- Input function
- Date & Time
- View PC Memory & CPU Usage:
- Read Excel file
- Read CSV file
- Read PDF File with Tables
Input function
print('Enter your name:')
x = input()
print('Hello, ' + x)
>>> print("Rand to Dollar: " + str(float(input("Enter Rand to Dollar: "))*0.068))
Enter Rand to Dollar: 100
Rand to Dollar: 6.800000000000001
>>>
Date & Time
For the date and time we need the following libraries shown in the code below. To access certain values we use list slicing.
>>> from datetime import datetime
>>> from datetime import *
>>>
>>> from time import *
>>>
>>> print(str(datetime.now())[:])
2021-08-01 09:49:34.791152
>>> print(str(datetime.now())[10:19])
09:49:41
View PC Memory & CPU Usage:
Overview
This is a simple program that outputs the PC memory and CPU usage and is useful for system monitoring. We will be using two libraries that is psutil and time.
psutil: Cross-platform lib for process and system monitoring in Python.time: Conversion of given time input into proper format.
Output:
PC Memory & CPU Usage
0: PC Memory: 89.3, CPU Usage: 59.7
1: PC Memory: 89.6, CPU Usage: 56.2
2: PC Memory: 89.7, CPU Usage: 54.7
3: PC Memory: 89.8, CPU Usage: 52.3
4: PC Memory: 89.8, CPU Usage: 60.8
5: PC Memory: 89.8, CPU Usage: 60.9
6: PC Memory: 89.9, CPU Usage: 64.9
7: PC Memory: 89.9, CPU Usage: 58.1
8: PC Memory: 89.9, CPU Usage: 53.1
9: PC Memory: 89.9, CPU Usage: 72.1
[Finished in 12.2s]
Code
The code below shows the output described in the previous section. We are importing psutil and time first. Then we are just printing
out header information in the form of “PC Memory & CPU Usage”. Then we create a for loop that runs 10 times using the range function.
In the for loop we use the psutil libraries and use two of its methods: psutil.virtual_memory() and psutil.cpu_percent(interval=1) to store the instance of those values and then print them out. The method time.sleep(0.1) is just used to add 100ms delay in the for loop.
import psutil
import time
print("PC Memory & CPU Usage\n")
for i in range(10):
mem = psutil.virtual_memory()
usage = psutil.cpu_percent(interval=1)
print(str(i) + ": PC Memory: "+str(mem[2]) + ", CPU Usage: " +str(usage))
time.sleep(0.1)
Read Excel file
country.xlsx
Country,Continent
Afghanistan,Asia
Albania,Europe
Algeria,Africa
Andorra,Europe
Angola,Africa
Argentina,South America
Armenia,Asia
>>> import openpyxl
>>> wb = openpyxl.load_workbook('country.xlsx')
>>> wb.sheetnames # The workbook's sheets' names.
['Sheet1', 'Sheet2', 'Sheet3']
>>> sheet = wb['Sheet1'] # Get a sheet from the workbook.
>>> sheet
<Worksheet "Sheet1">
>>> type(sheet)
<class 'openpyxl.worksheet.worksheet.Worksheet'>
>>> sheet.title # Get the sheet's title as a string.
'Sheet1'
>>> sheet['A1'].value # Get the value from the cell.
Country
>>> sheet.cell(row=1, column=1).value
Country
>>> for i in range(1, 3, 1): # Go through every other row:
... print(i, sheet.cell(row=i, column=1).value)
1 Country
2 Afghanistan
3 Albania
>>> sheet['A1'] = 'South Africa' # Edit the cell's value.
>>> sheet['A1'].value # Get the value from the cell.
South Africa
Read CSV file
country.csv
Country,Continent
Afghanistan,Asia
Albania,Europe
Algeria,Africa
Andorra,Europe
Angola,Africa
Argentina,South America
Armenia,Asia
with open('country.csv') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
p = Country(country=row['Country'], continent=row['Continent'])
p.save()
Read PDF File with Tables
import tabula
file = "data.pdf"
file2 = "data3.pdf"
table1 = tabula.read_pdf(file,pages=1)
table2 = tabula.read_pdf(file,pages=2)
print(table1[0])
print(type(table2[0]))
# Has multiple tables
tables = tabula.read_pdf(file2,pages=1,multiple_tables=True)
print(tables[0])
print(tables[1])