turtle은 간단한 움직임을 반복하는 프로그램을 사용하여 복잡한 모양을 그릴 수 있습니다.
In Python, turtle graphics provides a representation of a physical “turtle” (a little robot with a pen) that draws on a sheet of paper on the floor.
It’s an effective and well-proven way for learners to encounter programming concepts and interaction with software, as it provides instant, visible feedback. It also provides convenient access to graphical output in general.
Turtle drawing was originally created as an educational tool, to be used by teachers in the classroom. For the programmer who needs to produce some graphical output it can be a way to do that without the overhead of introducing more complex or external libraries into their work.
Tutorial
New users should start here. In this tutorial we’ll explore some of the basics of turtle drawing.
Starting a turtle environment
In a Python shell, import all the objects of theturtlemodule:
from turtle import *
If you run into aNomodulenamed'_tkinter'error, you’ll have to install theTkinterfacepackageon your system.
Basic drawing
Send the turtle forward 100 steps:
forward(100)
You should see (most likely, in a new window on your display) a line drawn by the turtle, heading East. Change the direction of the turtle, so that it turns 120 degrees left (anti-clockwise):
left(120)
Let’s continue by drawing a triangle:
forward(100)
left(120)
forward(100)
Notice how the turtle, represented by an arrow, points in different directions as you steer it.
Experiment with those commands, and also withbackward()andright().
펜 제어
Try changing the color - for example,color('blue')- and width of the line - for example,width(3)- and then drawing again.
You can also move the turtle around without drawing, by lifting up the pen:up()before moving. To start drawing again, usedown().
The turtle’s position
Send your turtle back to its starting-point (useful if it has disappeared off-screen):
home()
The home position is at the center of the turtle’s screen. If you ever need to know them, get the turtle’s x-y co-ordinates with:
pos()
Home is at(0,0).
And after a while, it will probably help to clear the window so we can start anew:
clearscreen()
Making algorithmic patterns
Using loops, it’s possible to build up geometric patterns:
for steps in range(100):
for c in ('blue', 'red', 'green'):
color(c)
forward(steps)
right(30)
- which of course, are limited only by the imagination!
Let’s draw the star shape at the top of this page. We want red lines, filled in with yellow:
color('red')
fillcolor('yellow')
Just asup()anddown()determine whether lines will be drawn, filling can be turned on and off:
begin_fill()
Next we’ll create a loop:
while True:
forward(200)
left(170)
if abs(pos()) < 1:
break
abs(pos())<1is a good way to know when the turtle is back at its home position.
Finally, complete the filling:
end_fill()
(Note that filling only actually takes place when you give theend_fill()command.)
How to…
This section covers some typical turtle use-cases and approaches.
Get started as quickly as possible
One of the joys of turtle graphics is the immediate, visual feedback that’s available from simple commands - it’s an excellent way to introduce children to programming ideas, with a minimum of overhead (not just children, of course).
The turtle module makes this possible by exposing all its basic functionality as functions, available withfromturtleimport*. Theturtle graphics tutorialcovers this approach.
It’s worth noting that many of the turtle commands also have even more terse equivalents, such asfd()forforward(). These are especially useful when working with learners for whom typing is not a skill.
You’ll need to have theTkinterfacepackageinstalled on your system for turtle graphics to work. Be warned that this is not always straightforward, so check this in advance if you’re planning to use turtle graphics with a learner.
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Tabular data with heterogeneously-types columns.
Ordered and unordered time series data.
Arbitrary matrix data with row and column labels.
Any other form of observational / statistical data sets.
The data actually need not be labeled at all to be placed into a pandas data structure.
2. NumPy Numpy is the core library for scientific computing in Python. It provides a high-performance multidimensional array object, and tools for working with these arrays.
3. Matplotlib
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Bar graph
Histograms
Scatter Plot
Pie Plot
Hexagonal Bin Plot
Area Plot
4. Selenium
The selenium package is used to automate web browser interaction from Python.
5. OpenCV
OpenCV- Python is a library of Python designed to solve computer vision problems.
6. SciPy
Scipy is a free and open-source Python library used for scientific computing and technical computing.
7. Scikit-Learn
Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms.
8. PySpark
The Spark Python API (PySpark) exposes the Spark programming model to Python.
9. Django
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Django is a high-level and has a MVC-MVT styled architecture.
Django web framework is written on quick and powerful Python language.
Django has a open-source collection of libraries for building a fully functioning web application.
10. Tensor Flow
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Astackis a linear data structure that stores items in aLast-In/First-Out (LIFO)or First-In/Last-Out (FILO) manner. In stack, a new element is added at one end and an element is removed from that end only. The insert and delete operations are often called push and pop.
The functions associated with stack are:
empty()– Returns whether the stack is empty – Time Complexity: O(1)
size()– Returns the size of the stack – Time Complexity: O(1)
top() / peek()– Returns a reference to the topmost element of the stack – Time Complexity: O(1)
push(a)– Inserts the element ‘a’ at the top of the stack – Time Complexity: O(1)
pop()– Deletes the topmost element of the stack – Time Complexity: O(1)
Implementation:
There are various ways from which a stack can be implemented in Python. This article covers the implementation of a stack using data structures and modules from the Python library. Stack in Python can be implemented using the following ways:
list
Collections.deque
queue.LifoQueue
# Python program to
# demonstrate stack implementation
# using list
stack = []
# append() function to push
# element in the stack
stack.append('a')
stack.append('b')
stack.append('c')
print('Initial stack')
print(stack)
# pop() function to pop
# element from stack in
# LIFO order
print('\nElements popped from stack:')
print(stack.pop())
print(stack.pop())
print(stack.pop())
print('\nStack after elements are popped:')
print(stack)
# uncommenting print(stack.pop())
# will cause an IndexError
# as the stack is now empty
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