Membangun aplikasi data berbasis command line

Anda sedang membangun alat command line yang memungkinkan pengguna menjelajahi himpunan data secara interaktif. Kami telah mendefinisikan empat fungsi: mean(), std(), minimum(), dan maximum() yang dapat dipanggil pengguna untuk menganalisis data mereka. Bantu selesaikan bagian kode ini agar pengguna dapat memanggil fungsi apa pun dengan mengetikkan nama fungsi pada prompt masukan.

Catatan: Fungsi get_user_input() pada latihan ini adalah versi tiruan dari meminta pengguna memasukkan perintah. Fungsi tersebut secara acak mengembalikan salah satu dari empat nama fungsi. Dalam praktiknya, Anda akan meminta masukan dan menunggu sampai pengguna memasukkan suatu nilai.

Latihan ini merupakan bagian dari kursus

Menulis Function di Python

Instruksi latihan

Tambahkan fungsi std(), minimum(), dan maximum() ke kamus function_map, seperti yang kita lakukan dengan mean().
Nama fungsi yang ingin dipanggil pengguna disimpan dalam func_name. Gunakan kamus fungsi, function_map, untuk memanggil fungsi yang dipilih dan teruskan data sebagai argumen.

Latihan interaktif langsung praktik

Cobalah latihan ini dengan melengkapi kode contoh ini.

# Add the missing function references to the function map
function_map = {
  'mean': mean,
  'std': ____,
  'minimum': ____,
  'maximum': ____
}

data = load_data()
print(data)

func_name = get_user_input()

# Call the chosen function and pass "data" as an argument
____[____](data)

Edit dan Jalankan Kode

Latihan ini merupakan bagian dari kursus

Menulis Function di Python

SkillTag.level.intermediateSkillTag.label

4.8+

Mulai Kursus Gratis

The goal of this course is to transform you into a Python expert, and so the first chapter starts off with best practices when writing functions. You'll cover docstrings and why they matter and how to know when you need to turn a chunk of code into a function. You will also learn the details of how Python passes arguments to functions, as well as some common gotchas that can cause debugging headaches when calling functions.

Exercise 1: Docstrings Exercise 2: Crafting a docstring Exercise 3: Retrieving docstrings Exercise 4: Docstrings to the rescue!Exercise 5: DRY and "Do One Thing"Exercise 6: Extract a function Exercise 7: Split up a function Exercise 8: Pass by assignment Exercise 9: Mutable or immutable?Exercise 10: Best practice for default arguments

If you've ever seen the "with" keyword in Python and wondered what its deal was, then this is the chapter for you! Context managers are a convenient way to provide connections in Python and guarantee that those connections get cleaned up when you are done using them. This chapter will show you how to use context managers, as well as how to write your own.

Exercise 1: Using context managers Exercise 2: The number of cats Exercise 3: The speed of cats Exercise 4: Writing context managers Exercise 5: The timer() context manager Exercise 6: A read-only open() context manager Exercise 7: Advanced topics Exercise 8: Context manager use cases Exercise 9: Scraping the NASDAQ Exercise 10: Changing the working directory

Decorators are an extremely powerful concept in Python. They allow you to modify the behavior of a function without changing the code of the function itself. This chapter will lay the foundational concepts needed to thoroughly understand decorators (functions as objects, scope, and closures), and give you a good introduction into how decorators are used and defined. This deep dive into Python internals will set you up to be a superstar Pythonista.

Exercise 1: Fungsi adalah objek Exercise 2: Membangun aplikasi data berbasis command line

Latihan Saat Ini

Exercise 3: Meninjau kode rekan kerja Anda Exercise 4: Mengembalikan fungsi untuk gim matematika Exercise 5: Ruang Lingkup Exercise 6: Memahami cakupan (scope)Exercise 7: Memodifikasi variabel di luar ruang lingkup lokal Exercise 8: Closure Exercise 9: Memeriksa closure Exercise 10: Closure menjaga nilai Anda tetap aman Exercise 11: Dekorator Exercise 12: Menggunakan sintaks dekorator Exercise 13: Mendefinisikan sebuah dekorator

Now that you understand how decorators work under the hood, this chapter gives you a bunch of real-world examples of when and how you would write decorators in your own code. You will also learn advanced decorator concepts like how to preserve the metadata of your decorated functions and how to write decorators that take arguments.

Exercise 1: Real-world examples Exercise 2: Print the return type Exercise 3: Counter Exercise 4: Decorators and metadata Exercise 5: Preserving docstrings when decorating functions Exercise 6: Measuring decorator overhead Exercise 7: Decorators that take arguments Exercise 8: Run_n_times()Exercise 9: HTML Generator Exercise 10: Timeout(): a real world example Exercise 11: Tag your functions Exercise 12: Check the return type Exercise 13: Great job!