Author SHA1 Message Date
shunan.z 74545a6ad1 Merge branch 'main' of https://gogs.gtsplab.com:5432/SVIG/python-bootcamp 2023-05-26 09:39:45 -05:00
shunan.z b6be9c9488 Shunan_z_HW2 2023-05-26 09:39:40 -05:00
scott.liu 716e254905 This is my hw2 2023-05-26 03:28:24 -07:00
leonhuang 161a4e28db Homework1 2023-05-25 14:28:54 -05:00
leonhuang 5af112ebae Leon's Submussions 2023-05-25 14:03:09 -05:00
shunan.z 5d36a06987 HW1_shunan_zhao 2023-05-25 11:46:29 -05:00
shunan.z b4f174be47 HW1_shunan_zhao 2023-05-25 11:14:38 -05:00
scott.liu 46acaf2e75 Scott;s Folder 2023-05-25 03:49:05 -07:00
scott.liu 28c277f369 something casual 2023-05-24 17:30:29 -07:00
shunan.z 02146e348d delete 2023-05-18 20:33:21 -05:00
shunan.z 9df129681d delete 2023-05-18 20:29:32 -05:00
shunan.z a566adc1df 新的 2023-05-18 20:28:30 -05:00
shunan.z aa1a8fee93 aaaaaaaaaaaaaaaaaaaaaaaaaa 2023-05-18 20:25:54 -05:00
shunan.z 285914f044 Merge branch 'main' of https://gogs.gtsplab.com:5432/SVIG/python-bootcamp 2023-05-18 19:34:44 -05:00
leonhuang da2c779bcd adfafafafsafafasfasfasfafafafsagagafafaagagagagagag 2023-05-18 19:27:06 -05:00
leonhuang 7259509d9e adadjalkfjlaskfjlaksfjlaskfjlkasfjlakfjakfjlasfjlgjslga 2023-05-18 19:27:06 -05:00
shunan.z b085e13c4e I like badminton. 2023-05-18 19:18:48 -05:00
scott.liu 59e84426af A brain teaser 2023-05-18 16:59:41 -07:00
scott.liu 97f93ebd8e A brain teaser w/ answer 2023-05-18 16:58:54 -07:00
scott.liu 35c8889e77 A brain teaser 2023-05-18 16:56:56 -07:00
cheezedoodle2 dca7e9d599 foo 2023-05-18 12:47:27 -07:00
cheezedoodle2 ce856e5626 foo 2023-05-18 12:44:01 -07:00
cheezedoodle2 072032e80e foo 2023-05-18 12:39:46 -07:00
cheezedoodle2 235e7b5268 foo 2023-05-18 12:38:03 -07:00
cheezedoodle2 22fa096271 Removed foo 2023-05-18 03:08:11 -07:00
scott.liu 13eb12bf69 An update on the test file 2023-05-18 02:49:43 -07:00
scott.liu efa189d0b6 Commit 2 2023-05-18 02:33:11 -07:00
scott.liu 111f551a39 This is a test commit 2023-05-18 02:33:11 -07:00
cheezedoodle2 e0fd81dc1d foo 2023-05-18 02:21:48 -07:00
cheezedoodle2 420194ef54 Removed test file 2023-05-17 17:31:15 -07:00
cheezedoodle2 632448c249 added test file 2023-05-17 17:30:22 -07:00
Sloetjes c3405d56e5 Homework for web server 2023-04-19 20:45:08 -04:00
cheezedoodle2 338824c028 Added loader column 2023-04-19 02:46:02 -07:00
cheezedoodle2 6625a4d6c1 Working version of module inspector. 2023-04-19 02:12:26 -07:00
cheezedoodle2 b1fccaf628 Added HTTP performance test 2023-04-12 21:39:39 -07:00
j 568e890c9f Update 'README.md' 2023-04-07 04:58:16 +02:00
cheezedoodle2 ff86e4a7c2 Added the ability for verbs to be a dict, for future use by an AI. 2023-04-03 23:49:36 -07:00
cheezedoodle2 0f10f22345 Added simulation files. 2023-04-03 23:19:16 -07:00
144 changed files with 787 additions and 1 deletions
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{
"configurations": [
{
"name": "Python: HotdogSimulation",
"type": "python",
"request": "launch",
"program": "simulation/SimulationRunner.py",
"justMyCode": true,
"args": "./HotdogSimulation.py"
}
]
}
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# Question 1:
