Command-line NHL skaters stats tool

Question

Have been playing with the undocumented NHL API for some days. I'd love to see any input about this little script. About overall structure, style, performance enhancements, etc. Not sure how to properly use long links in Python, should I even follow the PEP in this case? The same problem in a couple of other lines, it exceeds 79 symbols limit. Not sure if I should use pluses in the 'printed_info' lines, it behaves the same way without it, but some say it's more explicit, so it's better.

import requests
import json
import os
import collections
import timeit
import datetime


def basic_bio():
    api_basic_bio = "http://www.nhl.com/stats/rest/skaters?isAggregate=false&reportType=basic&isGame=false&reportName=skaterpercentages&cayenneExp=gameTypeId=2%20and%20seasonId=20182019"

    json_data = requests.get(api_basic_bio).json()
    basic_full_bio_list = json_data["data"]
    return basic_full_bio_list


def lastnames():
    list_lastnames = []
    players_range = range(len(basic_bio()))
    json_bios = basic_bio()

    for number in players_range:
        list_lastnames.append((json_bios[number]["playerLastName"]).lower())

    return list_lastnames


def duplicate_last_names():
    last_names_count = collections.Counter(lastnames())
    dup_last_names = {k: v for k, v in last_names_count.items() if v > 1}
    return dup_last_names


def get_id_name_dict():
    players_id_dict = {}
    players_range = range(len(basic_bio()))
    dups = duplicate_last_names()
    skaters = basic_bio()

    for number in players_range:
        if (skaters[number]["playerLastName"]).lower() in dups:
            players_id_dict[skaters[number]["playerName"].lower()] = skaters[number]["playerId"]
        else:
            players_id_dict[skaters[number]["playerLastName"].lower()] = skaters[number]["playerId"]

    with open('nhl_skaters_id.json', 'w') as file:
         file.write(json.dumps(players_id_dict, indent=4, sort_keys=True))


def get_id(player_lastname):
    with open('nhl_skaters_id.json') as file:
      data = json.load(file)
    dups = duplicate_last_names()

    if player_lastname in dups:
        player_firstname = input("Enter a player's firstname: ").lower()
        return data[player_firstname + ' ' + player_lastname]
    else:
        return data[player_lastname]


def get_stats(id):
    api_base = 'https://statsapi.web.nhl.com/api/v1/people/'
    api_end = '?hydrate=stats(splits=statsSingleSeason)'
    url = ''.join([api_base, str(id), api_end])
    json_data = requests.get(url).json()
    stats = json_data["people"]
    return stats


def show_stats(data):
    path_stats = data[0]['stats'][0]['splits'][0]['stat']
    path_bio = data[0]

    printed_info = (f"Name: {path_bio['fullName']}\n\n" +
         f"Birth Date: {path_bio['birthDate']}\n" +
         f"Height: {path_bio['height']}\n" +
         f"Weight: {path_bio['weight']}\n\n" +
         f"Games: {path_stats['games']}\n" +
         f"Goals: {path_stats['goals']}\n" +
         f"Assists: {path_stats['assists']}\n" +
         f"Points: {path_stats['points']}\n" +
         f"PP Points: {path_stats['powerPlayPoints']}\n" +
         f"Plus-minus: {path_stats['plusMinus']}\n" +
         f"Shots: {path_stats['shots']}\n" +
         f"Hits: {path_stats['hits']}\n" +
         f"Blocks: {path_stats['blocked']}\n" +
         f"Penalty Minutes: {path_stats['pim']}\n" +
         f"TOI per Game: {path_stats['timeOnIcePerGame']}\n" +
         f"PP TOI per Game: {path_stats['powerPlayTimeOnIcePerGame']}\n" +
         f"SH TOI per Game: {path_stats['shortHandedTimeOnIcePerGame']}\n")

    print(printed_info)


def data_old(file_name):
    one_day_ago = datetime.datetime.now() - datetime.timedelta(days=1)
    filetime = datetime.datetime.fromtimestamp(os.path.getmtime(file_name))

    if filetime < one_day_ago:
        return True
    else:
        return False


player_lastname = input("Enter a player's lastname: ").lower()

if os.path.isfile('nhl_skaters_id.json') == False or data_old('nhl_skaters_id.json') == True:
    get_id_name_dict()

try:
    data = get_stats(get_id(player_lastname))
    print('-----------------------------')
    show_stats(data)
except Exception:
    print(f"{player_lastname.capitalize()} did't play any NHL games this season")

Answer 1

• One way to deal with long URLs that are long because of lots of parameters is to let requests deal with those parameters by passing a dictionary:

  URL = "http://www.nhl.com/stats/rest/{}"
  
  def basic_bio():
      params = {"isAggregate": "false",
                "reportType": "basic",
                "isGame": "false",
                "reportName": "skaterpercentages",
                "cayenneExp": "gameTypeId=2 and seasonId=20182019"}
      return requests.get(URL.format("skaters"), params=params).json()["data"]
  

  It even performs the urlencoding for you (by escaping the spaces in the last parameter, in this case).

• Don't Repeat Yourself (DRY). In addition, always try to iterate over the elements of an iterable, instead of indices. This allows you to use iterable but not indexable things (like generators). For lastnames, you can use a list comprehension, though:

  def lastnames():
      return [player["playerLastName"].lower() for player in basic_bio()]
  

• Python has multiline strings:

  PLAYER_STATS = """Name: {fullName}
  
  Birth Date: {birthDate}
  Height: {height}
  ...
  SH TOI per Game: {shortHandedTimeOnIcePerGame}
  
  """
  
  def show_stats(data):
      path_stats = data[0]['stats'][0]['splits'][0]['stat']
      path_bio = data[0]
      print(PLAYER_STATS.format(**path_bio, **path_stats))
  

  This uses the fact that in Python 3 you can keyword expand multiple mappings. It is OK if not all keys of the dictionary/ies are used.

• Instead of comparing something directly with False or True, like in

  if os.path.isfile('nhl_skaters_id.json') == False or data_old('nhl_skaters_id.json') == True:
      # get info
  

  just do

  skaters_json = 'nhl_skaters_id.json'
  if not os.path.isfile(skaters_json) or data_old(skaters_json):
      # get info
  

• Don't explicitly return True or False unless you really have to. Instead of

  if filetime < one_day_ago:
      return True
  else:
      return False
  

  Just do

  return filetime < one_day_ago
  

• You should wrap your calling code in a if __name__ == "__main__": guard to allow importing from this script without executing those functions.
• When catching exceptions, try to be as specific as possible. except Exception is already better than a bare except (because at least it does not prevent the user from exiting using Ctrl+C), but if you know the specific exception (or exceptions) you want to guard against, then use that knowledge. Here it is probably a IndexError or KeyError?