werkzeug

://pypi.org/project/hupper/ 2. https://github.com/django/django/blob/master/django/utils/au... 3. https://github.com/pallets/werkzeug/blob/master/src/werkzeug... 4. https://youtu.be/IghyoR6ld60

ty, I used futurize and huge codebase to great success: https://python-future.org/futurize.html. I started with this: futurize --write --stage1 --unicode-literals --nobackups <files> and https://docs.python.org/2/library/2to3.html 2to3-2.7 -w -n <files> Really helped. Also, wire Travis / your CI system to have your tests run on python 2 and 3. If you want to test your python 3 codebase live on a subdomain / same SQL/NoSQL DB, be careful about jobs/tasks! Pickle version mismatches and stuff. Use a separate redis/whatever DB for the deployments. After you're finally on python 3, you can use https://github.com/asottile/pyupgrade to modern your code. [1] For the other 2%, use conditionals in your requirements file: enum34==1.0.4;python_version<"3" ushlex==0.99.1;python_version<"3"

nts and see if wsgi server is defining environ['wsgi.file_wrapper'] properly. Or more conveniently, you can just set 'USE_X_SENDFILE = True' in your flask settings, and then directly use send_file.

with a type cast - no need to call it again if you know you have a list. copy and deepcopy are implemented in python, and are generic functions that attempt to sniff the type of the object to be copied. They will use the __copy__ magic[4] of the object if it exists, so you can override it in your objects with return self[:]. You need to use these if you have a generator, a list of non-basic types (such as lists of lists, or lists of tuples, or lists of objects). Both functions use a module-level cache and deepcopy will iterate and apply copy there is very little performance degradation by aliasing copy to deepcopy and using it everywhere, although it could save you time by catching bugs. (Edit: scratch that, I got my benchmark wrong - deepcopy will still be slow even if you pass it a shallow list, see comment below, thanks tedunangst) Read the source of copy and deepcopy so you can understand them and can implement your own custom version for more advanced types. Find the file: >>> import copy >>> copy.__file__ /usr/local/python/2.6/lib/copy.pyc Each of these methods has its own use case, if you grep through a well implemented project such as Werkzeug[5] you can find how each is used efficiently. For eg. [:] is used when you know you have a list, such as template variables. list() is used to force into a list, eg. before these vars get to other objects and copy() is used on custom data types, making a copy of environ (which can contain almost anything) and in copying the routing table (which can not be trusted to be a list). [1] Benchmark times taken from: http://stackoverflow.com/questions/2612802/how-to-clone-a-li... which I had bookmarked as a reference [2] http://docs.python.org/faq/programming.html#how-do-i-copy-an... [3] http://docs.python.org/faq/programming.html#how-do-i-convert... [4] http://www.brpreiss.com/books/opus7/html/page85.html [5] https://github.com/mitsuhiko/werkzeug