<jupyter_start><jupyter_text>hasattribute( object, attribute name)   getattribute( object, attribute name)    delatttr(object, attribute name)<jupyter_code>hasattr(s1, "name")
hasattr(s2, "name")
getattr(s1, "name")
getattr(s3, "name")
getattr(s2, "name")
getattr(s2, "name", "no attribute")
getattr(s3, "name", "")
delattr(s2, "rollNumber")
s2.__dict__
s1.name
#Predict the output
class Student:
     name = "Rohan"
     age = 16
s1 = Student()
s2 = Student()
print(s1.name,end=" ")
print(s2.name,end=" ")
#Predict the output
class Student:
    pp = 50

s1 = Student()
s1.pp= 58
s2 = Student()
s2.pp = 60
print(s1.pp)
#Predict the output
class Student:
    name = "Parikh"
    def store_details(self):
        self.age = 60
    def print_details(self):
        print(self.name, end=" ")
        print(self.age)
s = Student()
s.store_details()
s.print_details()
#Predict the output
class Student:
    name = "Parikh"
    def store_details(self):
        self.age = 60
    def print_age(self):
        print(self.age)
s = Student()
s.store_details()
s1 = Student()
s1.print_age()
s1.__dict__<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15178571428571427, 'fraction_numerical': 0.030357142857142857, 'mean_word_length': 4.04954954954955, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '81705', 'license': 'Unlicense', 'n_tokens_mistral': 443, 'n_tokens_neox': 428, 'n_words': 102, 'path': '03 OOPS-1/3.03 Instance Attributes.ipynb', 'repo_name': 'suhassuhas/Coding-Ninjas---Data-Structures-and-Algorithms-in-Python', 'size': '1120'}