文件列表:

demo/
static/
templates/
Dockerfile
LICENSE
Procfile
app.py
config.toml
models.py
query.py
query_test.py
requirements.txt

# Malewicz Hackable GUI SQL-manager written in SQL itself (and a pinch of the HTML templates). > "If you want something done, do it yourself. Yep!" > > Jean-Baptiste Emanuel Zorg, "The Fifth Element", 1997. Malewicz is a cross-platform Database GUI tool for developers, SQL programmers, DBAs and data analysts. [Try Malewicz on Heroku](https://malewicz.herokuapp.com)   ## Current status :warning: This experimental project is in early development phase. If you have ideas, feel free to [text me](mailto:mgramin@gmail.com), create a PR or open an issue. ## What is Malewicz? Malewicz is Yet Another WEB client for DB schema exploring and performance analysis. Something like [PgHero](https://github.com/ankane/pghero), [Pgweb](https://github.com/sosedoff/pgweb) or even [phpMyAdmin](https://github.com/phpmyadmin/phpmyadmin), but with some key features: - Hackable - Malewicz was originally created specifically for hacking and extending (template driven, live reload) - Suprematistic - use only your SQL skills (and a little bit HTML) without any noisy boilerplate code - Template driven - we use all power of [Jinja](https://jinja.palletsprojects.com) - Lightning-fast AJAX web interface - but without a single line of JavaScript (we use [Hotwire Turbo](https://turbo.hotwired.dev)) - Simple and powerful integration with awesome tools, for charts, diagrams etc. - Strong bodrer - between SQL-scripts (it's our main value) and representation templates - Reusable SQL-queries - you can reuse queries in other contexts and database tools. ## Embedded SQL editor Malewicz **has no** embedded SQL editor. Instead, you might use your favorite code editor (like Vim or VS Code) or IDE (like DBeaver or DataGrips) for edit plain sql-files. ## We were inspired by - [dbt](https://github.com/dbt-labs/dbt-core) - Just drop your SQL-queries to your repository and the magic happens - [YeSQL](https://github.com/krisajenkins/yesql) - Keep the SQL as SQL - Treat your [Database as Code](https://github.com/mgramin/database-as-code) ## Run from sources Init and activate virtual env (optional): ``` virtualenv .venv source .venv/bin/activate ``` Install dependencies: ``` pip3 install -r requirements.txt ``` Set database connection parameters in `config.toml` file or set environment variable `DATABASE_URL` with datbase URI: ``` postgres://[USER]:[PASSWORD]@[HOST]:5432/[DATABASE] ``` Run: ``` python app.py ``` ## Run from Docker ``` cd demo docker-compose up -d ``` ## SQL scripts conventions - Use Python-style naming for parameters: `%(schema_name)s`, `%(max_table_count)s` - Keep to [axis](https://gramin.pro/posts/rivers-and-axis) when formatting ## Recomended VS Code plugins For productive and fast work with SQL scripts and Jinja2 templates we use [Visual Studio Code](https://github.com/microsoft/vscode) with some additional plugins: - [Better Jinja](https://marketplace.visualstudio.com/items?itemName=samuelcolvin.jinjahtml) - Syntax highlighting for jinja(2) including HTML, SQL, JSON, Markdown and other templates.

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