Pythoni sortimisloendi massiivi meetod - kasvav ja kahanev, selgitatud näidetega

Kui soovite õppida, kuidas sort()Pythoni projektides meetodiga töötada , siis see artikkel on mõeldud teile. See meetod on väga võimas ja saate seda vastavalt oma vajadustele kohandada, nii et vaatame, kuidas see üksikasjalikult töötab.

Sa õpid:

  • Kuidas seda meetodit kasutada ja selle funktsionaalsust kohandada.
  • Millal seda kasutada ja millal mitte kasutada.
  • Kuidas seda nimetada erinevate argumentide kombinatsioonide läbimiseks.
  • Loendi sortimine kasvavas ja kahanevas järjekorras.
  • Kuidas võrrelda loendi elemente vaheväärtuste põhjal.
  • Kuidas saate lambda funktsioone sellele meetodile edastada.
  • Kuidas seda meetodit võrreldakse sorted()funktsiooniga.
  • Miks sort()meetod teostab stabiilset sortimist.
  • Kuidas mutatsiooniprotsess kulisside taga toimib.

Oled sa valmis? Alustagem! ⭐

? Eesmärgi ja kasutamise juhtumid

Selle sort()meetodi abil saate loendi sortida kas:

  • Kasvav järjekord
  • Kahanev järjestus

Seda meetodit kasutatakse sorteerida nimekirja asemel, mis tähendab, et see muteerub või modifitseerib seda otse loomata täiendavaid koopiaid, nii pidage meeles:

Selles artiklis leiate lisateavet mutatsiooni kohta (luban!), Kuid praegu on väga oluline, et teaksite, et sort()meetod muudab loendit, nii et selle algne versioon on kadunud.

Seetõttu peaksite seda meetodit kasutama ainult siis, kui:

  • Soovite loendit jäädavalt muuta (sortida).
  • Te ei pea loendi algversiooni säilitama.

Kui see sobib teie vajadustega, on .sort()meetod just see, mida otsite.

? Süntaks ja argumendid

Vaatame, kuidas saate .sort()selle täisvõimsuse kasutamiseks helistada .

See on kõige elementaarsem kõne (ilma argumentideta):

Kui te ei edasta ühtegi argumenti, tehke vaikimisi järgmist.

  • Nimekiri sorteeritakse kasvavas järjekorras.
  • Loendi elemente võrreldakse otse nende väärtusega <operaatoriga.

Näiteks:

>>> b = [6, 3, 8, 2, 7, 3, 9] >>> b.sort() >>> b [2, 3, 3, 6, 7, 8, 9] # Sorted!

Kohandatud argumendid  

sort()Meetodi toimimise kohandamiseks võite edastada kaks valikulist argumenti:

  • Võti
  • Tagurpidi

Vaatame, kuidas nad muudavad selle meetodi käitumist. Siin on meetodikõne nende kahe argumendiga:

Enne nende töö selgitamist tahaksin selgitada midagi, mida te ilmselt ülaltoodud diagrammil märkasite - meetodi väljakutses tuleb parameetrite nimed lisada enne nende vastavaid väärtusi, näiteks:

  • key=
  • reverse=

Seda seetõttu, et need on ainult märksõnade argumendid . Kui edastate neile kohandatud väärtuse, tuleb meetodi kutses täpsustada nende nimed , millele järgneb võrdusmärk =ja vastavad väärtused, näiteks:

Vastasel juhul, kui proovite argumente edastada otse, nagu me tavaliselt teeme positsiooniparameetrite puhul, näete seda viga, kuna funktsioon ei tea, milline argument millisele parameetrile vastab:

TypeError: sort() takes no positional arguments

Tagurpidi

Nüüd, kui teate, mis on ainult märksõnadega seotud argumendid, alustame reverse.

Väärtus reversevõib olla kas Truevõi False:

  • False tähendab, et loetelu sorteeritakse kasvavas järjekorras.
  • True tähendab, et loetelu sorteeritakse kahanevas (vastupidises) järjekorras.

? Nõuanne . Vaikimisi on selle väärtus False- kui te ei anna selle parameetri jaoks ühtegi argumenti, sorteeritakse loend kasvavas järjekorras.

