python file reading

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()

1with open(filename,"w") as f:
2  f.write('Hello World')

1with open('filename', 'a') as f: # able to append data to file
2	f.write(var1) # Were var1 is some variable you have set previously
3	f.write('data') 
4	f.close() # You can add this but it is not mandatory 
5
6with open('filename', 'r') as f: # able to read data from file ( also is the default mode when opening a file in python)
7
8with open('filename', 'x') as f: # Creates new file, if it already exists it will cause it to fail
9
10with open('filename', 't') as f: # opens the file in text mode (also is defualt)
11
12with open('filename', 'b') as f: # Use if your file will contain binary data
13  
14with open('filename', 'w') as f: # Open file with ability to write, will also create the file if it does not exist (if it exists will cause it to fail)
15  
16with open('filename', '+') as f: # Opens file with reading and writing
17
18# You can combine these as you like with the + for reading and writing

1fin = open("NAME.txt", 'r')
2body = fin.read().split("\n")
3line = fin.readline().strip()