Python | widely used high-level programming language
kandi X-RAY | Python Summary
kandi X-RAY | Python Summary
Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991. An interpreted language, Python has a design philosophy which emphasizes code readability (notably using whitespace indentation to delimit code blocks rather than curly brackets or keywords), and a syntax which allows programmers to express concepts in fewer lines of code than might be used in languages such as C++ or Java.The language provides constructs intended to enable writing clear programs on both a small and large scale. Python features a dynamic type system and automatic memory management and supports multiple programming paradigms, including object-oriented, imperative, functional programming, and procedural styles. It has a large and comprehensive standard library. Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. CPython, the reference implementation of Python, is open source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.
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Python Examples and Code Snippets
Community Discussions
Trending Discussions on Python
QUESTION
I am trying to get a Flask and Docker application to work but when I try and run it using my docker-compose up
command in my Visual Studio terminal, it gives me an ImportError called ImportError: cannot import name 'json' from itsdangerous
. I have tried to look for possible solutions to this problem but as of right now there are not many on here or anywhere else. The only two solutions I could find are to change the current installation of MarkupSafe and itsdangerous to a higher version: https://serverfault.com/questions/1094062/from-itsdangerous-import-json-as-json-importerror-cannot-import-name-json-fr and another one on GitHub that tells me to essentially change the MarkUpSafe and itsdangerous installation again https://github.com/aws/aws-sam-cli/issues/3661, I have also tried to make a virtual environment named veganetworkscriptenv
to install the packages but that has also failed as well. I am currently using Flask 2.0.0 and Docker 5.0.0 and the error occurs on line eight in vegamain.py.
Here is the full ImportError that I get when I try and run the program:
...ANSWER
Answered 2022-Feb-20 at 12:31I was facing the same issue while running docker containers with flask.
I downgraded Flask
to 1.1.4
and markupsafe
to 2.0.1
which solved my issue.
Check this for reference.
QUESTION
Here are two measurements:
...ANSWER
Answered 2022-Mar-30 at 11:57Combining my comment and the comment by @khelwood:
TL;DR:
When analysing the bytecode for the two comparisons, it reveals the 'time'
and 'time'
strings are assigned to the same object. Therefore, an up-front identity check (at C-level) is the reason for the increased comparison speed.
The reason for the same object assignment is that, as an implementation detail, CPython interns strings which contain only 'name characters' (i.e. alpha and underscore characters). This enables the object's identity check.
Bytecode:
QUESTION
I saw a video about speed of loops in python, where it was explained that doing sum(range(N))
is much faster than manually looping through range
and adding the variables together, since the former runs in C due to built-in functions being used, while in the latter the summation is done in (slow) python. I was curious what happens when adding numpy
to the mix. As I expected np.sum(np.arange(N))
is the fastest, but sum(np.arange(N))
and np.sum(range(N))
are even slower than doing the naive for loop.
Why is this?
Here's the script I used to test, some comments about the supposed cause of slowing done where I know (taken mostly from the video) and the results I got on my machine (python 3.10.0, numpy 1.21.2):
updated script:
...ANSWER
Answered 2021-Oct-16 at 17:42From the cpython source code for sum
sum initially seems to attempt a fast path that assumes all inputs are the same type. If that fails it will just iterate:
QUESTION
version pip 21.2.4 python 3.6
The command:
...ANSWER
Answered 2021-Nov-19 at 13:30It looks like setuptools>=58
breaks support for use_2to3
:
So you should update setuptools
to setuptools<58
or avoid using packages with use_2to3
in the setup parameters.
I was having the same problem, pip==19.3.1
QUESTION
I have an array of positive integers. For example:
...ANSWER
Answered 2022-Feb-27 at 22:44This problem has a fun O(n) solution.
If you draw a graph of cumulative sum vs index, then:
The average value in the subarray between any two indexes is the slope of the line between those points on the graph.
The first highest-average-prefix will end at the point that makes the highest angle from 0. The next highest-average-prefix must then have a smaller average, and it will end at the point that makes the highest angle from the first ending. Continuing to the end of the array, we find that...
These segments of highest average are exactly the segments in the upper convex hull of the cumulative sum graph.
Find these segments using the monotone chain algorithm. Since the points are already sorted, it takes O(n) time.
QUESTION
I am making simple image of my python Django app in Docker. But at the end of the building container it throws next warning (I am building it on Ubuntu 20.04):
...ANSWER
Answered 2021-Aug-29 at 08:12The way your container is built doesn't add a user, so everything is done as root.
You could create a user and install to that users's home directory by doing something like this;
QUESTION
I need to calculate the square root of some numbers, for example √9 = 3
and √2 = 1.4142
. How can I do it in Python?
The inputs will probably be all positive integers, and relatively small (say less than a billion), but just in case they're not, is there anything that might break?
Related
- Integer square root in python
- Is there a short-hand for nth root of x in Python?
- Difference between **(1/2), math.sqrt and cmath.sqrt?
- Why is math.sqrt() incorrect for large numbers?
- Python sqrt limit for very large numbers?
- Which is faster in Python: x**.5 or math.sqrt(x)?
- Why does Python give the "wrong" answer for square root? (specific to Python 2)
- calculating n-th roots using Python 3's decimal module
- How can I take the square root of -1 using python? (focused on NumPy)
- Arbitrary precision of square roots
Note: This is an attempt at a canonical question after a discussion on Meta about an existing question with the same title.
...ANSWER
Answered 2022-Feb-04 at 19:44math.sqrt()
The math
module from the standard library has a sqrt
function to calculate the square root of a number. It takes any type that can be converted to float
(which includes int
) as an argument and returns a float
.
QUESTION
I have a dockerfile that currently only installs pip-tools
...ANSWER
Answered 2022-Feb-05 at 16:30It is a bug, you can downgrade using:
pip install "pip<22"
QUESTION
After upgrading to Django 4.0, I get the following error when running python manage.py runserver
ANSWER
Answered 2022-Jan-10 at 21:38django.conf.urls.url()
was deprecated in Django 3.0, and is removed in Django 4.0+.
The easiest fix is to replace url()
with re_path()
. re_path
uses regexes like url
, so you only have to update the import and replace url
with re_path
.
QUESTION
This code:
...ANSWER
Answered 2022-Feb-04 at 21:21I suspect this may have been an accident, though I prefer the new behavior.
The new behavior is a consequence of a change to how the bytecode for *
arguments works. The change is in the changelog under Python 3.9.0 alpha 3:
bpo-39320: Replace four complex bytecodes for building sequences with three simpler ones.
The following four bytecodes have been removed:
- BUILD_LIST_UNPACK
- BUILD_TUPLE_UNPACK
- BUILD_SET_UNPACK
- BUILD_TUPLE_UNPACK_WITH_CALL
The following three bytecodes have been added:
- LIST_TO_TUPLE
- LIST_EXTEND
- SET_UPDATE
On Python 3.8, the bytecode for f(*a, a.pop())
looks like this:
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Install Python
You can use Python like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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