Metadata-Version: 2.1
Name: schemarrow
Version: 0.1.0a0
Summary: right out of the box mljar pipeline.
License: MIT
Author: DanielAvdar
Author-email: 66269169+DanielAvdar@users.noreply.github.com
Requires-Python: >=3.9,<3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Provides-Extra: db-dtypes
Requires-Dist: db-dtypes[db-dtypes] (>=1) ; extra == "db-dtypes"
Requires-Dist: pandas (>=2)
Requires-Dist: pyarrow (>=7.0.0)
Description-Content-Type: text/markdown





# SchemArrow
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`SchemArrow` simplifies the conversion between pandas and Arrow DataFrames, allowing you to seamlessly switch back and forth.
**Get started:**
## Get started:
### Installation
To install the package use pip:

```bash
pip install schemarrow
```
### Usage

```python
import pandas as pd
from schemarrow import SchemArrow

# Create a pandas DataFrame
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': ['a', 'b', 'c'],
    'C': [1.1, 2.2, 3.3],
    'D': [True, False, True]
})

# Instantiate a SchemArrow object
arrow_schema = SchemArrow()

# Convert the pandas DataFrame dtypes to arrow dtypes
df_pa: pd.DataFrame = arrow_schema(df)

print(df_pa.dtypes)
```
outputs:
```
A     int64[pyarrow]
B    string[pyarrow]
C    double[pyarrow]
D      bool[pyarrow]
dtype: object
```

