python read file
with open("file.txt", "r") as txt_file:
return txt_file.readlines()python read file
with open("file.txt", "r") as txt_file:
return txt_file.readlines()python read file
# Basic syntax:
with open('/path/to/filename.extension', 'open_mode') as filename:
file_data = filename.readlines() # Or filename.read()
# Where:
# - open imports the file as a file object which then needs to be read
# with one of the read options
# - readlines() imports each line of the file as an element in a list
# - read() imports the file contents as one long new-line-separated
# string
# - open_mode can be one of:
# - "r" = Read which opens a file for reading (error if the file
# doesn't exist)
# - "a" = Append which opens a file for appending (creates the
# file if it doesn't exist)
# - "w" = Write which opens a file for writing (creates the file
# if it doesn't exist)
# - "x" = Create which creates the specified file (returns an error
# if the file exists)
# Note, "with open() as" is recommended because the file is closed
# automatically so you don't have to remember to use file.close()
# Basic syntax for a delimited file with multiple fields:
import csv
with open('/path/to/filename.extension', 'open_mode') as filename:
file_data = csv.reader(filename, delimiter='delimiter')
data_as_list = list(file_data)
# Where:
# - csv.reader can be used for files that use any delimiter, not just
# commas, e.g.: 't', '|', ';', etc. (It's a bit of a misnomer)
# - csv.reader() returns a csv.reader object which can be iterated
# over, directly converted to a list, and etc.
# Importing data using Numpy:
import numpy as np
data = np.loadtxt('/path/to/filename.extension',
delimiter=',', # String used to separate values
skiprows=2, # Number of rows to skip
usecols=[0,2], # Specify which columns to read
dtype=str) # The type of the resulting array
# Importing data using Pandas:
import pandas as pd
data = pd.read_csv('/path/to/filename.extension',
nrows=5, # Number of rows of file to read
header=None, # Row number to use as column names
sep='t', # Delimiter to use
comment='#', # Character to split comments
na_values=[""]) # String to recognize as NA/NaN
# Note, pandas can also import excel files with pd.read_excel()how to read files in python
#Read files with loop
#Replace (File path) with your text file's path
file = open("(File path)", "r")
text = ""
for line in file:
text = "%sn%s"%(text, line)
print(text)python read file
txt = open('FILENAME.txt')
txtread = txt.read()
print(txtread)
print(txt.read())python open and read file with
with open('pagehead.section.htm','r') as f:
output = f.read()how to open a file in python
open("filename" , "mode")
# do whatever you want to do!!Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
