Answers for "import python file"

python move file

# To move a file in Python, use one of the following:
import os
import shutil

os.rename("path/to/current/file.foo", "path/to/new/destination/for/file.foo")
shutil.move("path/to/current/file.foo", "path/to/new/destination/for/file.foo")
os.replace("path/to/current/file.foo", "path/to/new/destination/for/file.foo")

# In the first two cases the directory in which the new file
# is being created must already exist.

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()

import different module based on python version

try:
    import simplejson as json
except ImportError:
    import json

python include another python file

#import all from myfile.py (in same directory)
from myfile import *

python3 import all files in directory

from inspect import isclass
from pkgutil import iter_modules
from pathlib import Path
from importlib import import_module

# iterate through the modules in the current package
package_dir = Path(__file__).resolve().parent
for (_, module_name, _) in iter_modules([package_dir]):

    # import the module and iterate through its attributes
    module = import_module(f"{__name__}.{module_name}")
    for attribute_name in dir(module):
        attribute = getattr(module, attribute_name)

        if isclass(attribute):            
            # Add the class to this package's variables
            globals()[attribute_name] = attribute

python import file

from scripts import *