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0 likes • Nov 19, 2022
Python
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screencap.py

asnark
0 likes • Jan 23, 2021
Python
"""
Take screenshots at x interval - make a movie of doings on a computer.
"""
import time
from datetime import datetime
import ffmpeg
import pyautogui
while True:
epoch_time = int(time.time())
today = datetime.now().strftime("%Y_%m_%d")
filename = str(epoch_time) + ".png"
print("taking screenshot: {0}".format(filename))
myScreenshot = pyautogui.screenshot()
myScreenshot.save(today + "/" + filename)
time.sleep(5)
#
# and then tie it together with: https://github.com/kkroening/ffmpeg-python/blob/master/examples/README.md#assemble-video-from-sequence-of-frames
#
"""
import ffmpeg
(
ffmpeg
.input('./2021_01_22/*.png', pattern_type='glob', framerate=25)
.filter('deflicker', mode='pm', size=10)
.filter('scale', size='hd1080', force_original_aspect_ratio='increase')
.output('movie.mp4', crf=20, preset='slower', movflags='faststart', pix_fmt='yuv420p')
.run()
)
"""

Topological sort

CodeCatch
0 likes • Nov 19, 2022
Python
#Python program to print topological sorting of a DAG
from collections import defaultdict
#Class to represent a graph
class Graph:
def __init__(self,vertices):
self.graph = defaultdict(list) #dictionary containing adjacency List
self.V = vertices #No. of vertices
# function to add an edge to graph
def addEdge(self,u,v):
self.graph[u].append(v)
# A recursive function used by topologicalSort
def topologicalSortUtil(self,v,visited,stack):
# Mark the current node as visited.
visited[v] = True
# Recur for all the vertices adjacent to this vertex
for i in self.graph[v]:
if visited[i] == False:
self.topologicalSortUtil(i,visited,stack)
# Push current vertex to stack which stores result
stack.insert(0,v)
# The function to do Topological Sort. It uses recursive
# topologicalSortUtil()
def topologicalSort(self):
# Mark all the vertices as not visited
visited = [False]*self.V
stack =[]
# Call the recursive helper function to store Topological
# Sort starting from all vertices one by one
for i in range(self.V):
if visited[i] == False:
self.topologicalSortUtil(i,visited,stack)
# Print contents of stack
print(stack)
g= Graph(6)
g.addEdge(5, 2);
g.addEdge(5, 0);
g.addEdge(4, 0);
g.addEdge(4, 1);
g.addEdge(2, 3);
g.addEdge(3, 1);
print("Following is a Topological Sort of the given graph")
g.topologicalSort()

Hello, python

Ntindle
0 likes • Jan 20, 2021
Python
print(“Hello World”)

