# Introduction

A Column Level Lineage Graph for SQL.

Have you ever wondered what is the column level relationship among your SQL scripts and base tables? 
Don't worry, this tool is intended to help you by creating an interactive graph on a webpage to explore the 
column level lineage among them(Currently only supports Postgres, other connection types or dialects are under development).

## How to run
Here is a [live demo](https://zshandy.github.io/lineagex-demo/) with the [mimic-iv concepts_postgres](https://github.com/MIT-LCP/mimic-code/tree/main/mimic-iv/concepts_postgres) files([navigation instructions](https://sfu-db.github.io/lineagex/output.html#how-to-navigate-the-webpage)) and that is created with one line of code:

```python
from lineagex.lineagex import lineagex
  
lineagex(sql=path/to/sql, target_schema="schema1", conn_string="postgresql://username:password@server:port/database", search_path_schema="schema1, public")
```
Check out more detailed usage and examples [here](https://sfu-db.github.io/lineagex/api.html). 

## What does it output
The input can be a path to a SQL file, a path to a folder containing SQL files, a list of SQLs or a list of view names and/or schemas. Optionally, you can provide less information with only the SQLs, but providing the schema information and database connection is highly recommended for the best result.
The output would be a output.json and a index.html file in the folder. Start a local http server and you would be able to see the interactive graph.
<img src="https://raw.githubusercontent.com/sfu-db/lineagex/main/docs/example.gif"/>
Check out more detailed navigation instructions [here](https://sfu-db.github.io/lineagex/output.html#how-to-navigate-the-webpage).

## Why use LineageX
A general introduction of the project can be found in this [blog post](https://medium.com/@shz1/lineagex-the-python-library-for-your-lineage-needs-5e51b77a0032).
- Automatic dependency creation: When there are dependency among the SQL files, and those tables are not yet in the database, LineageX will automatically tries to find the dependency table and creates it.
- Clean and simple but very interactive user interface: The user interface is very simple to use with minimal clutters on the page while showing all of the necessary information.
- Variety of SQL statements: LineageX supports a variety of SQL statements, aside from the typical `SELECT` statement, it also supports `CREATE TABLE/VIEW [IF NOT EXISTS]` statement as well as the `INSERT` and `DELETE` statement.
- [dbt](https://docs.getdbt.com/) support: LineageX also implemented in the [dbt-LineageX](https://github.com/sfu-db/dbt-lineagex), it is added into a dbt project and by using the dbt library [fal](https://github.com/fal-ai/fal), it is able to reuse the Python core and create the similar output from the dbt project.

# Supported Database Connection Types
When entering the `conn_string` parameter, only supported databases' connection types can be parsed successfully, or the lineage graph would be created as if no `conn_string` parameter is given.

## Database Connection Types
- [x] Postgres
- [x] dbt-Postgres
- [ ] Mysql
- [ ] Sqlite
- [ ] SQL Server
- [ ] Oracle
- [ ] ...


# Documentation
Doc: https://sfu-db.github.io/lineagex/intro.html or just [here](https://sfu-db.github.io/lineagex/intro.html)