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1. Top results related to what is a non-trivial graph example of function in python code generator

   • What is the point of a function in a simple code [beginner Python]

     Top Answer

     Answered Jan 15, 2018 · 0 votes

     In this particular instance, there's effectively no difference. The point of functions is that you can reuse and maintain code much more easily. For example, if you were repeating this 10 times without functions and you wanted to add "raven" to the bird types, you'd have to add it to all 10 places where you defined the bird types. Having it in a function, you'd only have to change it once.

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     1/5

   • What is the code of read() function in python?

     Top Answer

     Answered Sep 28, 2018 · 0 votes

     As others already mentionned, there's no read() function in Python - what you're looking for (as confirmed in a comment) is the read() method of the file object (Python 2.x) or _io.TextIOWrapper object (Python3.x) , so the correct call to inspect would be (assuming Python 2.x):

     inspect.getsource(file.read)-

     Also note that we're NOT calling (no parens) the method or function passed to getsource(), as it would instead pass the function or method call result instead of the function or method itself.

     But anyway: the code you're looking for is written in C, not in Python, so inspect can't do much for you here. You'll have to check the C source code here:

     https://github.com/python/cpython/blob/master/Modules/_io/fileio.c

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     2/5

   • What is a maximum number of arguments in a Python function?

     Top Answer

     Answered Jan 25, 2020 · 36 votes

     In Python 3.7 and newer, there is no limit. This is the result of work done in issue #27213 and issue #12844; #27213 reworked the CALL_FUNCTION* family of opcodes for performance and simplicity (part of 3.6), freeing up the opcode argument to only encode a single argument count, and #12844 removed the compile-time check that prevented code with more arguments from being compiled.

     So as of 3.7, with the EXTENDED_ARG()

     opcode, there is now no limit at all on how many arguments you can pass in using explicit arguments, save how many can be fitted onto the stack (so bound now by your memory):

     >>> import sys>>> sys.version_infosys.version_info(major=3, minor=7, micro=0, releaselevel='alpha', serial=2)>>> def f(*args, **kwargs): pass...>>> exec("f({})".format(', '.join(map(str, range(256)))))>>> exec("f({})".format(', '.join(map(str, range(2 ** 16)))))

     Do note that lists, tuples and dictionaries are limited to sys.maxsize

     elements, so if the called function uses *args and/or **kwargs catch-all parameters then those are limited.

     For the *args and **kwargs call syntax (expanding arguments) there are no limits other than the same sys.maxint size limits on Python standard types.

     In versions before Python 3.7, CPython has a limit of 255 explicitly passed arguments in a call:

     >>> def f(*args, **kwargs): pass...>>> exec("f({})".format(', '.join(map(str, range(256)))))Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<string>", line 1SyntaxError: more than 255 arguments

     This limitation is in place because until Python 3.5, the CALL_FUNCTION

     opcode overloaded the opcode argument to encode both the number of positional and keyword arguments on the stack, each encoded in a single byte.

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     3/5

   • What is in the meaning of `return "DONE"` at the end of a function in Python?

     Top Answer

     Answered May 29, 2019 · 2 votes

     If you were to run the function in a variable assignment you would literally get "DONE". I'm assuming you mean "DONE" instead of "HOME" since there is no return "HOME" in your example.

     For instance:

     x = per(7)print(x)

     Would print the usual output and also print DONE when you called print(x). Because 7 is a single digit the condition if len(str(n)) == 1 is met on the first run..

     TOTAL STEPS 0DONE

     This function calls itself though, which makes it a confusing choice to learn about this stuff since that's fairly unusual. If we run the script with a number with more than one digit, we'll get None instead.. because it never runs the return statement, it's return value is the python default, which is a NoneType:

     x = per(27)print(x)

     Result:

     144TOTAL STEPS 2None

     Because 27 doesn't meet the condition of having a single digit.. the script calls itself with the results it's printing out.. until it finally uses 4.. which meets the condition and prints out the TOTAL STEPS line.

     To see this value we have to modify the function:

     def per(n, steps = 0): if len(str(n)) == 1: print("TOTAL STEPS " + str(steps)) return "DONE" steps += 1 digits = [int(i) for i in str(n)] result = 1 for j in digits: result *= j print(result) x = per(result, steps) print("Inner return", x)x = per(27)print("Outer return", x)

     Result:

     144TOTAL STEPS 2Inner return DONEInner return NoneOuter return None

     Thankfully you don't have to worry too much about return values.. since you aren't capturing the return value in a variable in your example.. just using return by itself would have the same result. Which is to stop running the function at that point, and to move on to the line after per(27) if there was one.. it can be a useful way to see what's happening in this function though.

     Using variable assignment with = is not the only way to use a return value.. just the easiest way to demonstrate what's happening. for instance just running print(per(27)) would have the same result as my example.

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     4/5

   • What is a basic example of single inheritance using the super() keyword in Python?

     Top Answer

     Answered Apr 20, 2015 · 26 votes

     In Python >=3.0, like this:

     class Foo(): def __init__(self, frob, frotz) self.frobnicate = frob self.frotz = frotz-class Bar(Foo): def __init__(self, frob, frizzle) super().__init__(frob, 34) self.frazzle = frizzle

     Read more here: http://docs.python.org/3.1/library/functions.html#super

     EDIT: As said in another answer, sometimes just using Foo.__init__(self, frob, 34) can be the better solution. (For instance, when working with certain forms of multiple inheritance.)

