Very Basic Question: Biopython And Python 3.X

Question

[User 7219]

This is all very new to me and I'm coming at this from needing an sql resource and was pointed in the direction of python and sqlite. I think the pair in general is just what I've been looking for, but am uncertain how to find which exact bits I should be using, particularly in terms of versions.

I was originally planning on building a resource and application to manipulate my own data, but have to stumbled on a way of making this even better with biopython.

I should be able to functionally map out what I think I need, but before I even get started in earnest I need to get some fundamental bits confirmed:

Should I learn 3.X and just use various modules of 2.7 for the bits of biopython I need, or just keep everything pre-3? This fundamental decision also seems to have a cascading effect on libraries and other resources? (qt, pyqt, sip, scintilla)

sqlite, slqlite3, BioSQL, SQLalchemy? What are the adv/disadvantages of each- where can I find them?

I'm on a windows pc- can you recommend an editor. I've tried dreampie and eric, but again I think there are version issues (with eric?) that need to be addressed before everything can be complied?

Is there are central resource that walks one through the lot?

I've been reading a lot and not having been able to unstuck myself thought I could turn here.

Sorry for the deluge and many thanks in advance...

[Pierre Lindenbaum]

can you tell us more about the application you want to write (type and amount of data, etc...) ?

[David W]

I think the python2 or 3 was the main thrust of your question, but on the editors check out this from stack overflow and this from the main python site.

Answer 1

[Istvan Albert]

From a beginner's perspective the difference between 2.7 and 3.0 is very small. They are different mostly in their low level implementations.

Start with Python 2.6 (stay away from 2.7 for at least a year).

Edit:

The reason for sticking with an older python is that there are delays in porting useful packages to the latest python version. For experts there is a great fun to be had when playing with the latest language features, but for beginners IMHO the fewer disruptions the better.

[Paulo Nuin]

Don't stay away from 2.7; start with 2.6 but get acquainted with 2.7 and even 3.x. Don't be shy, you are starting with the language, don't worry about functionalities that are going to be obsolete soon. I don't understand this posture of "staying away" from new developments, go forward and don't listen to the bad omen cassandras.

[User 7219]

Read the links above and agree there's no present need to unnecessarily confuse myself. Start at the beginning and if I need to move on, hopefully I'll be in a position to do just that when the time comes... Thanks!

[Istvan Albert]

New users can get very discouraged when starting out with the latest python version only to find that the most useful and important libraries like matplotlib, biopython, numpy are not yet available in a precompiled fashion. Many packages lag at least a year behind. I always considered that Python's main strengths are in its external packages and not necessarily the language features.

[Istvan Albert]

But I agree that I should make that point a little more nuanced way and not just saying: "stay away" but I was pressed for time ... ;-)

[Paulo Nuin]

It always easier to go back, in language versions, than move forward sometimes. The language itself is not only made by packages but by the structure, syntax and power. If he starts with 2.7 (or even 3.x) and needs to access some package still not ported he can easily go back to 2.6 and use it with minimal changes.

Answer 2

[User 59]

You might be interested in the discussion here on BioStar about biopython and python3 that might be relevant.

There are also a number of StackOverflow questions on just₂ this₃ topic.

[Brad Chapman]

Biopython is currently working on supporting Python3; there are branches on GitHub but no officially released version yet. In general this is the current state for a lot of Python modules.