![]() ![]() JupyterHub is a multi-user version of Jupyter Notebook, designed for teams, classrooms, and labs. JupyterHub is another offering from Project Jupyter. With JupyterLab, you can run terminals, text editors, and code consoles in your web browser. It allows you to set up your user interface to support various workflows in machine learning, data science, scientific computation, and more. In addition to the Jupyter Notebook, there’s also JupyterLab, which is a web-based IDE for Jupyter Notebooks. In 2014, Project Jupyter and Jupyter Notebook became spin-off projects from IPython and the IPython Notebook. It’s maintained by the Project Jupyter community. Self.Jupyter Notebook is an open-source web application used to create and share documents that have live code, equations, visualizations, and text. Self.assertTrue(quick_steps < slow_steps)ĭef test_slow_is_equal_to_quick_at_2(self): ![]() Self.assertEqual(expected_quick, expected_slow)Įxpected = my_calc.FibonacciSlow(my_calc.number)ĭef test_slow_needs_more_steps_with_11(self): My_calc.ResetNumber(self.list_of_values)Įxpected = my_calc.Fibonacci(my_calc.number)Įxpected_quick = my_calc.Fibonacci(my_calc.number)Įxpected_slow = my_calc.FibonacciSlow(my_calc.number) Self.list_of_values = np.arange(1, 22, 1).tolist() Still, comparing the results of the “slow” and the “quick” Fibonacci and comparing their operations was quite a must:Ĭlass FibonaticsTests(unittest.TestCase): I was quite “lucky” that I had prepared tests from the articles for C#, thus I did not have to come up with something extraordinary. Take a look at the difference of the number of calculations, between the function with memoization and the function with recursion – 49 vs 75025 is quite impressive. Number variable in the class, together with the other counters. ResetNumber ( self, number ) function is actually put there, so I can illustrate what the To present the difference between the different Fibonacci calculations, I have written an article some years ago – C# – Three Algorithms For Fibonacci Numbers. FibonacciSlow ( number - 2 )įibonacci ( self, number ) function is actually “Fibonacci on steroids”, using memoisation, while theįibonacciSlow ( self, number ) is the good old example of Fibonacci with recursion. ![]()
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