UNT CSCE 2100 Assignment 6

AustinLeath
0 likes • Nov 18, 2022
Python
"""
Assignment 6
The goal is to make a graph of
who bit who and who was bitten.
There should be 10 nodes and 15 edges.
3 arrows of biting each other and
3 arrows of someone biting themselves.
Networkx can not do self biting
arrows, but it is in the code.
"""
from graphviz import Digraph as DDotGraph
from graphviz import Graph as UDotGraph
import networkx as nx
from networkx.algorithms.dag import transitive_closure
import graphviz as gv
import matplotlib.pyplot as plt
import numpy as np
from numpy.linalg import matrix_power
"""
class DGraph:
def __init__(self):
self.d = dict()
def clear(self):
self.d = dict()
def add_node(self,n):
if not self.d.get(n):
self.d[n] = set()
def add_edge(self,e):
f,t=e
self.add_node(f)
self.add_node(t)
vs=self.d.get(f)
if not vs:
self.d[f] = {t}
else:
vs.add(t)
def add_edges_from(self,es):
for e in es:
self.add_edge(e)
def edges(self):
for f in self.d:
for t in self.d[f]:
yield (f,t)
def number_of_nodes(self):
return len(self.d)
def __repr__(self):
return self.d.__repr__()
def show(self):
dot = gv.Digraph()
for e in self.edges():
#print(e)
f, t = e
dot.edge(str(f), str(t), label='')
#print(dot.source)
show(dot)
# displays graph with graphviz
def show(dot, show=True, file_name='graph.gv'):
dot.render(file_name, view=show)
def showGraph(g,label="",directed=True):
if directed:
dot = gv.Digraph()
else:
dot = gv.Graph()
for e in g.edges():
print(e)
f, t = e
dot.edge(str(f), str(t), label=label)
print(dot.source)
show(dot)
def bit():
G = DGraph()
G.add_edge(("Blade","Samara"))
G.add_edge(("Shadow","Wolfe"))
G.add_edge(("Raven", "Austin"))
G.add_edge(("Blade", "Alice"))
G.add_edge(("Alice","Brandon"))
G.add_edge(("Blade", "Wolfe"))
G.add_edge(("Samara", "Robin"))
G.add_edge(("Samara", "Raven"))
G.add_edge(("Samara", "Hamed"))
G.add_edge(("Wolfe", "Blade"))
G.add_edge(("Hamed", "Samara"))
G.add_edge(("Wolfe", "Shadow"))
G.add_edge(("Brandon", "Brandon"))
G.add_edge(("Hamed", "Hamed"))
G.add_edge(("Austin", "Austin"))
showGraph(G, label="bit")
bit()
def bitten():
G=DGraph()
G.add_edge(("Samara","Blade"))
G.add_edge(("Wolfe","Shadow"))
G.add_edge(("Austin", "Raven"))
G.add_edge(("Alice","Blade"))
G.add_edge(("Brandon", "Alice"))
G.add_edge(("Wolfe", "Blade" ))
G.add_edge(("Robin", "Samara"))
G.add_edge(("Raven", "Samara"))
G.add_edge(("Hamed", "Samara"))
G.add_edge(("Blade", "Wolfe"))
G.add_edge(("Samara", "Hamed"))
G.add_edge(("Shadow", "Wolfe"))
G.add_edge(("Brandon", "Brandon"))
G.add_edge(("Hamed", "Hamed"))
G.add_edge(("Austin", "Austin"))
showGraph(G, label="bitten by")
#bitten()
family = ["Blade", "Samara", "Shadow", "Wolfe", "Raven", "Alice"]
"""
#Do transitive closure call out and the
#matrix power operation should be the same
D = nx.DiGraph()
#D.add_nodes_from("SamaraBladeWolfeShadowAliceRavenBrandonRobinHamedAustin")
D.add_edge("Blade","Samara")
D.add_edge("Shadow","Wolfe")
D.add_edge("Raven", "Austin")
D.add_edge("Blade", "Alice")
D.add_edge("Alice","Brandon")
D.add_edge("Blade", "Wolfe")
D.add_edge("Samara", "Robin")
D.add_edge("Samara", "Raven")
D.add_edge("Samara", "Hamed")
D.add_edge("Wolfe", "Blade")
D.add_edge("Hamed", "Samara")
D.add_edge("Wolfe", "Shadow")
D.add_edge("Brandon", "Brandon")
D.add_edge("Hamed", "Hamed")
D.add_edge("Austin", "Austin")
T = transitive_closure(D)
for e in D.edges(): print(e)
for n in D.nodes(): print(n)
def show(H):
nx.draw(H, with_labels=True, font_weight='bold')
plt.show()
#Use nx.to_numpy_matrix instead of nx.adjacency_matrix
# M = nx.adjacency_matrix(D)
# MT = nx.adjacency_matrix(T)
M = nx.to_numpy_matrix(D)
MT = nx.to_numpy_matrix(T)
def mPower(M, k): #M is numpy matrix
assert k >= 1
P = M
for _ in range(k):
P = P @ M
return P
def tc(M):
#compute transitive closure
pass
D1 = nx.DiGraph(M)
D2 = nx.DiGraph(M2)
print('Matrix for Original\n', M)
N = nx.to_numpy_array(D,dtype=int)
print('np_array for Original\n', N)
print('\nMatrix for Transitive Closure\n', MT)
N2 = nx.to_numpy_array(T,dtype=int)
print('np_array for Transitive Closure\n', N2)
show(D) #can use D, T, and numpy matrix power operation
show(T)
show(T)

Reverse a linked list

CodeCatch
0 likes • Nov 19, 2022
Python
# Python program to reverse a linked list
# Time Complexity : O(n)
# Space Complexity : O(n) as 'next'
#variable is getting created in each loop.
# Node class
class Node:
# Constructor to initialize the node object
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
# Function to initialize head
def __init__(self):
self.head = None
# Function to reverse the linked list
def reverse(self):
prev = None
current = self.head
while(current is not None):
next = current.next
current.next = prev
prev = current
current = next
self.head = prev
# Function to insert a new node at the beginning
def push(self, new_data):
new_node = Node(new_data)
new_node.next = self.head
self.head = new_node
# Utility function to print the linked LinkedList
def printList(self):
temp = self.head
while(temp):
print temp.data,
temp = temp.next
# Driver program to test above functions
llist = LinkedList()
llist.push(20)
llist.push(4)
llist.push(15)
llist.push(85)
print "Given Linked List"
llist.printList()
llist.reverse()
print "\nReversed Linked List"
llist.printList()
import mysql.connector
mydb = mysql.connector.connect(
host="localhost",
user="yourusername",
password="yourpassword"
)
mycursor = mydb.cursor()
mycursor.execute("CREATE DATABASE mydatabase")