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| Original file line number | Diff line number | Diff line change |
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| # Quary VSCode Extension | ||
| <p align="center"> | ||
| <a href="https://quary.dev"> | ||
| <img align="center" src="https://storage.googleapis.com/public_hosted_materials/quary.svg" height="128"> | ||
| <h1 align="center">Quary</h1> | ||
| <h3 align="center">Business Intelligence for Engineers 🅀</h3> | ||
| </a> | ||
| </p> | ||
|
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| Quary is a VSCode extension that streamlines data analysis within your editor. It allows you to organize, wrangle, and analyze data with ease, turning VSCode into a powerful data analysis workbench. | ||
| <div class="title-block" style="text-align: center;" align="center"> | ||
|
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| ## Features | ||
| [](https://www.quary.dev/) | ||
| [](https://join.slack.com/t/quarylabs/shared_invite/zt-2dlbfnztw-dMLXJVL38NcbhqRuM5gUcw) | ||
| [](https://www.ycombinator.com/companies/quary) | ||
| [](https://github.com/quarylabs/quary) | ||
|
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| - **Seamless Integration**: Work with data right within VSCode. | ||
| - **Project Scaffolding**: Instantly generate a structured data project. | ||
| - **Model Visualization**: Render and visualize data models interactively. | ||
| - **Test Execution**: Run custom tests and validate your data models with built-in test suites. | ||
| - **Integrations**: Push your models and structure directly to a local SQLite database or BigQuery, allowing for collaboration and use by others. | ||
| </div> | ||
|
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| ## Requirements | ||
| <h2>With Quary, engineers can:</h2> | ||
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| - VSCode version 1.8 or higher. | ||
| - 🔌 Connect to their Database | ||
| - 📖 Write SQL queries to transform, organize, and document tables in a database | ||
| - 📊 Create charts, dashboards and reports (in development) | ||
| - 🧪 Test, collaborate & refactor iteratively through version control | ||
| - 🚀 Deploy the organised, documented model back up to the database | ||
|
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| ## Core commands | ||
| View the [documentation](https://www.quary.dev/docs). | ||
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| - `quary.run`: Configure and run your Quary data project. | ||
| - `quary.runTests`: Execute tests against your data models. | ||
| - `quary.renderModel`: Visualize data models within VSCode. | ||
| ... | ||
| ## 🗃️ Supported Databases | ||
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| ## Known Issues | ||
| <p align="center"> | ||
| <img src="https://img.shields.io/badge/Amazon%20Redshift-527FFF?style=for-the-badge&logo=Amazon%20Redshift&logoColor=white" alt="Amazon Redshift"> | ||
| <img src="https://img.shields.io/badge/Google%20BigQuery-4285F4?style=for-the-badge&logo=Google%20Cloud&logoColor=white" alt="Google BigQuery"> | ||
| <img src="https://img.shields.io/badge/PostgreSQL-336791?style=for-the-badge&logo=postgresql&logoColor=white" alt="PostgreSQL"> | ||
| <img src="https://img.shields.io/badge/Snowflake-29B5E8?style=for-the-badge&logo=snowflake&logoColor=white" alt="Snowflake"> | ||
| <img src="https://img.shields.io/badge/Supabase-3ECF8E?style=for-the-badge&logo=supabase&logoColor=white" alt="Supabase"> | ||
| <img src="https://img.shields.io/badge/DuckDB-FFF?style=for-the-badge&logo=duckdb&logoColor=black" alt="DuckDB"> | ||
| <img src="https://img.shields.io/badge/SQLite-003B57?style=for-the-badge&logo=sqlite&logoColor=white" alt="SQLite"> | ||
| </p> | ||
|
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| There are no known issues at the moment. For any new issues, please report them on our GitHub repository. | ||
|  | ||
|
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| ## Release Notes | ||
| ## 🏗️ Asset Types in Quary | ||
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| - Initial prerelease version. | ||
| Define and manage the following asset types as code: | ||
|
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| ## Getting Started with Quary | ||
| - **Sources:** Define the external data sources that feed into Quary, such as database tables, flat files, or APIs (with DuckDB). | ||
| - **Models:** Transform raw data from sources into analysis-ready datasets using SQL, this lets engineers split complex queries into atomic components. | ||
| - **Charts:** Create visual representations of your data using SQL. | ||