# The international standard for floating-point representation is
# called the "IEEE 754 Standard for Floating-Point Arithmetic."
# Question 2:
# 32-bit and 64-bit formats are the most widely used ones in practice.
# Question 3:
# My computer supports all these formats
import numpy as np
supported_formats = np.finfo(np.float32).bits, np.finfo(np.float64).bits
print(f"Your computer supports the following floating-point formats: {supported_formats}")
# Question 4:
# Using the Pandas multiplication operator (df['Number1'] * df['Number2'])
# , the result is automatically converted to a floating-point data type.
# On the other hand, when I multiply the numbers using the normal Python
# multiplication operator (num1 * num2), the result remains an integer
# data type.
# Question 5:
# The size of a floating-point number in memory is primarily determined
# by the data type and not the actual value it represents. So the size
# of a Python floating-point number does not change as it gets larger.
import sys
print(sys.getsizeof(70))
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print('Hi')
+1 -1
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GTSP Python Bootcamp
This bootcamp is intended for OTP interns with a math and applied analysis
This bootcamp is intended for OPT interns with a math and applied analysis
background to get up to speed quickly on how to use Python for practical
commercial work. It is not intended for large classes above 2-3 study groups
of a maximum of 4 students each.
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# A quick brain teaser
print('What has a head and a tail but no body?')
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# A coin
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import sys
print(sys.float_info)
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{\rtf1\ansi\ansicpg1252\cocoartf2580
\cocoatextscaling0\cocoaplatform0{\fonttbl\f0\fnil\fcharset0 HelveticaNeue;\f1\fnil\fcharset0 Menlo-Regular;}
{\colortbl;\red255\green255\blue255;\red0\green0\blue0;\red0\green0\blue0;}
{\*\expandedcolortbl;;\cssrgb\c0\c0\c0\c87059;\cssrgb\c0\c0\c0\c3922;}
\margl1440\margr1440\vieww11520\viewh8400\viewkind0
\deftab720
\pard\pardeftab720\partightenfactor0
\f0\fs32 \cf2 \expnd0\expndtw0\kerning0
1. What is the name of the international standard for floating-point representation?\
\
The IEEE-754 standard describes floating-point formats, a way to represent real numbers in hardware.\
\
\
2. How many bits are the floating point numbers defined by that standard allowed to be?\
\
The floating-point numbers defined by the international standard can be allowed to be of different lengths depending on the specific interchange format. For binary interchange, the formats can be 16 bits, 32 bits, 64 bits, and any multiple of 32 bits \uc0\u8805 128. For decimal interchange, the formats can be any multiple of 32 bits.\
\
\
3. Does your computer support all those formats? Can you think of an easy way to check with only one line of Python?\
\
import sys\
print(sys.float_info)\
\
scott@MacBook-Pro-6 python-bootcamp % python3 Floating_Point_Formats.py \
sys.float_info(max=1.7976931348623157e+308, max_exp=1024, max_10_exp=308, min=2.2250738585072014e-308, min_exp=-1021, min_10_exp=-307, dig=15, mant_dig=53, epsilon=2.220446049250313e-16, radix=2, rounds=1)\
\
\
\pard\pardeftab720\sa320\partightenfactor0
\cf2 4. Why doesn't this code give the same answers to the two multiplications?\
Because they are different operations. The normal Python multiplication operator will multiply two numbers together and return the product. The Pandas multiplication operator, on the other hand, performs element-wise multiplication on the corresponding columns in a DataFrame. In other words, it multiplies the first element in the first column with the first element in the second column, the second element in the first column with the second element in the second column, and so on. \
Floating-point arithmetic has a limited precision due to the finite number of bits used to represent floating-point numbers in binary format. This can lead to rounding errors and loss of precision in arithmetic operations, particularly with very large or very small numbers.\
\
5. You can use
\f1\fs27\fsmilli13600 \cf2 \cb3 sys.getsizeof
\f0\fs32 \cf2 \cb1 to see how large a Python object is. Does the size of a Python floating-point number change as it gets larger? Why or why not?\
The size of a Python floating-point number does not change as it gets larger. This is because Python uses a fixed number of bytes to represent floating-point numbers, regardless of their value.}
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# Name three practical differences between Python strings and bytes.
