Metadata-Version: 2.1
Name: openmetadata-sqllineage
Version: 1.0.2
Summary: OpenMetadata SQL Lineage for Analysis Tool powered by Python and sqlfluff based on sqllineage.
Home-page: https://github.com/open-metadata/openmetadata-sqllineage
Author: OpenMetadata Committers
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: ci
Provides-Extra: docs
License-File: LICENSE

# SQLLineage
SQL Lineage Analysis Tool powered by Python.

This is a fork authored by the OpenMetadata community, where we are adding `sqlfluff` as a parsing backend instead of `sqlparse`.

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Never get the hang of a SQL parser? SQLLineage comes to the rescue. Given a SQL command, SQLLineage will tell you its
source and target tables, without worrying about Tokens, Keyword, Identifier and all the jagons used by SQL parsers.

Behind the scene, SQLLineage uses the fantastic [`sqlparse`](https://github.com/andialbrecht/sqlparse) library to parse 
the SQL command, and bring you all the human-readable result with ease.

## Demo & Documentation
Talk is cheap, show me a [demo](https://reata.github.io/sqllineage/).

[Documentation](https://sqllineage.readthedocs.io) is online hosted by readthedocs, and you can check the 
[release note](https://sqllineage.readthedocs.io/en/latest/release_note/changelog.html) there.


## Quick Start
Install sqllineage via PyPI:
```bash
$ pip install sqllineage
```

Using sqllineage command to parse a quoted-query-string:
```
$ sqllineage -e "insert into db1.table1 select * from db2.table2"
Statements(#): 1
Source Tables:
    db2.table2
Target Tables:
    db1.table1
```

Or you can parse a SQL file with -f option:
```
$ sqllineage -f foo.sql
Statements(#): 1
Source Tables:
    db1.table_foo
    db1.table_bar
Target Tables:
    db2.table_baz
```

## Advanced Usage

### Multiple SQL Statements
Lineage result combined for multiple SQL statements, with intermediate tables identified:
```
$ sqllineage -e "insert into db1.table1 select * from db2.table2; insert into db3.table3 select * from db1.table1;"
Statements(#): 2
Source Tables:
    db2.table2
Target Tables:
    db3.table3
Intermediate Tables:
    db1.table1
```

### Verbose Lineage Result
And if you want to see lineage result for every SQL statement, just toggle verbose option
```
$ sqllineage -v -e "insert into db1.table1 select * from db2.table2; insert into db3.table3 select * from db1.table1;"
Statement #1: insert into db1.table1 select * from db2.table2;
    table read: [Table: db2.table2]
    table write: [Table: db1.table1]
    table cte: []
    table rename: []
    table drop: []
Statement #2: insert into db3.table3 select * from db1.table1;
    table read: [Table: db1.table1]
    table write: [Table: db3.table3]
    table cte: []
    table rename: []
    table drop: []
==========
Summary:
Statements(#): 2
Source Tables:
    db2.table2
Target Tables:
    db3.table3
Intermediate Tables:
    db1.table1
```

### Column-Level Lineage
We also support column level lineage in command line interface, set level option to column, all column lineage path will 
be printed.

```sql
INSERT OVERWRITE TABLE foo
SELECT a.col1,
       b.col1     AS col2,
       c.col3_sum AS col3,
       col4,
       d.*
FROM bar a
         JOIN baz b
              ON a.id = b.bar_id
         LEFT JOIN (SELECT bar_id, sum(col3) AS col3_sum
                    FROM qux
                    GROUP BY bar_id) c
                   ON a.id = sq.bar_id
         CROSS JOIN quux d;

INSERT OVERWRITE TABLE corge
SELECT a.col1,
       a.col2 + b.col2 AS col2
FROM foo a
         LEFT JOIN grault b
              ON a.col1 = b.col1;
```

Suppose this sql is stored in a file called foo.sql

```
$ sqllineage -f foo.sql -l column
<default>.corge.col1 <- <default>.foo.col1 <- <default>.bar.col1
<default>.corge.col2 <- <default>.foo.col2 <- <default>.baz.col1
<default>.corge.col2 <- <default>.grault.col2
<default>.foo.* <- <default>.quux.*
<default>.foo.col3 <- c.col3_sum <- <default>.qux.col3
<default>.foo.col4 <- col4
```

### Lineage Visualization
One more cool feature, if you want a graph visualization for the lineage result, toggle graph-visualization option

Still using the above SQL file
```
sqllineage -g -f foo.sql
```
A webserver will be started, showing DAG representation of the lineage result in browser:

- Table-Level Lineage

<img src="https://raw.githubusercontent.com/reata/sqllineage/master/docs/_static/table.jpg" alt="Table-Level Lineage">

- Column-Level Lineage

<img src="https://raw.githubusercontent.com/reata/sqllineage/master/docs/_static/column.jpg" alt="Column-Level Lineage">
