RANK vs DENSE_RANK vs ROW_NUMBER, I have been asked this in interviews a million times. - level 4 You understand table scans, b-tree indexes, and partitioning schemes to increase performance. Doing something like COUNT(CASE WHEN) is much better than doing multiple queries with a UNION ALL. UNION ALL is terrible for all sorts of reasons that I don’t want to get into in this post. B-trees indexes allow for efficient scanning of data in the WHERE clause. Use explain plans to understand if an index is actually being used or not! Partitioning is similar to indexes except it’s a “poor mans” index. It just keeps data in specific folders and skips the folders that don’t include the data I question. What else did I miss for mastering SQL?

SQL has levels to it: - level 1 SELECT, FROM, WHERE, GROUP BY, HAVING, LIMIT Master these basic keywords and you’ll be well on your way to mastering SQL. - level 2 Mastering JOINs: Most common JOINs: INNER and LEFT Less common JOINs: FULL OUTER Joins you should avoid almost always: RIGHT and CROSS JOIN Mastering common table expressions (CTEs). The WITH keyword defines a CTE which you can imagine as a “variable” that you can query later. Using variables like this you can master algorithm techniques like recursion, breadth first search and more! CTEs also make your SQL much more readable and make your coworkers hate you less compared to nested sub queries. - level 3 Mastering window functions Window functions have 3 pieces: The function (i.e. SUM, RANK, AVG) The over clause to start the window The window definition which has 3 pieces: - how to split the window up with PARTITION BY - how to order the window with ORDER BY - how to restrict the window size with ROWS clause (useful for rolling monthly averages) Understand RANK vs DENSE_RANK vs ROW_NUMBER, I have been asked this in interviews a million times. - level 4 You understand table scans, b-tree indexes, and partitioning schemes to increase performance. Doing something like COUNT(CASE WHEN) is much better than doing multiple queries with a UNION ALL. UNION ALL is terrible for all sorts of reasons that I don’t want to get into in this post. B-trees indexes allow for efficient scanning of data in the WHERE clause. Use explain plans to understand if an index is actually being used or not! Partitioning is similar to indexes except it’s a “poor mans” index. It just keeps data in specific folders and skips the folders that don’t include the data I question. What else did I miss for mastering SQL?

Zach Wilson

34,221 просмотров • 3 месяцев назад

This is 2XKO in Spain. 150+ players joined BATTLE BY THE BAR. Thanks to everyone who made it possible and... see you soon? 👀

This is 2XKO in Spain. 150+ players joined BATTLE BY THE BAR. Thanks to everyone who made it possible and... see you soon? 👀

Javier Sanabria

35,787 просмотров • 9 месяцев назад

Claude Code is now a full video editor! Our new plugin opens a full built-in NLE right inside the Claude desktop app, where you and your agent can edit together, effortlessly. If you're already paying for Claude, you get this one for FREE. It's available now. Start using it in 1 minute, by pasting this prompt into any Claude Code chat: "Read to install and use the ChatCut plugin"

Claude Code is now a full video editor! Our new plugin opens a full built-in NLE right inside the Claude desktop app, where you and your agent can edit together, effortlessly. If you're already paying for Claude, you get this one for FREE. It's available now. Start using it in 1 minute, by pasting this prompt into any Claude Code chat: "Read to install and use the ChatCut plugin"

ChatCut

226,918 просмотров • 20 дней назад

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

Avid

338,253 просмотров • 2 месяцев назад

Been waiting to share this with you all 🙌 The video is live — check the link in bio! Credits- Featuring James Maslow, Maya Dadon and Shahar Saul Directed by Aaron Gatewood Co-Directed by Haim Silberstein Executive Production by Jonathan Baruch Special thanks - Christine Wu 🎻 Made in partnership with Birthright Israel Foundation #newmusic #jamesmaslow #birthrightisrael #Israel #onmymind

Been waiting to share this with you all 🙌 The video is live — check the link in bio! Credits- Featuring James Maslow, Maya Dadon and Shahar Saul Directed by Aaron Gatewood Co-Directed by Haim Silberstein Executive Production by Jonathan Baruch Special thanks - Christine Wu 🎻 Made in partnership with Birthright Israel Foundation #newmusic #jamesmaslow #birthrightisrael #Israel #onmymind

James Maslow

73,107 просмотров • 10 месяцев назад

Lens Sim add-on by Håvard Dalen is out! In brief: photorealistic rendering in #b3d will never be the same. As we've been testing the development version, there was enough time for us to record a walkthrough/review about this phenomenal Blender plugin. So, is it the best? 👇🔽

Lens Sim add-on by Håvard Dalen is out! In brief: photorealistic rendering in #b3d will never be the same. As we've been testing the development version, there was enough time for us to record a walkthrough/review about this phenomenal Blender plugin. So, is it the best? 👇🔽

Gleb Alexandrov

19,628 просмотров • 1 год назад

We're excited to announce duckdb-skills, a DuckDB plugin for Claude Code! We think the embedded nature of DuckDB makes it a perfect companion for Claude in your local workflows. The skills supported include: + read-file and query – uses DuckDB's CLI to query data locally, unlocking easy access to any file that DuckDB can read. + read-memories – a clever idea to store your Claude memories in DuckDB and query them at blazing speed. These are powered by two additional skills: + attach-db – gives Claude a mechanism to manage DuckDB state through a .sql file linked to your project. + duckdb-docs – uses a remote DuckDB full-text search database to query the DuckDB docs and answer all of your (and Claude's own) questions.

We're excited to announce duckdb-skills, a DuckDB plugin for Claude Code! We think the embedded nature of DuckDB makes it a perfect companion for Claude in your local workflows. The skills supported include: + read-file and query – uses DuckDB's CLI to query data locally, unlocking easy access to any file that DuckDB can read. + read-memories – a clever idea to store your Claude memories in DuckDB and query them at blazing speed. These are powered by two additional skills: + attach-db – gives Claude a mechanism to manage DuckDB state through a .sql file linked to your project. + duckdb-docs – uses a remote DuckDB full-text search database to query the DuckDB docs and answer all of your (and Claude's own) questions.

DuckDB

60,683 просмотров • 4 месяцев назад