# Using sys.getsizeof, see how the sizes may be different.
# Do emoji change this answer?
# Encoding
# Strings are created using Unicode character points.
# While bytes are used to represent actual bytes in memory, which can be encoded using ASCII or UTF-8.
# Usage
# Strings are usually used to represent text.
# While bytes are used to represent binary data.
# Memory Size
# Strings take up more memory than bytes, because they are Unicode-based and can contain any character.
# While bytes are limited to binary data.
print("---------------------------------------------")
print("This is the Memory Size test print out:")
import sys
my_string = "Hello, world!"
my_bytes = b'\x48\x65\x6c\x6c'
print(sys.getsizeof(my_string)) # Prints 62
print(sys.getsizeof(my_bytes)) # Prints 37
print()
print('Test the emoji:')
x = 'pizza' # Prints 54
y = b'pizza' # Prints 38
z = '🍕' #Prints 80
print(sys.getsizeof(x))
print(sys.getsizeof(y))
print(sys.getsizeof(z))
print("---------------------------------------------")
print("This is the String to Sequence of Numbers print out:")
def String_to_SequenceofNumbers():
my_string = input("Enter a string: ")
num_sequence = [ord(c) for c in my_string]
print(num_sequence)
if __name__ == "__main__":
String_to_SequenceofNumbers()
print("---------------------------------------------")
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import pandas as pd
import numpy as np
# Generate two random 64-bit integers
num1 = np.random.randint(0, 10 - 1)
num2 = np.random.randint(0, 10 - 1)
# Multiply them together using the normal Python multiplication operator
print(f"num1 * num2 = {num1 * num2}")
# Create a Pandas DataFrame with the generated numbers
data = {'Number1': [num1], 'Number2': [num2]}
df = pd.DataFrame(data)
# Multiply the numbers together using the Pandas multiplication operator
df['Product'] = df['Number1'] * df['Number2']
print(df)
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import sys
num = 99999999999
size = sys.getsizeof(num)
print(f"The size of the float is {size} bytes.")
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import time
i=0
while True:
print(f"\015{i=}", end='')
i += 1
time.sleep(0.2)
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char1 = "u"
result1 = ord(char1)
print("ASCII value of the character {} is {}.".format(char1, result1))
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "0593e529",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"from urllib.parse import urlparse\n",
"\n",
"class JPEGRequestHandler:\n",
" def __init__(self, app):\n",
" self.app = app\n",
"\n",
" def __call__(self, environ, start_response):\n",
" url = urlparse(environ['REQUEST_URI'])\n",
" path = url.path\n",
"\n",
" if path.endswith('.jpg'):\n",
" file_path = path[1:]\n",
"\n",
" if os.path.isfile(file_path):\n",
" with open(file_path, 'rb') as file:\n",
" response_body = file.read()\n",
" status = '200 OK'\n",
" headers = [('Content-type', 'image/jpeg'),\n",
" ('Content-Length', str(len(response_body)))]\n",
"\n",
" start_response(status, headers)\n",
" return [response_body]\n",
" else:\n",
" status = '404 Not Found'\n",
" headers = [('Content-type', 'text/plain'),\n",
" ('Content-Length', '0')]\n",
"\n",
" start_response(status, headers)\n",
" return []\n",
" else:\n",
" status = '403 Forbidden'\n",
" headers = [('Content-type', 'text/plain'),\n",
" ('Content-Length', '0')]\n",
"\n",
" start_response(status, headers)\n",
" return []\n",
"\n",
"if __name__ == '__main__':\n",
" from werkzeug.serving import run_simple\n",
" from werkzeug.middleware.dispatcher import DispatcherMiddleware\n",
"\n",
" app = DispatcherMiddleware(JPEGRequestHandler(app), {'/': app})\n",
" run_simple('0.0.0.0', 8000, app, use_reloader=True)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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import os
from urllib.parse import urlparse
class JPEGRequestHandler:
def __init__(self, app):
self.app = app
def __call__(self, environ, start_response):
url = urlparse(environ['REQUEST_URI'])
path = url.path
if path.endswith('.jpg'):
file_path = path[1:]
if os.path.isfile(file_path):
with open(file_path, 'rb') as file:
response_body = file.read()
status = '200 OK'
headers = [('Content-type', 'image/jpeg'),
('Content-Length', str(len(response_body)))]
start_response(status, headers)
return [response_body]
else:
status = '404 Not Found'
headers = [('Content-type', 'text/plain'),
('Content-Length', '0')]
start_response(status, headers)
return []
else:
status = '403 Forbidden'
headers = [('Content-type', 'text/plain'),
('Content-Length', '0')]
start_response(status, headers)
return []
if __name__ == '__main__':
from werkzeug.serving import run_simple
from werkzeug.middleware.dispatcher import DispatcherMiddleware
app = DispatcherMiddleware(JPEGRequestHandler(app), {'/': app})
run_simple('0.0.0.0', 8000, app, use_reloader=True)
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import os
from http.server import SimpleHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse
class JPEGRequestHandler(SimpleHTTPRequestHandler):
def do_GET(self):
url = urlparse(self.path)
path = url.path
if path.endswith('.jpg'):
file_path = path[1:]
if os.path.isfile(file_path):
self.send_response(200)
self.send_header('Content-Type', 'image/jpeg')
self.end_headers()
with open(file_path, 'rb') as file:
self.wfile.write(file.read())
else:
self.send_error(404, 'File not found')
else:
self.send_error(403, 'Only .jpg files are allowed')
def run(server_class=HTTPServer, handler_class=JPEGRequestHandler, port=8000):
server_address = ('', port)
httpd = server_class(server_address, handler_class)
print(f'Serving JPEGs on port {port}...')