Siin on mõned näited:

# List of Integers >>> b = [6, 3, 8, 2, 7, 3, 9] >>> b.sort() >>> b [2, 3, 3, 6, 7, 8, 9] # List of Strings >>> c = ["A", "Z", "D", "T", "U"] >>> c.sort() >>> c ['A', 'D', 'T', 'U', 'Z'] 

? Nõuanne: kui loendi elemendid on stringid, sorteeritakse need tähestiku järgi.

# List of Integers >>> b = [6, 3, 8, 2, 7, 3, 9] >>> b.sort(reverse=True) >>> b [9, 8, 7, 6, 3, 3, 2] # List of Strings >>> c = ["A", "Z", "D", "T", "U"] >>> c.sort(reverse=True) >>> c ['Z', 'U', 'T', 'D', 'A']

? Nõuanne. Pange tähele, kuidas loend on järjestatud kahanevas järjekorras, kui see reverseon True.

Võti

Nüüd, kui teate, kuidas reverseparameetriga töötada , vaatame keyparameetrit.

See parameeter on natuke üksikasjalikum, kuna see määrab, kuidas loendi elemente sortimisprotsessi käigus võrreldakse.

Väärtus keyon kas:

  • None, which means that the elements of the list will be compared directly. For example, in a list of integers, the integers themselves can be used for the comparison.
  • Afunction of one argument that generates an intermediate value for each element. This intermediate value is calculated only once and it's used to make the comparisons during the entire sorting process. We use this when we don't want to compare the elements directly, for example, when we want to compare strings based on their length (the intermediate value).

? Tip: By default, the value of key is None, so the elements are compared directly.

For example:

Let's say that we want to sort a list of strings based on their length, from the shortest string to the longest string. We can pass the function len as the value of key, like this:

>>> d = ["aaa", "bb", "c"] >>> d.sort(key=len) >>> d ['c', 'bb', 'aaa']

? Tip: Notice that we are only passing the name of the function (len) without parenthesis because we are not calling the function. This is very important.

Notice the difference between comparing the elements directly and comparing their length (see below). Using the default value of key (None) would have sorted the strings alphabetically (left), but now we are sorting them based on their length (right):

What happens behind the scenes? Each element is passed as an argument to the len() function, and the value returned by this function call is used to perform the comparisons during the sorting process:

This results in a list with a different sorting criteria: length.

Here we have another example:

Another interesting example is sorting a list of strings as if they were all written in lowercase letters (for example, making "Aa" equivalent to "aa").

According to lexicographical order, capital letters come before lowercase letters:

>>> "E" < "e" True

So the string "Emma" would come before "emily" in a sorted list, even if their lowercase versions would be in the opposite order:

>>> "Emma" >> "emma" < "emily" False

To avoid distinguishing between capital and lowercase letters, we can pass the function str.lower as key. This will generate a lowercase version of the strings that will be used for the comparisons:

>>> e = ["Emma", "emily", "Amy", "Jason"] >>> e.sort(key=str.lower) >>> e ['Amy', 'emily', 'Emma', 'Jason']

Notice that now, "emily" comes before "Emma" in the sorted list, which is exactly what we wanted.

? Tip: if we had used the default sorting process, all the strings that started with an uppercase letter would have come before all the strings that started with a lowercase letter:

>>> e = ["Emma", "emily", "Amy", "Jason"] >>> e.sort() >>> e ['Amy', 'Emma', 'Jason', 'emily']

Here is an example using Object-Oriented Programming (OOP):

If we have this very simple Python class:

>>> class Client: def __init__(self, age): self.age = age

And we create four instances:

>>> client1 = Client(67) >>> client2 = Client(23) >>> client3 = Client(13) >>> client4 = Client(35)

We can make a list that references them:

>>> clients = [client1, client2, client3, client4]

Then, if we define a function to get the age of these instances:

>>> def get_age(client): return client.age

We can sort the list based on their age by passing the get_age function an an argument:

>>> clients.sort(key=get_age)

This is the final, sorted version of the list. We use a for loop to print the age of the instances in the order that they appear in the list:

>>> for client in clients: print(client.age) 13 23 35 67

Exactly what we wanted – now the list is sorted in ascending order based on the age of the instances.

? Tip: Instead of defining a get_age function, we could have used a lambda function to get the age of each instance, like this:

>>> clients.sort(key=lambda x: x.age)

Lambda functions are small and simple anonymous functions, which means that they don't have a name. They are very helpful for these scenarios when we only want to use them in particular places for a very short period of time.

