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Library compatibility is definitely an issue. You still have some very influential libraries that are not Python 3.x compatible. But an oft underestimated issue

Library compatibility is definitely an issue. You still have some very influential libraries that are not Python 3.x compatible. But an oft underestimated issue is the number of Py3 improvements that have been backported to Py2. For example absolute imports. That has made the case for moving to Py3 harder.

takeda 11y ago
Argh, I don't like this argument. There's really barely anything that is python2 specific, most of the things that weren't ported is no longer being maintained. I think the main reason you should start moving to python3 is that it will be discontinued. Python 2.6 was EOL in 2013, 2.7 they've been more generous and you have 4 more years, originally it supposed to be 2015. There's no good reason to stick with 2.7, if you have some legacy apps there's nothing preventing you from having Py2 and Py3 installed side by side. If you need to write libraries that share code, it's much easier to write the code in Py3 and then make it backwards compatible with use of from __future__ ... imports and six module. I feel like people who still complaining about the difficulties did not actually tried Python 3. Py3 is much more enjoyable language to write in.
- pbhowmic 11y ago
  TensorFlow is just the latest library that is Py2 only. App Engine is Py2 only. The bigger issue is the 2 biggest weakness with Py2 that were not addressed in Py3 (CPython version at least) - GIL & JIT. JIT is addressed more or less by PyPy but it is Py2.7-compatible, not Py3 compatible. Addressing this in the standard CPython implementation can make for a very compelling case for move to Py3. Otherwise, it does not buy you much.
  - takeda 11y ago
    TensorFlow and App Engine are both released by Google which prefers Py2 because of the FUD, although regarding TF hopefully it won't be for too long. The first issue created on GitHub[1] is basically about adding Py3 support. Regarding GIL and JIT. Those problems are mostly performance related and not easy. As you mentioned GIL is available everywhere so it's not a good argument regarding py2 vs py3. As for JIT you get it with PyPy which by itself is not 100% compatible with CPython (for example as of now majority of python modules written in C simply won't work). Although they do have PyPy compatible with Python 3 although it is not as stable, but since Py3 is picking up hopefully it will be becoming more popular. For me, it's the other way around, I have not used PyPy primarily because it's compatible 2.7 and I don't use Python for performance, but if I could get performant Py3 implementation then why wouldn't I want to use it? [1] https://github.com/tensorflow/tensorflow/issues/1 https://github.com/tensorflow/tensorflow/issues/1

takeda 11y ago

Argh, I don't like this argument. There's really barely anything that is python2 specific, most of the things that weren't ported is no longer being maintained. I think the main reason you should start moving to python3 is that it will be discontinued. Python 2.6 was EOL in 2013, 2.7 they've been more generous and you have 4 more years, originally it supposed to be 2015. There's no good reason to stick with 2.7, if you have some legacy apps there's nothing preventing you from having Py2 and Py3 installed side by side. If you need to write libraries that share code, it's much easier to write the code in Py3 and then make it backwards compatible with use of from __future__ ... imports and six module. I feel like people who still complaining about the difficulties did not actually tried Python 3. Py3 is much more enjoyable language to write in.

pbhowmic 11y ago
TensorFlow is just the latest library that is Py2 only. App Engine is Py2 only. The bigger issue is the 2 biggest weakness with Py2 that were not addressed in Py3 (CPython version at least) - GIL & JIT. JIT is addressed more or less by PyPy but it is Py2.7-compatible, not Py3 compatible. Addressing this in the standard CPython implementation can make for a very compelling case for move to Py3. Otherwise, it does not buy you much.
- takeda 11y ago
  TensorFlow and App Engine are both released by Google which prefers Py2 because of the FUD, although regarding TF hopefully it won't be for too long. The first issue created on GitHub[1] is basically about adding Py3 support. Regarding GIL and JIT. Those problems are mostly performance related and not easy. As you mentioned GIL is available everywhere so it's not a good argument regarding py2 vs py3. As for JIT you get it with PyPy which by itself is not 100% compatible with CPython (for example as of now majority of python modules written in C simply won't work). Although they do have PyPy compatible with Python 3 although it is not as stable, but since Py3 is picking up hopefully it will be becoming more popular. For me, it's the other way around, I have not used PyPy primarily because it's compatible 2.7 and I don't use Python for performance, but if I could get performant Py3 implementation then why wouldn't I want to use it? [1] https://github.com/tensorflow/tensorflow/issues/1 https://github.com/tensorflow/tensorflow/issues/1