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How can I call stored procedures of sql server with sqlAlchemy?
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One of the key aspects of any data science workflow is the sourcing, cleaning, and storing of raw data in a form that can be used upstream. This process is commonly referred to as “Extract-Transform-Load,” or ETL for short.
SQLAlchemy is the ORM of choice for working with relational databases in python. The reason why SQLAlchemy is so popular is because it is very simple to implement, helps you develop your code quicker and doesn't require knowledge of SQL to get started.
The create_engine() method of sqlalchemy library takes in the connection URL and returns a sqlalchemy engine that references both a Dialect and a Pool, which together interpret the DBAPI's module functions as well as the behavior of the database.
If you want to view your data in a more schema-centric view (as used in SQL), use Core. If you have data for which business objects are not needed, use Core. If you view your data as business objects, use ORM. If you are building a quick prototype, use ORM.
Engines and Connections have an execute() method you can use for arbitrary sql statements, and so do Sessions. For example:
results = sess.execute('myproc ?, ?', [param1, param2]) You can use outparam() to create output parameters if you need to (or for bind parameters use bindparam() with the isoutparam=True option)
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