The content between the ‘’’ is known as ‘docstring’, which are displayed by the ‘help’ function as shown below. Press ‘q’ to exit from help-screen.
>>> def add2Num(x, y): ... ''' add two numbers : x, y ''' ... print(x+y) ... >>> add2Num(2, 3) 5 >>> help(add2Num) Help on function add2Num in module __main__: add2Num(x, y) add two numbers : x, y
6.2. types of docstring¶
There are two standard format of creating the docstrings, i.e. Numpy style and Goole style, which are supported by Sphinx-documentation for generating the auto-documentation of the project.
6.3. Convert previous code into function¶
Now, we will convert the code in Listing 5.1 into function. Conversion process is quite simple, as shown in Listing 6.1, where function with docstring is defined at Lines 5-6. Ther previous code is indented and finally a return statement is added in Line 20. Lines 22-24 calls the function and print the output. Lastly, Lines 28-29 are the standard boilerplate to set the function ‘main’ as the entry point.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
# price.py import csv def ring_cost(filename): ''' calculate the total cost ''' total_price = 0 # for all items in the list with open(filename, 'r') as f: # open file in read mode rows = csv.reader(f) header = next(rows) # skip line 1 i.e. header for row in rows: row = float(row) # price row = int(row) # quantity total_price += row * row # print("Total price = %10.2f" % total_price) return total_price # return total_price def main(): total = ring_cost('price.csv') # function call print("Total price = %10.2f" % total) # print value # standard boilerplate # main is the starting function if __name__ == '__main__': main()
$ python price.py Total price = 1328.38
$ python -i price.py Total price = 1328.38 >>> >>> ring_cost('price.csv') 1328.3799999999999 >>> ring_cost('price2.csv') 1328.3799999999999 >>>
In the above command, ‘python -i price.py’, the main() function is called. And after entering the Python shell, we can call the function directly i.e. ring_cost(‘price.csv’), and the corresponding ‘return value’, i.e. 1328.3799999999999, will be printed in the shell.
6.4. glob module¶
‘glob’ module can be used to select the files for further processing, as shown in this section. To understand it, first create some files as below,
$ touch data1.txt data2.txt data3.txt data_1.txt data_2.txt data_3.txt data1.csv data2.csv data3.csv
Next, open the Python shell and see the following function of ‘glob’ module,
>>> glob.glob('*.csv') # find all csv files ['data3.csv', 'data2.csv', 'data1.csv'] >>> glob.glob('data*.txt') # select all txt file which starts with 'data' ['data_3.txt', 'data_2.txt', 'data2.txt', 'data_1.txt', 'data3.txt', 'data1.txt'] >>> # select txt files which have one character between 'data' and '.txt' >>> glob.glob('data?.txt') ['data2.txt', 'data3.txt', 'data1.txt'] >>> glob.glob('data[0-2]*.csv') # select csv file with numbers 0,1,2 after 'data' ['data2.csv', 'data1.csv']
- The ‘glob’ module returns the ‘list’.
- The list is in unordered form.
6.4.1. Price calculation on files using ‘glob’¶
Now, we will use the glob module to perform ‘price calculation’ on files using ‘glob’ module. First open the Python shell without using ‘-i’ operation.
Since we did not use the ‘-i’ operation to open the shell, therefore we need to import the function ‘ring_cost’ in the shell, as shown below,
>>> import glob >>> from price import ring_cost >>> >>> files = glob.glob('pri*.csv') >>> for file in files: ... print(file, ring_cost(file)) ... price.csv 1328.3799999999999 price2.csv 1328.3799999999999
Note that we need to restart python shell every time, we made some changes in the code. This is required as the ‘import’ statement loads all the data at the first time; and when we re-import the modules then it is fetched from the cache.
Note that, the ‘glob’ returns a list, therefore we can extend the list using various listing operation. This can be useful when we have files names with different names, but required same operations e.g. we want to perform price calculation on another set of items which has same columns as price.csv file. List can be modified as below,
>>> files = glob.glob('pri*.csv') >>> files2 = glob.glob('pri*.csv') >>> files.extend(files2) # extend list >>> files ['price.csv', 'price2.csv', 'price.csv', 'price2.csv'] >>> files.append('price2.csv') # append data >>> files ['price.csv', 'price2.csv', 'price.csv', 'price2.csv', 'price2.csv']