Are there any Python libraries that provide an abstraction of SQL DDL?
I have an application that needs to dynamically add/adjust database columns, and I don't want to have to model CREATE TABLE and all the datatypes.
I am looking for something relatively lightweight; full ORMs like SQLAlchemy will unfortunately not be available.
Have you looked at SQLAlchemy?
It's an object-relational mapper (abstraction layer) that sits between your python code and the (relational) database.
It does DDL such as create table.
Related
I want to write my SQL queries in Python so that I can make them parameterizable and composable.
I was hoping to do something like the following via SQLAlchemy, but the expression API doesn't seem to support it without automapping my database.
select('*').from_('table')
How can I accomplish that with SQLAlchemy or should I look to use a different tool?
I am new to working with databases and couldn't find any relevant answers for this.
What are the uses of SQLAlchemy over MYSQL CONNECTOR for python.
I do not have much experience with MYSQL CONNECTOR for Python. However, from what I know SQLAlchemy primarily uses ORM (Object-Relational Mapping) in order to abstract the details of handling the database. This can help avoid errors some times (and also introduce possibly introduce others). You might want to have a look at the ORM technique and see if it is for you (but don't use it as a way to avoid learning SQL). Generally, ORMs tend not to be as scalable as raw SQL either.
I am also a newbie. In my understanding SQLAlchemy is an ORM (Object-Relational Mapping) that allows you to abstract the database and query data from the DB more easily in your coding language treating query data as another object. Pros is that that you can more easily switch your DB under the hood. But it has some learning curve.
Whereas MySQL Connector is "just" a plain simple direct connection to the DBMS at your database and you write SQL queries to get the data.
For now I am sticking with the mysql connector to just train SQL queries more. But later on I will definitely test out SQLAlchemy.
I'm pretty new to database and server related tasks. I currently have two tables stored in a MSsql database on a server and I'm trying to use python package sqlalchemy to pull some of the data to my local machine. The first table has default schema dbo, and I was able to use the Connect String
'mssql+pyodbc://<username>:<password>#<dsnname>'
to inspect the table, but the other table has a customized schema, and I don't see any information about the table when I use the previous commands. I assume it is because now the second table has different schema and the python package can't find it anymore.
I was looking at automap hoping the package offers a way to deal with customized schema, but many concepts described in there I don't quite understand and I'm not trying to alter the database just pulling data so not sure if it's the right way, any suggestions?
Thanks
In case of automap you should pass the schema argument when preparing reflectively:
AutomapBase.prepare(reflect=True, schema='myschema')
If you wish to reflect both the default schema and your "customized schema" using the same automapper, then first reflect both schemas using the MetaData instance and after that prepare the automapper:
AutomapBase.metadata.reflect()
AutomapBase.metadata.reflect(schema='myschema')
AutomapBase.prepare()
If you call AutomapBase.prepare(reflect=True, ...) consecutively for both schemas, then the automapper will recreate and replace the classes from the 1st prepare because the tables already exist in the metadata. This will then raise warnings.
I need to read data from MySQL, process it with python script and write the result into Sqlite.
Also, I need to convert MySql create definitions to Sqlite create definitions.
Are there any existing libraries for python to convert MySql data type (including set, enum, timestamp, etc.) to Sqlite data type, or I should write it myself?
Depending on your use case, you could use an ORM library like peewee for abstracting away the MySQL and Sqlite databases.
One possible way of approaching your problem would be to use peewee's model generator for creating models for the MySQL database, which you can later reuse for the Sqlite one using this example as reference.
I am writing a quick and dirty script which requires interaction with a database (PG).
The script is a pragmatic, tactical solution to an existing problem. however, I envisage that the script will evolve over time into a more "refined" system. Given the fact that it is currently being put together very quickly (i.e. I don't have the time to pour over huge reams of documentation), I am tempted to go the quick and dirty route, using psycopg.
The advantages for psycopg2 (as I currently understand it) is that:
written in C, so faster than sqlAlchemy (written in Python)?
No abstraction layer over the DBAPI since works with one db and one db only (implication -> fast)
(For now), I don't need an ORM, so I can directly execute my SQL statements without having to learn a new ORM syntax (i.e. lightweight)
Disadvantages:
I KNOW that I will want an ORM further down the line
psycopg2 is ("dated"?) - don't know how long it will remain around for
Are my perceptions of SqlAlchemy (slow/interpreted, bloated, steep learning curve) true - IS there anyway I can use sqlAlchemy in the "rough and ready" way I want to use psycopg - namely:
execute SQL statements directly without having to mess about with the ORM layer, etc.
Any examples of doing this available?
SQLAlchemy is a ORM, psycopg2 is a database driver. These are completely different things: SQLAlchemy generates SQL statements and psycopg2 sends SQL statements to the database. SQLAlchemy depends on psycopg2 or other database drivers to communicate with the database!
As a rather complex software layer SQLAlchemy does add some overhead but it also is a huge boost to development speed, at least once you learned the library. SQLAlchemy is an excellent library and will teach you the whole ORM concept, but if you don't want to generate SQL statements to begin with then you don't want SQLAlchemy.
To talk with database any one need driver for that. If you are using client like SQL Plus for oracle, MysqlCLI for Mysql then it will direct run the query and that client come with DBServer pack.
To communicate from outside with any language like java, c, python, C#... We need driver to for that database. psycopg2 is driver to run query for PostgreSQL from python.
SQLAlchemy is the ORM which is not same as database driver. It will give you flexibility so you can write your code without any database specific standard. ORM provide database independence for programmer. If you write object.save in ORM then it will check, which database is associated with that object and it will generate insert query according to the backend database.