httpd.serve_forever()
if __name__ == '__main__':
run()
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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>D3.js Image Loading Time Graph</title>
<script src="https://d3js.org/d3.v5.min.js"></script>
<style>
/* Add some basic styling for the chart */
.bar {
fill: steelblue;
}
.bar:hover {
fill: brown;
}
.axis {
font: 10px sans-serif;
}
.axis path,
.axis line {
fill: none;
stroke: #000;
shape-rendering: crispEdges;
}
</style>
</head>
<body>
<div id="chart"></div>
<div id="stats"></div>
<script>
// Generate the list of image URLs named kublai0.jpg to kublai118.jpg
const numberOfImages = 119;
const imagePrefix = 'http://localhost:8000/kublai';
const imageExtension = '.jpg';
const images = [];
for (let i = 0; i < numberOfImages; i++) {
const imageName = `${imagePrefix}${i}${imageExtension}`;
images.push(imageName);
}
// Disable caching using cache-buster technique
const cacheBuster = (url) => `${url}?${new Date().getTime()}`;
// Load images and measure their loading times
const loadImages = async () => {
const loadingTimes = [];
for (const url of images) {
const startTime = performance.now();
const img = new Image();
img.src = cacheBuster(url);
img.style.display = 'none';
document.body.appendChild(img);
await new Promise((resolve) => {
img.onload = () => {
const endTime = performance.now();
loadingTimes.push(endTime - startTime);
resolve();
};
});
}
return loadingTimes;
};
// Create a D3.js bar chart to visualize loading times
const createChart = (data) => {
const margin = { top: 20, right: 20, bottom: 30, left: 40 },
width = 1280 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;
const x = d3.scaleBand().rangeRound([0, width]).padding(0.1);
const y = d3.scaleLinear().rangeRound([height, 0]);
const svg = d3.select('#chart')
.append('svg')
.attr('width', width + margin.left + margin.right)
.attr('height', height + margin.top + margin.bottom)
.append('g')
.attr('transform', `translate(${margin.left},${margin.top})`);
x.domain(data.map((d, i) => i));
y.domain([0, d3.max(data)]);
svg.append('g')
.attr('class', 'axis axis--x')
.attr('transform', `translate(0,${height})`)
.call(d3.axisBottom(x));
svg.append('g')
.attr('class', 'axis axis--y')
.call(d3.axisLeft(y).ticks(10))
.append('text')
.attr('transform', 'rotate(-90)')
.attr('y', 6)
.attr('dy', '0.71em')
.attr('text-anchor', 'end')
.text('Loading Time (ms)');
svg.selectAll('.bar')
.data(data)
.enter().append('rect')
.attr('class', 'bar')
.attr('x', (d, i) => x(i))
.attr('y', (d) => y(d))
.attr('width', x.bandwidth())
.attr('height', (d) => height - y(d));
const stats = document.getElementById('stats');
let textContent = '';
let average = 0;
let sum = 0;
let min = parseFloat(data[0]);
let max = parseFloat(data[0]);
for(datum of data) {
loadingTime = parseFloat(datum)
sum = sum + loadingTime
if(loadingTime > max) {
max = loadingTime;
}
if(loadingTime < min) {
min = loadingTime;
}
}
average = sum / data.length
textContent =
'Total: ' + sum +
' Average: ' + average +
' Min: ' + min +
' Max: ' + max;
stats.textContent = textContent;
};
// Load images and create the chart
(async () => {
const loadingTimes = await loadImages();
createChart(loadingTimes);
})();
</script>
</body>
</html>
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