python-notes | Learning Python : notes and example code
kandi X-RAY | python-notes Summary
kandi X-RAY | python-notes Summary
In my path to learning Python, I'll be collecting my notes and example code here for reference and review purposes. Filenames reflect the topic as much as possible. The data directory contains resources for some of the examples. To date, my training is self-guided through the use of text books and online resources.
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Top functions reviewed by kandi - BETA
- Generate watering schedule
- Append an integer to the list
- Generates pi - series random variates
- Generator for odds generator
- Extract city names from a file
- Factorial i
- Display the inventory
- Create the inventory
- Test for nonlocal variables
- Use this method to withdraw the account
- Generate Fibonacci generator
- Generate a sequence of numbers
- Sum a list of numbers
- Print execution order
- Get the number of milliseconds from the time field
- Fill the walk
- Get input
- List a directory listing
- Calculates the squared of a number
- Generator for the odds generator
- R Calculates the temperature for a given temperature
- Print the execution order
- Decorates a function and prints the result
python-notes Key Features
python-notes Examples and Code Snippets
Community Discussions
Trending Discussions on python-notes
QUESTION
I have the following set up.
...ANSWER
Answered 2020-May-22 at 14:18The problem here is that ~/python/pyct/lib/printer.py
looks for module named utils
in its working directory - not in directory where it is placed itself.
You can use relative import in ~/python/pyct/lib/printer.py:
QUESTION
In this article Nick Coghlan talks about some of the design decisions that went in to the PEP 435 Enum
type, and how EnumMeta
can be subclassed to provide a different Enum
experience.
However, the advice I give (and I am the primary stdlib Enum
author) about using a metaclass is it should not be done without a really good reason -- such as not being able to accomplish what you need with a class decorator, or a dedicated function to hide any ugliness; and in my own work I've been able to do whatever I needed simply by using __new__
, __init__
, and/or normal class/instance methods when creating the Enum
class:
And then there is this cautionary tale of being careful when delving into Enum
, with and without metaclass subclassing:
Given all that, when would I need to fiddle with EnumMeta
itself?
ANSWER
Answered 2019-May-14 at 19:29The best (and only) cases I have seen so far for subclassing EnumMeta
comes from these three questions:
We'll examine the dynamic member case further here.
First, a look at the code needed when not subclassing EnumMeta
:
The stdlib way
QUESTION
So I have the infamous ModuleNotFoundError, and for a couple of hours I can't find the solution. I know that my project works in Pycharm but I wanted to set it up in Visual Studio Code.
the error
...ANSWER
Answered 2018-Nov-07 at 14:55if you want to import Agent in Main.py just use
QUESTION
I have a function that is supposed to generate a tuple of all built-in exceptions, (for use in the except (Exception1, Exception2, etc...) as error:
form) and when I run it normally, it works just fine.
ANSWER
Answered 2017-Dec-20 at 02:15This works, and seems to be the common technique for getting at the builtins module.
QUESTION
I am trying to work on improvements to a pip installed package developed by our team. I am unable to import my improved and additional modules for thoroughly testing before integration into new version. I understand this is likely namespace issues, but i'm unable to resolve them. I've read what I can find, including this excellent blog on import traps.
I am doing my testing and applications for the library methods in Jupyter. In a failed attempt to avoid collision, I have this renamed the top package dir:
...ANSWER
Answered 2017-May-07 at 20:25I'm now able to answer my own question, by piecing together various other stackoverflow answers and blog posts. In the end, the solution was to:
- create a virtual environment,
- create a development version of the working package within that environment, and
- create a jupyter/ipython kernel for the the environment to use in JupyterHub.
Specifically, this is how I achieved those things and the hiccups along the way:
Creating the Virtual EnvironmentThis is all standard conda virtual environments. Install virtualenv. If conda is already installed, use
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install python-notes
You can use python-notes 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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