# A simple web scraper

I've written a simple web scraper in Python. As it is my first venture in Python, I'd like to ask for a code review from more experienced coders. All input is welcome.

A little bit of background:

I'm a huge fan of video games. In Japan, there is a company called Media Create which tracks all sales of games and consoles and releases them weekly (in Japanese language). Another site (www.gematsu.com) translates those charts and releases them weekly on their website. My script fetches the data and saves it to a text file.

The script should run as-is, but it is dependent on a text file of the previous week existing in script-location/data.

The name of the script needs to be something like media-create-sales-11-26-18-12-2-18.txt (replacing the start and end dates with any dates other than the dates of the most recently released data).

I am not affiliated with Media Create or Gematsu and this script serves no commercial purpose.

import requests
from bs4 import BeautifulSoup
import datetime
import glob
import os

def getLatestFilename():

list_of_files = glob.glob('data/*')
latest_file = max(list_of_files, key=os.path.getctime)

return latest_file

def parseUrl(dateString):

dateString = dateString.split('-')

lastdateString = str("-".join(dateString[6:9])).split('.')[0]

lastdate_object = datetime.datetime.strptime(lastdateString, "%m-%d-%y")

current_startdatetime_object = lastdate_object + datetime.timedelta(days=1)
current_enddatetime_object = lastdate_object + datetime.timedelta(days=7)

cur_startDateString = current_startdatetime_object.strftime("%m-%d-%y").lstrip("0").replace("0", "")
cur_endDateString = current_enddatetime_object.strftime("%m-%d-%y").lstrip("0").replace("0", "")

return (cur_startDateString + '-' + cur_endDateString)

def getUrl(filename):

curIntervalString = parseUrl(filename)

now = datetime.datetime.now()

url = list()
url.append("https://gematsu.com/")
url.append(str(now.year))
url.append('/')
url.append(str(now.month))
url.append('/')
url.append('media-create-sales-')
url.append(curIntervalString)

return url

def fetchContentForUrl(url):

page = requests.get(url)
soup = BeautifulSoup(page.text, 'html.parser')

outputfile = open("data/media" + url.split('media')[1] + ".txt", "w")

outputfile.write(url + '\n' + '\n')

content = soup.find(class_='entry')

gameCharts = content.findNext('ol')
gameEntries = gameCharts.find_all('li')

for idx,entry in enumerate(gameEntries,start=1):
outputfile.write(str(idx) + "." + entry.get_text() + "\n")

print ('\n')

consoleCharts = gameCharts.find_next_sibling("ol")
consoleEntries = consoleCharts.find_all('li')

for entry in consoleEntries:
outputfile.write(entry.get_text() + "\n")

def main():
latestFilename = getLatestFilename()
print (latestFilename)
url = ''.join(getUrl(latestFilename))
print (url)
fetchContentForUrl(url)

if __name__ == '__main__':
main()


This is a very good attempt for the first Python venture!

Here is what I would consider improving:

• stylistic / PEP8

• naming. In Python, it is recommended to use lower_case_with_underscores notation. Your function and variable names are inconsistent and there is a mix of styles - e.g. cur_startDateString follows both camelCase and lower_case_with_underscores
• the user of blank lines. In Python, it is recommended to have 2 blank lines between top-level blocks of the code and have an extra new-line at the end of the script
• the use of whitespaces. Watch for whitespaces after commas in expressions, e.g.:

for idx,entry in enumerate(gameEntries,start=1):
^                              ^

• import grouping and order. See Imports section of the PEP8

• parenthesis around the return value are redundant
• consider adding docstrings explaining what your functions are about. For instance, getLatestFilename would benefit from a note about how does it define which file is the latest. And, parseUrl is not really easy to understand just by reading the code
• if you are using Python 3.5+, consider adding Type Hints
• Design and modularity

• it is a good thing that you tried to logically separate scraping from parsing
• I would also separate parsing and dumping the results into a CSV file
• HTML Parsing

• if performance is a concern, consider switching from html.parser to lxml - see "Installing a Parser" section of the documentation
• you could also improve performance of the parsing stage by using a SoupStrainer which allows you to parse the desired part of the HTML tree in the first place:

from bs4 import BeautifulSoup, SoupStrainer

parse_only = SoupStrainer(class_='entry')
soup = BeautifulSoup(page.text, 'lxml', parse_only=parse_only)

• .findNext() is deprecated in favour of .find_next()

• Other

• getUrl() method feels a little bit overcomplicated and you can definitely improve its readability and simplify it at the same time. Plus, I would make it return the URL as a string and not as a list to avoid any extra external code needed to make it a string. If you are using Python 3.6+, f-strings would be handy:

def get_url(filename: str) -> str:
"""Constructs a complete URL based on the filename and current date."""
current_interval = parse_url(filename)

now = datetime.datetime.now()

return f"https://gematsu.com/{now.year}/{now.month}/media-create-sales-{current_interval}"


Having the complete URL string with placeholders helps to see what the end result might look like.

Note that most of the PEP8 violations mentioned above could be caught by running a linter (like flake8, or pylint) against your code.