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     5/5

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2. stackoverflow.com · questions · 1756096Understanding generators in Python - Stack Overflow

   stackoverflow.com · questions · 1756096

   

   May 20, 2018 · A generator is simply a function which returns an object on which you can call next, such that for every call it returns some value, until it raises a StopIteration exception, signaling that all values have been generated. Such an object is called an iterator. Normal functions return a single value using return, just like in Java.

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4. datagy.io · python-matplotlib-plot-functionHow to Plot a Function in Python with Matplotlib • datagy

   datagy.io · python-matplotlib-plot-function

   

   • How to Plot A Function in Python Using Matplotlib
   • How to Plot A Function Using Seaborn
   • Conclusion

   In order to plot a function in Python using Matplotlib, we need to define a range of x and y values that correspond to that function. In order to do this, we need to: 1. Define our function, and 2. Create a range of continuous x-values and map their corresponding y-values Let’s see how we can accomplish this. First, we’ll need to import our librari...

   See full list on datagy.io

   In this section, you’ll learn how to use Seaborn to plot two functions. Since this process is very similar to using just Matplotlib, I won’t cover every detail, but rather explain what is different from our Matplotlib implementation. Take a look at the code block below: Let’s break down what we did in the code block above: 1. We imported Seaborn an...

   See full list on datagy.io

   In conclusion, plotting a function using Python’s Matplotlib and Seaborn libraries can be a powerful way to visualize data and gain insights into relationships between variables. By using NumPy’s linspace function, we can easily create x and y values to represent the function. With Matplotlib, we can plot the function, add a title and legend, and c...

   See full list on datagy.io

5. www.geeksforgeeks.org · plot-mathematicalPlot Mathematical Expressions in Python using Matplotlib

   www.geeksforgeeks.org · plot-mathematical

   

   Jun 16, 2022 · In this article, we will plot two dotted lines and set markers using various functions of the matplotlib package in the python programming language. We can use the pyplot.plot along with the linestyle parameter function to draw the dotted line. matplotlib.pyplot.plot(array1,array2,linestyle='dotted') Note: To set the marker, we have to use the labe

6. www.machinelearningplus.com · plots · top-50-matploTop 50 matplotlib Visualizations - The Master Plots (w/ Full ...

   www.machinelearningplus.com · plots · top-50-matplo

   

   A compilation of the Top 50 matplotlib plots most useful in data analysis and visualization. This list lets you choose what visualization to show for what situation using python’s matplotlib and seaborn library.

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7. cerfacs.fr · coop · pycallgraphGenerating and using a Callgraph, in Python · The COOP Blog

   cerfacs.fr · coop · pycallgraph

   

   Oct 11, 2022 · To visualize results, we will use a non-python resource : Graphviz. Read the download section to find your way out. At CERFACS most of the user will get it on OSX using. brew install graphviz. (Beware, brew can mess up your Python installation by upgrading it). This tutorial will use pycallgraph3, which we install this way: pip install pycallgraph3

8. matplotlib.org · stable · tutorialsPyplot tutorial — Matplotlib 3.9.2 documentation

   matplotlib.org · stable · tutorials

   

   matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.

9. People also ask

   What is a call graph in Python?

   • (Si, questi sono bucatini…) The call graph is a log of the different routines calling each other. It traces what the reader would look if he were to perform an exhaustive read in the chronological order. An execution call graph generated for a simple computer program in Python.

   Generating and using a Callgraph, in Python · The COOP Blog

   cerfacs.fr/coop/pycallgraph

   See all results for this question

   Which Python code uses a generator?

   • Consider the following code that uses a generator: pp, p = 0, 1 while 1: yield pp pp, p = p, pp+p g.next() Which gives us the results: The yield statement is used in conjuction with Python generators. It saves the state of the function and returns the yeilded value.

   Understanding generators in Python - Stack Overflow

   stackoverflow.com/questions/1756096/understanding-generators-in-python

   See all results for this question

   How to plot a function in Python using matplotlib?

   • In order to plot a function in Python using Matplotlib, we need to define a range of x and y values that correspond to that function. In order to do this, we need to: Let’s see how we can accomplish this. First, we’ll need to import our libraries: import numpy as np

   How to Plot a Function in Python with Matplotlib • datagy

   datagy.io/python-matplotlib-plot-function/

   See all results for this question

   What is an execution call graph in Python?

   • An execution call graph generated for a simple computer program in Python. Tools and litterature are abundant on the topic This document details some pratical applications of callgraphs in Python from the point of view of an end-user. We oppose here two approches:

   Generating and using a Callgraph, in Python · The COOP Blog

   cerfacs.fr/coop/pycallgraph

   See all results for this question

10. realpython.com · python-matplotlib-guidePython Plotting With Matplotlib (Guide) – Real Python

    realpython.com · python-matplotlib-guide

    

    Using one-liners to generate basic plots in matplotlib is fairly simple, but skillfully commanding the remaining 98% of the library can be daunting. This article is a beginner-to-intermediate-level walkthrough on matplotlib that mixes theory with examples.