

Cubes - Python Lightweight OLAP - 0.9 released - stefanu
http://blog.databrewery.org/post/23049114551/

======
stefanu
Author here. Just a small explanation: target audience are mostly those who
would like to add OLAP to their apps with simple multi-dimensional reporting
needs (see trivial hello-world example [1]). This release brings new
star/snowflake aggregation browser which can be (roughly) considered to your
analytical data as ORM framework is to your transactional data - some magic
happens between your code and the database that makes your life easier.

Visualisation is not yet included and will be added in modular form of
"presenters" [2]. If anyone with web/JS skills would like to help, he is
welcome, as my skills in this area is little bit weak. There is unmaintained
and unfinished prototype of JavaScript front-end as well [3]. Flask based
example of simple dimension browsing is included in the source [4].

If you need any help with model creation, you encounter any issues, have a
suggestion let me know.

[1]
[https://github.com/Stiivi/cubes/blob/master/examples/hello_w...](https://github.com/Stiivi/cubes/blob/master/examples/hello_world/aggregate.py)

[2] <https://github.com/Stiivi/cubes/issues/53>

[3] <https://github.com/stiivi/cubes.js>

[4]
[https://github.com/Stiivi/cubes/tree/master/examples/sandbox...](https://github.com/Stiivi/cubes/tree/master/examples/sandbox/flask_dimension_browser)

------
sgt
Interesting idea. Ofcourse, OLAP isn't just about the underlying cubes and
dimensions, in the end it's about how the information is being presented to
the user. There's a reason why Microsoft is so good at data warehousing,
because their product is one of the best, and also extremely feature-rich from
the "front end" to the back end.

~~~
systems
well from my experience, working with OLAP Cubes, Microsoft is normally used
when cost saving is important, its considered cheaper than competition. And
the development tools are so easy to use, non-programmers can be trained to
create and customize cubes.

On the front end, they only have excel, which is good, really good, but other
tools have much simpler and in my opinion better clients, for example Cognos
and BO

~~~
slantyyz
You might want to look at OSS options like Pentaho, Jasper and Palo.

Palo (a competitor to Cognos TM1), in particular, is really nice. The other
two leave a little to be desired on the UI side.

------
slantyyz
I haven't encountered a lot of BI nerds who are Pythonistas, but this is a
great contribution nonetheless.

The more open source tools we can get that can begin displacing products like
Cognos and BO, the better.

~~~
bsg75
> BI nerds who are Pythonistas

One here. Very interested to see this project evolve.

~~~
stefanu
Thank you, both. If you have any questions or suggestions, drop me a line or
much better: discuss it on the cubes-discuss google group [1]. I would
appreciate feedback from more experienced BI people than I am.

[1] [https://groups.google.com/forum/?fromgroups#!forum/cubes-
dis...](https://groups.google.com/forum/?fromgroups#!forum/cubes-discuss)

------
dbecker
Is this going to integrate with the broader python ecosystem? I'm specifically
wondering about packages like pyTables, pandas and larry.

~~~
stefanu
I would love to and actually was looking at pyTables and little bit at pandas.
I am coming from RDBMS-based DWH world mostly, so it is a bit new area to me,
howerver from what I've learned so far, there is huge potential.
Unfortunately, currently I have no resources to do that, even I would like to
see that more than RDBS backends (as there are already plenty of tools for
that). Is there any way how this possibility can be supported? I would not
mind working on a project for someone that would require OLAP layer on top of
something "strange" and that there will be (open-source) by-product in form of
a backend...

[edit] p.s.: I am the only developer so far, and I am open for collaboration.

