<div align="center">
<img src="./assets/xorbits-logo.png" width="180px" alt="xorbits" />
# Xorbits SQL: made pandas and SQL APIs work seamlessly together
[](https://pypi.org/project/xorbits_sql/)
[](https://github.com/xorbitsai/xorbits_sql/blob/main/LICENSE)
[](https://actions-badge.atrox.dev/xorbitsai/xorbits_sql/goto?ref=main)
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[](https://twitter.com/xorbitsio)
Xorbits SQL provides a SQL interface built on [Xorbits](https://github.com/xorbitsai/xorbits),
allowing you to fluidly combine pandas and SQL to solve problems using the most familiar interface.
</div>
<br />
<div align="center">
<i><a href="https://join.slack.com/t/xorbitsio/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA">👉 Join our Slack community!</a></i>
</div>
**Xorbits SQL is still at an early development stage and under active improvement.
Please feel free to provide feedback if you encounter any issues or have any suggestion.**
## Key features
🌟 **Pandas and SQL APIs in one**: The popular pandas and SQL APIs now work seamlessly together.
⚡️**Out-of-core and distributed capabilities**: Thanks to the underlying Xorbits execution engine,
out-of-core and distributed runtimes are natively supported.
🔌 **Mainstream SQL dialects compatible**: By leveraging [SQLGlot](https://github.com/tobymao/sqlglot) as the SQL parser,
Xorbits SQL is compatible with many dialects including DuckDB, Presto, Spark, Snowflake, and BigQuery.
## Getting Started
Xorbits SQL can be installed via pip from PyPI. It is highly recommended to create a new virtual
environment to avoid conflicts.
### Installation
```bash
$ pip install "xorbits_sql"
```
### Quick Start
Xorbits SQL provides a single API `execute()` which will return an Xorbits DataFrame.
```python
import xorbits.pandas as pd
import xorbits_sql as xsql
df = pd.DataFrame({"a": [1, 2, 3], "b": ['a', 'b', 'a']})
# SQL
sql = """
select b, AVG(a) as result
from t
group by b
"""
df2 = xsql.execute(
sql,
dialect=None, # optional, replace with SQL dialect, e.g. "duckdb"
tables={'t': df} # register table, table name to Xorbits DataFrame
)
print(df2)
```
## License
[Apache 2](LICENSE)
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