python read file

1file = open("text.txt", "w") 
2file.write("Your text goes here") 
3file.close() 
4'r' open for reading (default)
5'w' open for writing, truncating the file first
6'x' open for exclusive creation, failing if the file already exists
7'a' open for writing, appending to the end of the file if it exists

1file = open(“testfile.txt”,”w”) 
2 
3file.write(“Hello World”) 
4file.write(“This is our new text file”) 
5file.write(“and this is another line.”) 
6file.write(“Why? Because we can.”) 
7 
8file.close() 

1with open("file.txt", "r") as txt_file:
2  return txt_file.readlines()

1# Basic syntax:
2with open('/path/to/filename.extension', 'open_mode') as filename:
3  file_data = filename.readlines()	# Or filename.read() 
4# Where:
5#	- open imports the file as a file object which then needs to be read
6#		with one of the read options
7#	- readlines() imports each line of the file as an element in a list
8#	- read() imports the file contents as one long new-line-separated 
9#		string
10#	- open_mode can be one of:
11#		- "r" = Read which opens a file for reading (error if the file 
12#			doesn't exist)
13#		- "a" = Append which opens a file for appending (creates the 
14#			file if it doesn't exist)
15#		- "w" = Write which opens a file for writing (creates the file 
16#			if it doesn't exist)
17#		- "x" = Create which creates the specified file (returns an error
18#			if the file exists)
19# Note, "with open() as" is recommended because the file is closed 
20#	automatically so you don't have to remember to use file.close()
21
22# Basic syntax for a delimited file with multiple fields:
23import csv
24with open('/path/to/filename.extension', 'open_mode') as filename:
25	file_data = csv.reader(filename, delimiter='delimiter')
26    data_as_list = list(file_data)
27# Where:
28#	- csv.reader can be used for files that use any delimiter, not just
29#		commas, e.g.: '\t', '|', ';', etc. (It's a bit of a misnomer)
30#	- csv.reader() returns a csv.reader object which can be iterated 
31#		over, directly converted to a list, and etc. 
32
33# Importing data using Numpy:
34import numpy as np
35data = np.loadtxt('/path/to/filename.extension',
36				delimiter=',', 	# String used to separate values
37				skiprows=2, 	# Number of rows to skip
38				usecols=[0,2], 	# Specify which columns to read
39				dtype=str) 		# The type of the resulting array
40
41# Importing data using Pandas:
42import pandas as pd
43data = pd.read_csv('/path/to/filename.extension',
44				nrows=5, 		# Number of rows of file to read
45				header=None, 	# Row number to use as column names 
46	            sep='\t', 		# Delimiter to use 
47	            comment='#', 	# Character to split comments
48				na_values=[""])	# String to recognize as NA/NaN
49
50# Note, pandas can also import excel files with pd.read_excel()

1f=open("Diabetes.txt",'r')
2f.read()

1txt = open('FILENAME.txt')
2txtread = txt.read()
3print(txtread)
4print(txt.read())