    string = "Great success. My name is Borat. I have come to America, to find <NAME>, and \
        make her my wife. Very nice!"
    string2 = "take in a database of URLs associated with particular usernames, store it in dictionary with scores,\
    append it to dict_list2, now should have list of dictionaries to scroll through"
    string3 = " Once you have a list of dictionaries, you can scroll through each score related to each function, \
    one by one,  and get the data needed to start implementing the curve function, to then ultimately, \
        return star values for each player"
    string4 = "Remember that the Learning Rate is a hyperparameter that is specific to your gradient-descent based optimizer \
    selection. A learning rate that is too high will cause divergent behavior, but a Learning Rate that is\
         too low will fail to converge, again, you're looking for the sweet spot."
    string5 = "Momentum is a hyperparameter that is more commonly associated with Stochastic Gradient Descent. \
    SGD is a common optimizer because it's what people understand and know, but I doubt it will get you the \
        best results, you can try hyperparameter tuning its attributes and see if you can beat the performance from adam."         
    string6 = "Using dropout on hidden layers might not have any effect while using dropout on hidden layers might\
     have a substantial effect. You don't necessarily need to turn use dropout unless you see that your model\
          has overfitting and generalizability problems."
    string7 = "In the case of a binomial outcome (flipping a coin), the binomial distribution may be \
    approximated by a normal distribution (for sufficiently large n {\displaystyle n} n). Because \
        the square of a standard normal distribution is the chi-square distribution with one degree of freedom,\
             the probability of a result such as 1 heads in 10 trials can be approximated either by using \
                 the normal distribution directly, or the chi-square distribution for the normalised,\
                      squared difference between observed and expected value."
    string8 = "The rabbit-hole went straight on like a tunnel for some way, and then dipped suddenly down, so suddenly\
     that Alice had not a moment to think about stopping herself before she found herself falling down a very deep well. "
    string9 = "Tell me that first, and then, if I like being that person,\
         I’ll come up: if not, I’ll stay down here till I’m somebody else’—but, \
             oh dear!” cried Alice, with a sudden burst of tears, “I do wish they\
                  would put their heads down! I am so very tired of being all alone here"

    a = store(string, "bill")
    b = store(string2, "Kate")
    c = store(string3, "Edward")
    d = store(string4, "Bobby")
    e = store(string5, "Hadi")
    f = store(string6, "Jesse")
    g = store(string7, "Pierre")
    h = store(string8, "Bruce")
    i = store(string9, "Franklin")

    

    dictlist2 = []
    dictlist2.append(a)
    dictlist2.append(b)
    dictlist2.append(c)
    dictlist2.append(d)
    dictlist2.append(e)
    dictlist2.append(f)
    dictlist2.append(g)
    dictlist2.append(h)
    dictlist2.append(i)
    string = "Great success. My name is Borat. I have come to America, to find <NAME>, and \
        make her my wife. Very nice!"
    string2 = "take in a database of URLs associated with particular usernames, store it in dictionary with scores,\
    append it to dict_list2, now should have list of dictionaries to scroll through"
    string3 = " Once you have a list of dictionaries, you can scroll through each score related to each function, \
    one by one,  and get the data needed to start implementing the curve function, to then ultimately, \
        return star values for each player"
    string4 = "Remember that the Learning Rate is a hyperparameter that is specific to your gradient-descent based optimizer \
    selection. A learning rate that is too high will cause divergent behavior, but a Learning Rate that is\
         too low will fail to converge, again, you're looking for the sweet spot."
    string5 = "Momentum is a hyperparameter that is more commonly associated with Stochastic Gradient Descent. \
    SGD is a common optimizer because it's what people understand and know, but I doubt it will get you the \
        best results, you can try hyperparameter tuning its attributes and see if you can beat the performance from adam."         
    string6 = "Using dropout on hidden layers might not have any effect while using dropout on hidden layers might\
     have a substantial effect. You don't necessarily need to turn use dropout unless you see that your model\
          has overfitting and generalizability problems."
    string7 = "In the case of a binomial outcome (flipping a coin), the binomial distribution may be \
    approximated by a normal distribution (for sufficiently large n {\displaystyle n} n). Because \
        the square of a standard normal distribution is the chi-square distribution with one degree of freedom,\
             the probability of a result such as 1 heads in 10 trials can be approximated either by using \
                 the normal distribution directly, or the chi-square distribution for the normalised,\
                      squared difference between observed and expected value."
    string8 = "The rabbit-hole went straight on like a tunnel for some way, and then dipped suddenly down, so suddenly\
     that Alice had not a moment to think about stopping herself before she found herself falling down a very deep well. "
    string9 = "Tell me that first, and then, if I like being that person,\
         I’ll come up: if not, I’ll stay down here till I’m somebody else’—but, \
             oh dear!” cried Alice, with a sudden burst of tears, “I do wish they\
                  would put their heads down! I am so very tired of being all alone here"

    a = store(string, "bill")
    b = store(string2, "Kate")
    c = store(string3, "Edward")
    d = store(string4, "Bobby")
    e = store(string5, "Hadi")
    f = store(string6, "Jesse")
    g = store(string7, "Pierre")
    h = store(string8, "Bruce")
    i = store(string9, "Franklin")

    

    dictlist2 = []
    dictlist2.append(a)
    dictlist2.append(b)
    dictlist2.append(c)
    dictlist2.append(d)
    dictlist2.append(e)
    dictlist2.append(f)
    dictlist2.append(g)
    dictlist2.append(h)
    dictlist2.append(i)