python-3.6

I want to annotate a type of a variable in a for -loop. I tried this: for i: int in range(5): pass But it didn't work, obviously. What I expect is working autocomplete in PyCharm 2016.3.2. Pre-annotation like this: i: int for i in range(5): pass doesn't help. P.S. Pre-annotation works for PyCharm >= 2017.1 According to PEP 526 , this is not allowed: In addition, one cannot annotate variables used in a for or with statement ; they can be annotated ahead of time, in a similar manner to tuple unpacking Annotate it before the loop: i: int for i in range(5): pass PyCharm 2018.1 and up now

A simple snippet in Python 3.6.1: import datetime j = iter(datetime.datetime.now, None) next(j) returns: Traceback (most recent call last): File "<stdin>", line 1, in <module> StopIteration instead of printing out the classic now() behavior with each next() . I've seen similar code working in Python 3.3, am I missing something or has something changed in version 3.6.1? This is definitely a bug introduced in Python 3.6.0b1. The iter() implementation recently switched to using _PyObject_FastCall() (an optimisation, see issue 27128 ), and it must be this call that is breaking this. The same issue

I'm using Ubuntu 16.04, which comes with Python 2.7 and Python 3.5. I've installed Python 3.6 on it and symlink python3 to python3.6 through alias python3=python3.6 . Then, I've installed virtualenv using sudo -H pip3 install virtualenv . When I checked, the virtualenv got installed in "/usr/local/lib/python3.5/dist-packages" location, so when I'm trying to create virtualenv using python3 -m venv ./venv1 it's throwing me errors: Error Command: ['/home/wgetdj/WorkPlace/Programming/Python/myvenv/bin/python3', '-Im', 'ensurepip', '--upgrade', '--default-pip'] What should I do? We usually use $

I'm trying to install tensorflow onto a Mac with Python3.7. However, I'm getting the error: $ pip3 -v install tensorflow ... Skipping link https://files.pythonhosted.org/packages/56/7a/c6bca0fe52a94ca508731d8b139e7dbd5a36cddc64c19f422f97e5a853e8/tensorflow-1.10.0rc1-cp36-cp36m-win_amd64.whl#sha256=3ab24374888d6a13d55ce2e3cf4ba0c9cd6f824723313db5322512087525cb78 (from https://pypi.org/simple/tensorflow/); it is not compatible with this Python Could not find a version that satisfies the requirement tensorflow (from versions: ) Cleaning up... Removed build tracker '/private/var/folders/4n

I have a function that mimics range(). I am stuck at one point. I need to be able to make the first (x) and third (step) arguments optional, but the middle argument (y) mandatory. In the code below, everything works except the two commented out lines. If I am only passing in one argument, how do I construct the function to accept the single passed in argument as the mandatory (y) argument? I cannot do this: def float_range(x=0, y, step=1.0): Non-default parameter cannot follow a default parameter. def float_range(x, y, step=1.0): if x < y: while x < y: yield x x += step else: while x > y:

I just started the PyTorch-Tutorial Deep Learning with PyTorch: A 60 Minute Blitz and I should add, that I haven't programmed any python (but other languages like Java) before. Right now, my Code looks like import torch import torchvision import torchvision.transforms as transforms import matplotlib.pyplot as plt import numpy as np print("\n-------------------Backpropagation-------------------\n") transform = transforms.Compose( [transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]) trainset = torchvision.datasets.CIFAR10(root='./data', train=True,download=True,