| - **🚧 Dashboards (WIP):** Combine multiple charts into a single view, allowing engineers to monitor and analyze data in one place. | ||
| - **🚧 Reports (WIP):** Create detailed reports to share insights and findings with your team or stakeholders. | ||
|
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| Quary projects consist of seeds, models, tests, sources, and custom tests. Don't be daunted by the terminology; our guide will walk you through each component. | ||
| ## 🚀 Getting Started | ||
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| ### Quickstart | ||
| ### Installation | ||
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| 1. **Open the Sample Project**: Access our template repository in GitHub's VSCode instance with no account required. | ||
| 2. **Install Quary**: Search for `Quary.quary` in the extensions tab and install. | ||
| 3. **Run Your Project**: Use `QUARY: Run` from the command palette to start your project against a sqlite database. | ||
| Quary is a VSCode Extension (Interface) & Rust-based CLI (Core) | ||
|
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| ### Anatomy of a Quary Project | ||
| #### Extension | ||
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| - `project.yml`: Root configuration file defining tests, models, and seeds. | ||
| - `.quary.config.yaml`: Specifies build configurations and database connections. | ||
| - `seeds/`: Holds initial data from .csv files to populate the database. | ||
| - `models/`: Contains SQL-based data models for project analysis. | ||
| The VSCode extension can be installed [here](https://marketplace.visualstudio.com/items?itemName=Quary.quary-extension). Note that it depends on the CLI being installed. | ||
|
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| ### Your First Model | ||
| #### CLI | ||
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| Models are at the heart of Quary, letting you transform raw data into insightful analytics. For example, `shifts_by_month` helps analyze employee shifts over time. | ||
| #### Homebrew installation | ||
|
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| ```sql | ||
| SELECT | ||
| employee_id, | ||
| strftime('%Y-%m', shift_date) AS shift_month, | ||
| COUNT(*) AS total_shifts | ||
| FROM q.stg_shifts | ||
| GROUP BY employee_id, shift_month | ||
| ``` | ||
| brew install quarylabs/quary/quary | ||
| ``` | ||
|
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| #### Linux/Mac through curl | ||
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| Quary can be installed using curl on Linux/Mac using the following command: | ||
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| ```shell | ||
| curl -fsSL https://raw.githubusercontent.com/quarylabs/quary/main/install.sh | bash | ||
| ``` | ||
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| #### Other installations | ||
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| Other builds are available in the [releases page](https://github.com/quarylabs/quary/releases/latest) to download. | ||
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| ### Usage | ||
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| Once installed, a sample project can be created and run as follows: | ||
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| ```shell | ||
| mkdir example # create an empty project folder | ||
| cd example | ||
| quary init # initialize DuckDB demo project with sample data | ||
| quary compile # validate the project structure and model references without database | ||
| quary build # build and execute the model views/seeds against target database | ||
| quary test -s # run defined tests against target database | ||
| ``` | ||
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| <h2>🅀 Community</h2> | ||
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| [Join our Slack channel](https://join.slack.com/t/quarylabs/shared_invite/zt-2dlbfnztw-dMLXJVL38NcbhqRuM5gUcw), for help, ideas, and discussions. | ||
|
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| ## Support | ||
|
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| If you run into any problems using Quary, please let us know. We want Quary to be easy-to-use, so if you are getting | ||
| confused, it is our fault, not yours. [Create an issue](https://github.com/quarylabs/quary/issues) and we'll be happy to | ||
| help you out. | ||
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| ### Check out our other projects | ||
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| [SQRUFF](https://github.com/quarylabs/sqruff), a compact, high-speed SQL linter, engineered with Rust efficiency. |