macky | Python Script to change MAC address in linux
kandi X-RAY | macky Summary
kandi X-RAY | macky Summary
This python script is compatable with both python 2.x as well as python 3.x and works on linux. The script is used to change the mac address of any network interface easily. You can use the -h option to display all options available in the script.
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Top functions reviewed by kandi - BETA
- Change the MAC of an interface
- Find the MAC address
macky Key Features
macky Examples and Code Snippets
Community Discussions
Trending Discussions on macky
QUESTION
I'm having a trouble on how can I retain the navigation bar when going to the next page in flutter, I've been using curved_navigation_bar
and when I click dashboard bar it goes to the next page, but the problem is the navigation bar did not retain at all. It would be great if anybody could figure out, thank you so much in advance!.
Navigation bar page
...ANSWER
Answered 2021-Apr-07 at 06:13UPDATED:
QUESTION
I have a problem with openpyxl package. To illustrate the isue, I have prepared a simple example.
I have an excel file which contains nothing but formula =A1
in B1
cell. I would like to (1) write a value of 123 into cell A1
, (2) save the workbook, (3) open it again and (4) read a content of cell B1
. Instead of 123
I get None
. Below you can find a simple code, which (I hope) should do as just described. Can anyone see, what I am doing wrong?
ANSWER
Answered 2018-Sep-12 at 15:58openpyxl does not and will not calculate the result of formulas, hence the formula B1=A1 will only be calculated when you open the excel sheet or use another program that will calculate it. There are other libraries that I believe can help, like pycel.
QUESTION
My original question was about parallelism under Python. However, since the question remained without an answer I deleted it and I try to summarize my conclusions. Hopefully it will help someone...
In general there are two main ways to make your code running parallel - either by using multithreading or multiprocessing library.
According to many posts on stackoverflow.com multithreading library is able to share memory effectively across threads but runs the threads on a single core. Therefore it can speed up your code mainly if the bottleneck are I/O operations. I am not sure if there are many real life applications for the library...
If your code is CPU intensive (sometimes called CPU bounded), multiprocessing library could be answer to your problem. The library spreads the threads across individual cores. However, many people (including me) observed that such a multicore code can be significantly slower its singlecore counterpart. The issue is supposedly caused by the fact that individual threads are not able to effectively share memory - data is extensively copied, which creates quite an overhead. As my below code illustrates the overhead is hugely dependent on input data type. The problem is according to many more profound on Windows than on Linux. I have to say that parallelism is my biggest Python disappointment - apparently Python was not designed with parallelism in mind...
The first piece of code allocates pandas dataframe
between cores using Process
.
ANSWER
Answered 2017-Nov-25 at 21:14Multiprocessing works best when parts of a problem can be calculated independantly, e.g. with a multiprocessing.Pool
.
Every worker process in the pools processes part of the input and returns a result to the master process.
If all processes need to modify data all over the input arrays, then it is likely that the syncronization overhead from the manager
destroys any gains from multiprocessing.
QUESTION
Does anybody know how to modify the following code so that the graph is updated every time I change a goniometric function? The plotting is done in function plot()
. There are some related threads on stackoverflow, but I was not able to apply them on my example code...
Many thx,
Macky
...ANSWER
Answered 2017-Dec-01 at 22:59You should create empty plot on canvas and later only replace data in plot using a.set_xdata()
, a.set_ydata()
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Install macky
You can use macky 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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