Metadata-Version: 2.1
Name: SQLServerToPandasDataFrame-germanandresjejencortes
Version: 0.0.2
Summary: Query Data from a Private DataBase and save it in a Pandas DataFrame
Home-page: https://github.com/AndresJejen/MicrosoftSQLServerToPandasDataFrame
Author: Andres Jejen
Author-email: gajcam@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pyodbc
Requires-Dist: pandas

# MicrosoftSQLServerToPandasDataFrame

## Description

This package query data from any SQL Server Database and parse it into a Pandas Dataframe
it can be useful for pipelines process and speed up your development process.

## Usage

```
from SQLServerToPandasDataFrame import createConnection, runQuery

Base_Query = "select * from [DataBase].dbo.Table"

server = "HOST_DIRECTION"
user = "USER_NAME"
password = "PASSWORD"

conn = createConnection("MyDataBase", server, user, password)
print(runQuery(query1, conn))
```

## Settings

This package performs by default all the connections to a SQL Server using ``ODBC Driver 17 for SQL Server`` driver. if you wanna use a different driver, please replace add the driver parameter in create Connection method.

```
conn = createConnection("MyDataBase", server, user, password, driver = "DRIVER OF YOUR PREFERENCE")
```


```
conn = createConnection("MyDataBase", server, user, password, driver = "ODBC Driver 17 for SQL Server")
```

We use ``Pyodbc `` as ODBC access library, for more driver options please ckeck the documentation [PyODBC Documentation](https://github.com/mkleehammer/pyodbc).

## Collaborators

- GermÃ¡n AndrÃ©s JejÃ©n CortÃ©s [@andres_jejen on twitter](https://twitter.com/andres_jejen)

