StephenFordham

for i in tqdm(range(1, 21)):

    player = WebDriverWait(browser, 20).until(expected_conditions.visibility_of_element_located((By.XPATH, '//*[@id="rankingDetailAjaxContainer"]/table/tbody/tr['+str(i)+']/td[4]/a')))
    Tennis_data_collection.write(player.text + ',')
    WebDriverWait(browser, 20).until(expected_conditions.visibility_of_element_located((By.XPATH, '//*[@id="rankingDetailAjaxContainer"]/table/tbody/tr['+str(i)+']/td[4]/a'))).click()
    turned_pro = WebDriverWait(browser, 20).until(expected_conditions.visibility_of_element_located((By.XPATH, '//*[@id="playerProfileHero"]/div[2]/div[2]/div/table/tbody/tr[1]/td[2]/div/div[2]'))).text
    career_length = 2019 - int(turned_pro)
    Tennis_data_collection.write(str(career_length) + ',')

    WebDriverWait(browser, 20).until(expected_conditions.visibility_of_element_located((By.XPATH, '//*[@id="profileTabs"]/ul/li[6]/a'))).click()

StephenFordham

import matplotlib.pyplot as plt 
from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import precision_recall_curve, auc
import seaborn as sns

X, y = make_classification(n_samples=1000, n_classes=2, random_state=1)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=2)
model = LogisticRegression(solver='lbfgs')

StephenFordham

import matplotlib.pyplot as plt 
# ROC and AUC modules
from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import roc_curve, roc_auc_score
import seaborn as sns 

# generate 2 class dataset
X, y = make_classification(n_samples=1000, n_classes=2, weights=[0.5], random_state=1)

StephenFordham

def meta_decorator(arg):
    def decorator_list(fnc):
        def inner(list_of_tuples):
            return [(fnc(val[0], val[1])) ** power for val in list_of_tuples]
        return inner
    if callable(arg):
        power = 2
        return decorator_list(arg)
    else:
        power = arg

StephenFordham

def integer_check(method):
	def inner(ref, expo=None):
		if expo == None:
			if not isinstance(ref._val1, int) or not isinstance(ref._val2, int):
				raise TypeError('Please enter numerical numbers for val1 and val2')
			else:
				return method(ref)
		if expo:
			if not isinstance(ref._val1, int) or not isinstance(ref._val2, int)\
					or not isinstance(expo, int):

StephenFordham

# Class Decorators: Using Decorators with methods defined in a Class

def integer_check(method):
	def inner(ref):
		if not isinstance(ref._val1, int) or not isinstance(ref._val2, int):
			raise TypeError('val1 and val2 must be integers')
		else:
			return method(ref)
	return inner

StephenFordham

class CustomIterTeams(object):
	def __init__(self, division, teams=[]):
		self._mng = division
		self._teams = teams
		self._index = -1

	def __iter__(self):
		return self

# 	def __iter__(self):

StephenFordham

# __init__ method with a decorator
def attr_validation(method):
    def inner(ref, name, age, location):
        for attr in [name, location]:
            if not isinstance(attr, str):
                raise TypeError('Name and Location attributes must be of type str')
        if not isinstance(age, int):
            raise TypeError('Age attributes must be of type int')
        return method(ref, name, age, location)
    return inner

StephenFordham

e1 = Employees(46347832, 30, 'Bournemouth')

for key, value in e1.__dict__.items():
    print('{}: {}'.format(key, value))
    
#Console output 

TypeError: Only valid attributes of type string are accepted

StephenFordham

class Employees(object):
    def __init__(self, name, age, location):
        self._name = name
        self._age = age
        self._location = location

    def __setattr__(self, key, value):
        if key in ['_name', '_location']:
            if not isinstance(value, str):
                raise TypeError('Only valid attributes of type string are accepted')