147 lines
4.2 KiB
Python
147 lines
4.2 KiB
Python
# 1. Annotate the following python expressions with the specific types of each literal, as well as the overall return value:
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# i = 3
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# f = 3.0
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# c = 3+3j
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# b = b'abcdefg'
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# s = 'abcdefg'
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# s = "abcdefg"
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i = 3
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f = 3.0
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c = 3+3j
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b = b'abcdefg'
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s1 = 'abcdefg'
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s2 = "abcdefg"
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def check_the_datatype():
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print()
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print('This is the answer for Q1:')
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print()
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variable_names = ['i', 'f', 'c', 'b', 's1', 's2']
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data_list = [i, f, c, b, s1, s2]
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for variable, data in zip(variable_names, data_list):
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print("The type of this assigned value {} = {} is: {}".format(variable, data, type(data).__name__))
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# 2. For each of the types string, bytestring, integer, floating point, and imaginary literals,
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# construct a 5x5 table showing what happens when the character "0" or number 0 is compared to each other type
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from tabulate import tabulate
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from termcolor import colored
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from tabulate import tabulate
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from termcolor import colored
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def tablesQ2():
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print()
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print('-' * 20)
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print()
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print('This is the answer for Q2:')
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print()
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types = ["String", "Byte String", "Integer", "Floating Point", "Imaginary"]
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literals = ['"0"', 'b"0"', '0', '0.0', '0j']
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table_data = []
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for type_ in types:
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row = [type_]
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for literal in literals:
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if type_ == "String":
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result = literal == '"0"'
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elif type_ == "Byte String":
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result = literal.encode() == b"0"
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elif type_ == "Integer":
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try:
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result = int(literal) == 0
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except ValueError:
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result = False
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elif type_ == "Floating Point":
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try:
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result = float(literal) == 0.0
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except ValueError:
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result = False
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elif type_ == "Imaginary":
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result = literal.replace('j', 'j0') == "0j"
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color = 'green' if result else 'red'
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colored_result = colored(result, color)
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row.append(colored_result)
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table_data.append(row)
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table = tabulate(table_data, headers=["Type"] + literals, tablefmt="pipe")
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print(table)
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# 3. Now do the same thing for the + and == operators for each pair of types in two other 5x5 tables.
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def tablesQ3():
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print()
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print('-' * 20)
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print()
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print('This is the answer for Q3:')
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print()
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operators = ["+", "=="]
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types = ["str", "bytes", "int", "float", "complex"]
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literals = ['"0"', 'b"0"', '0', '0.0', '0+0j']
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for operator in operators:
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print(f"Table for {operator} Operator:")
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table_data = []
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for type_ in types:
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row = [type_]
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for literal in literals:
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try:
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result = eval(f"{literal} {operator} {type_}({literal})")
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color = 'green'
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except TypeError:
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result = False
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color = 'red'
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colored_result = colored(result, color)
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row.append(colored_result)
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table_data.append(row)
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table = tabulate(table_data, headers=["Type"] + literals, tablefmt="pipe")
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print(table)
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print()
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# Write a small program that uses the AST module to open the lexer/parser example, and dumps the resulting AST.
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# See if there are any arguments to the parse method which make the output easier to read.
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# By default, ast.dump() prints the AST in a compact format.
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# However, there are two optional arguments that can enhance the readability:
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# indent: Specifies the number of spaces to use for indentation. Setting it to a positive integer (e.g., 4) indents each level of the AST by that amount.
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# annotate_fields: When set to True, adds field names as comments to the output, making it easier to identify each part of the AST.
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import ast
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def dump_ast(filename):
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with open(filename, 'r') as file:
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source_code = file.read()
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try:
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tree = ast.parse(source_code)
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ast_dump = ast.dump(tree, indent=4, annotate_fields=True)
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print(ast_dump)
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except SyntaxError as e:
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print(f"Syntax error in {filename}: {e}")
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if __name__ == "__main__":
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check_the_datatype()
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tablesQ2()
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tablesQ3()
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print()
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