Python

This page contains a brief Python tutorial for students who are not very familiar with the language. We will process files series.csv and episodes.csv introduced in the lecture in SQL.

Several Python scripts

We will illustrate basic features of Python on several scripts working with these CSV files.

• In the first two examples we just use standard Python functions for reading files and split lines into columns by split command.
• This does not work well for episodes.csv file where comma sometimes separates columns and sometimes is in quotes within a column. Therefore we use csv module, which is one the the standard Python modules.
• Alternatively, one could import CSV files via more complex libraries, such as Pandas.
• We will see that similar tasks as these scripts can be done by very short SQL commands. In Pandas we could also achieve similar results using a few commands.

prog1.py

The first script prints the second column (series title) from series.csv

#! /usr/bin/python3

# open a file for reading
with open('series.csv') as csvfile:
    # iterate over lines of the input file
    for line in csvfile:
        # split a line into columns at commas
        columns = line.split(",")
        # print the second column
        print(columns[1])

• Python uses indentation to delimit blocks. In this example, the with command starts a block and within this block the for command starts another block containing commands columns=... and print. The body of each block is indented several spaces relative to the enclosing block.
• Variables are not declared, but directly used. This program uses variables csvfile, line, columns.
• The open command opens a file (here for reading, but other options are available).
• The with command opens the file, stores the file handle in csvfile variable, executes all commands within its block and finally closes the file.
• The for-loop iterates over all lines in the file, assigning each in variable line and executing the body of the block.
• Method split of the built-in string type str splits the line at every comma and returns a list of strings, one for every column of the table (see also other string methods)
• The final line prints the second column and the end of line character.

prog2.py

The following script prints the list of series of each TV channel.

• For illustration we also separately count the number of the series for each channel, but the count could be also obtained as the length of the list.

#! /usr/bin/python3
from collections import defaultdict

# Create a dictionary in which default value
# for non-existent key is 0 (type int)
# For each channel we will count the series
channel_counts = defaultdict(int)

# Create a dictionary for keeping a list of series per channel
# default value empty list
channel_lists = defaultdict(list)

# open a file and iterate over lines
with open('series.csv') as csvfile:
    for line in csvfile:
        # strip whitespace (e.g. end of line) from end of line
        line = line.rstrip()
        # split line into columns, find channel and series names
        columns = line.split(",")
        channel = columns[2]
        series = columns[1]
        # increase counter for channel
        channel_counts[channel] += 1
        # add series to list for the channel
        channel_lists[channel].append(series)

# print counts
print("Counts:")
for (channel, count) in channel_counts.items():
    print(f"Channel \"{channel}\" has {count} series.")

# print series lists
print("\nLists:")
for channel in channel_lists:
    list = ", ".join(channel_lists[channel]) 
    print("Series for channel \"%s\": %s" % (channel,list))

• In this script, we use two dictionaries (maps, associative arrays), both having channel names as keys. Dictionary channel_counts stores the number of series, channel_lists stores the list of series names.
• For simplicity we use a library data structure called defaultdict instead of a plain python dictionary. The reason is easier initialization: keys do not need to be explicitly inserted to the dictionary, but are initialized with a default value at the first access.
• Reading of the input file is similar to the previous script.
• Afterwards we iterate through the keys of both dictionaries and print both the keys and the values.
• We format the output string using f-strings f"..." where expressions in { } are evaluated and substituted to the string. Formatting similar to C-style printf, e.g. print(f"{2/3:.3f}").
• Notice that when we print counts, we iterate through pairs (channel, count) returned by channel_counts.items(), while when we print series, we iterate through keys of the dictionary.

prog3.py

This script finds the episode with the highest number of votes among all episodes.

• We use a library for csv parsing to deal with quotation marks around episode names with commas, such as "Dark Wings, Dark Words".
• This is done by first opening a file and then passing it as an argument to csv.reader, which returns a reader object used to iterate over rows.

#! /usr/bin/python3
import csv

# keep maximum number of votes and its episode
max_votes = 0
max_votes_episode = None

# open a file
with open('episodes.csv') as csvfile:
    # create a reader for parsing csv files
    reader = csv.reader(csvfile, delimiter=',', quotechar='"')
    # iterate over rows already split into columns
    for row in reader:
        votes = int(row[6])
        if votes > max_votes:
            max_votes = votes
            max_votes_episode = row[1]
        
# print result
print(f"Maximum votes {max_votes} in episode \"{max_votes_episode}\"")

prog4.py

The following script shows an example of function definition.

• The function reads a whole csv file into a 2d array.
• The rest of the program calls this function twice for each of the two files.
• This could be followed by some further processing of these 2d arrays.

#! /usr/bin/python3
import csv

def read_csv_to_list(filename):
    # create empty list
    rows = []
    # open a file
    with open(filename) as csvfile:
        # create a reader for parsing csv files
        reader = csv.reader(csvfile, delimiter=',', quotechar='"')
        # iterate over rows already split into columns
        for row in reader:
            rows.append(row)
    return rows

series = read_csv_to_list('series.csv')
episodes = read_csv_to_list('episodes.csv')
print(f"The number of episodes is {len(episodes)}.")
# further processing of series and episodes...