Metadata-Version: 2.1
Name: fast-to-sql
Version: 2.1.11
Summary: UNKNOWN
Home-page: https://github.com/jdglaser/fast-to-sql
Author: Jarred Glaser
Author-email: jarred.glaser@gmail.com
License: MIT License
Keywords: pandas,to_sql,fast,sql
Platform: ALL
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: pyodbc

# fast_to_sql

## Introduction

`fast_to_sql` is an improved way to upload pandas dataframes to Microsoft SQL Server.

`fast_to_sql` takes advantage of pyodbc rather than SQLAlchemy. This allows for a much lighter weight import for writing pandas dataframes to sql server. It uses pyodbc's `executemany` method with `fast_executemany` set to `True`, resulting in far superior run times when inserting data. 

## Installation

```python
pip install fast_to_sql
```

## Requirements

* Written for Python 3.8+
* Requires pandas, pyodbc

## Example

```py
from datetime import datetime

import pandas as pd

import pyodbc
from fast_to_sql import fast_to_sql as fts

# Test Dataframe for insertion
df = pd.DataFrame({
    "Col1": [1, 2, 3],
    "Col2": ["A", "B", "C"],
    "Col3": [True, False, True],
    "Col4": [datetime(2020,1,1),datetime(2020,1,2),datetime(2020,1,3)]
})

# Create a pyodbc connection
conn = pyodbc.connect(
    """
    Driver={ODBC Driver 17 for SQL Server};
    Server=localhost;
    Database=my_database;
    UID=my_user;
    PWD=my_pass;
    """
)

# If a table is created, the generated sql is returned
create_statement = fts.fast_to_sql(df, "my_great_table", conn, if_exists="replace", custom={"Col1":"INT PRIMARY KEY"}, temp=False)

# Commit upload actions and close connection
conn.commit()
conn.close()
```

## Usage

### Main function

```python
fts.fast_to_sql(df, name, conn, if_exists="append", custom=None, temp=False)
```

* ```df```: pandas DataFrame to upload
* ```name```: String of desired name for the table in SQL server
* ```conn```: A valid pyodbc connection object
* ```if_exists```: Option for what to do if the specified table name already exists in the database. If the table does not exist a new one will be created. By default this option is set to 'append'
  * __'append'__: Appends the dataframe to the table if it already exists in SQL server.
  * __'fail'__: Purposely raises a `FailError` if the table already exists in SQL server.
  * __'replace'__: Drops the old table with the specified name, and creates a new one. **Be careful with this option**, it will completely delete a table with the specified name in SQL server.
* ```custom```: A dictionary object with one or more of the column names being uploaded as the key, and a valid SQL column definition as the value. The value must contain a type (`INT`, `FLOAT`, `VARCHAR(500)`, etc.), and can optionally also include constraints (`NOT NULL`, `PRIMARY KEY`, etc.)
  * Examples: 
  `{'ColumnName':'varchar(1000)'}` 
  `{'ColumnName2':'int primary key'}`
* ```temp```: Either `True` if creating a local sql server temporary table for the connection, or `False` (default) if not.













