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Loading data from a (MySQL) database into Django without models

This might sound like a bit of an odd question - but is it possible to load data from a (in this case MySQL) table to be used in Django without the need for a model to be present?
I realise this isn't really the Django way, but given my current scenario, I don't really know how better to solve the problem.
I'm working on a site, which for one aspect makes use of a table of data which has been bought from a third party. The columns of interest are liklely to remain stable, however the structure of the table could change with subsequent updates to the data set. The table is also massive (in terms of columns) - so I'm not keen on typing out each field in the model one-by-one. I'd also like to leave the table intact - so coming up with a model which represents the set of columns I am interested in is not really an ideal solution.
Ideally, I want to have this table in a database somewhere (possibly separate to the main site database) and access its contents directly using SQL.

You can always execute raw SQL directly against the database: see the docs.

There is one feature called inspectdb in Django. for legacy databases like MySQL , it creates models automatically by inspecting your db tables. it stored in our app files as models.py. so we don't need to type all column manually.But read the documentation carefully before creating the models because it may affect the DB data ...i hope this will be useful for you.

I guess you can use any SQL library available for Python. For example : http://www.sqlalchemy.org/
You have just then to connect to your database, perform your request and use the datas at your will. I think you can't use Django without their model system, but nothing prevents you from using another library for this in parallel.

Dynamic Scalable Mysql Table

Here is my situation. I used Python, Django and MySQL for a web development.
I have several tables for form posting, whose fields may change dynamically. Here is an example.
Like a table called Article, it has three fields now, called id INT, title VARCHAR(50), author VARCHAR(20), and it should be able store some other values dynamically in the future, like source VARCHAR(100) or something else.
How can I implement this gracefully? Is MySQL be able to handle it? Anyway, I don't want to give up MySQL totally, for that I'm not really familiar with NoSQL databases, and it may be risky to change technique plan in the process of development.
Any ideas welcome. Thanks in advance!

You might be interested in this post about FriendFeed's schemaless SQL approach.
Loosely:
Store documents in JSON, extracting the ID as a column but no other columns
Create new tables for any indexes you require
Populate the indexes via code
There are several drawbacks to this approach, such as indexes not necessarily reflecting the actual data. You'll also need to hack up django's ORM pretty heavily. Depending on your requirements you might be able to keep some of your fields as pure DB columns and store others as JSON?

I've never actually used it, but django-not-eav looks like the tool for the job.
"This app attempts the impossible: implement a bad idea the right way." I already love it :)
That said, this question sounds like a "rethink your approach" situation, for sure. But yes, sometimes that is simply not an option...

How to perform this insert into PostgreSQL using MySQL data?

I'm in the processing of moving over a mysql database to a postgres database. I have read all of the articles presented here, as well as reading over some of the solutions presented on stackoverflow. The tools recommended don't seem to work for me. Both databases were generated by Django's syncdb, although the postgres db is more or less empty at the moment. I tried to migrate the tables over using Django's built in dumpdata / loaddata functions and its serializers, but it doesn't seem to like a lot of my tables, leading me to believe that writing a manual solution might be best in this case. I have code to verify that the column headers are the same for each table in the database and that the matching tables exist- that works fine. I was thinking it would be best to just grab the mysql data row by row and then insert it into the respective postgres table row by row (I'm not concerned with speed atm). The one thing is, I don't know what's the proper way to construct the insert statement. I have something like:
table_name = retrieve_table()
column_headers = get_headers(table_name) #can return a tuple or a list
postgres_cursor = postgres_con.cursor()
rows = mysql_cursor.fetchall()
for row in rows: #row is a tuple
postgres_cursor.execute(????)
Where ??? would be the insert statement. I just don't know what the proper way is to construct it. I have the table name that I would like to insert into as a string, I have the column headers that I can treat as a list, tuple, or string, and I have the respective values that I'd like to insert. What would be the recommended way to construct the statement? I have read the documentation on psycopg's documentation page and I didn't quite see the way that would satisfy my needs. I don't know (or think) this is the entirely correct way to properly migrate, so if someone could steer me in the correct way or offer any advice I'd really appreciate it.

Materialize data from cache table to production table [PostgreSQL]

I am trying to find the best solution (perfomance/easy code) for the following situation:
Considering a database system with two tables, A (production table) and A'(cache table):
Future rows are added first into A' table in order to not disturb the production one.
When a timer says go (at midnight, for example) rows from A' are incorporated to A.
Dealing with duplicates, inexistent rows, etc have to be considerated.
I've been reading some about Materialized Views, Triggers, etc. The problem is that I should not introduce so much noise in the production table because is the reference table for a server (a PowerDNS server in fact).
So, what do you guys make of it? Should I better use triggers, MV, or programatically outside of the database?? (I'm using python, BTW)
Thanks in advance for helping me.

The "best" solution according to the criteria you've laid out so far would just be to insert into the production table.
...unless there's actually something extremely relevant you're not telling us

Work with Postgres/PostGIS View in SQLAlchemy

Two questions:
i want to generate a View in my PostGIS-DB. How do i add this View to my geometry_columns Table?
What i have to do, to use a View with SQLAlchemy? Is there a difference between a Table and View to SQLAlchemy or could i use the same way to use a View as i do to use a Table?
sorry for my poor english.
If there a questions about my question, please feel free to ask so i can try to explain it in another way maybe :)
Nico

Table objects in SQLAlchemy have two roles. They can be used to issue DDL commands to create the table in the database. But their main purpose is to describe the columns and types of tabular data that can be selected from and inserted to.
If you only want to select, then a view looks to SQLAlchemy exactly like a regular table. It's enough to describe the view as a Table with the columns that interest you (you don't even need to describe all of the columns). If you want to use the ORM you'll need to declare for SQLAlchemy that some combination of the columns can be used as the primary key (anything that's unique will do). Declaring some columns as foreign keys will also make it easier to set up any relations. If you don't issue create for that Table object, then it is just metadata for SQLAlchemy to know how to query the database.
If you also want to insert to the view, then you'll need to create PostgreSQL rules or triggers on the view that redirect the writes to the correct location. I'm not aware of a good usage recipe to redirect writes on the Python side.