This is the basic structure of the lambda function that we are using to sort the list:

Passing Both Arguments

Awesome! Now you know to customize the functionality of the sort() method. But you can take your skills to a whole new level by combining the effect of key and reverse in the same method call:

>>> f = ["A", "a", "B", "b", "C", "c"] >>> f.sort(key=str.lower, reverse=True) >>> f ['C', 'c', 'B', 'b', 'A', 'a']

These are the different combinations of the arguments and their effect:

The Order of Keyword-Only Arguments Doesn't Matter

Since we are specifying the names of the arguments, we already know which value corresponds to which parameter, so we can include either key or reverse first in the list and the effect will be exactly the same.

So this method call:

Is equivalent to:

This is an example:

>>> a = ["Zz", "c", "y", "o", "F"] >>> a.sort(key=str.lower, reverse=True) >>> a ['Zz', 'y', 'o', 'F', 'c']

If we change the order of the arguments, we get the exact same result:

>>> a = ["Zz", "c", "y", "o", "F"] >>> a.sort(reverse=True, key=str.lower) >>> a ['Zz', 'y', 'o', 'F', 'c']

? Return Value

Räägime nüüd natuke selle meetodi tagastusväärtusest. sort()Meetod tagastab None- see ei ole tagastada järjestatud loetelu versiooni, nagu me võiksime intuitiivselt oodata.

Vastavalt Pythoni dokumentatsioonile:

Kasutajatele meelde tuletamiseks, et see toimib kõrvalmõjuna, ei tagasta see järjestatud järjestust.

Põhimõtteliselt kasutatakse seda selleks, et meelde tuletada, et me muudame mälus algset loendit, mitte ei loo loendi uut koopiat.

See on näide järgmise väärtuse tagastusväärtusest sort():

>>> nums = [6.5, 2.4, 7.3, 3.5, 2.6, 7.4] # Assign the return value to this variable: >>> val = nums.sort() # Check the return value: >>> print(val) None

Näete? Nonetagastati meetodi kutsega.

? Tip: It is very important not to confuse the sort() method with the sorted() function, which is a function that works very similarly, but doesn't modify the original list. Instead sorted() generates and returns a new copy of the list, already sorted.

This is an example that we can use to compare them:

# The sort() method returns None >>> nums = [6.5, 2.4, 7.3, 3.5, 2.6, 7.4] >>> val = nums.sort() >>> print(val) None
# sorted() returns a new sorted copy of the original list >>> nums = [6.5, 2.4, 7.3, 3.5, 2.6, 7.4] >>> val = sorted(nums) >>> val [2.4, 2.6, 3.5, 6.5, 7.3, 7.4] # But it doesn't modify the original list >>> nums [6.5, 2.4, 7.3, 3.5, 2.6, 7.4]

This is very important because their effect is very different. Using the sort() method when you intended to use sorted() can introduce serious bugs into your program because you might not realize that the list is being mutated.

? The sort() Method Performs a Stable Sort

Now let's talk a little bit about the characteristics of the sorting algorithm used by sort().

See meetod teostab stabiilset sorteerimist, kuna see töötab TimSorti rakendusega, mis on väga tõhus ja stabiilne sortimisalgoritm.

Vastavalt Pythoni dokumentatsioonile:

Sorteerimine on stabiilne, kui see tagab , et võrdsete elementide suhtelist järjestust ei muudeta - see on kasulik mitme läbimise korral sortimiseks (näiteks sortimine osakonna, siis palgaastme järgi).

See tähendab, et kui kahel elemendil on sama väärtus või vaheväärtus (võti), siis tagatakse nende püsimine üksteise suhtes samas järjekorras.

Vaatame, mida ma sellega mõtlen. Vaadake mõni hetk seda näidet:

>>> d = ["BB", "AA", "CC", "A", "B", "AAA", "BBB"] >>> d.sort(key=len) >>> d ['A', 'B', 'BB', 'AA', 'CC', 'AAA', 'BBB']

Me võrdleme elemente nende pikkuse põhjal, kuna andsime lenfunktsiooni argumendina edasi key.

We can see that there are three elements with length 2: "BB", "AA", and "CC" in that order.

Now, notice that these three elements are in the same relative order in the final sorted list:

This is because the algorithm is guaranteed to be stable and the three of them had the same intermediate value (key) during the sorting process (their length was 2, so their key was 2).

? Tip: The same happened with "A" and "B" (length 1) and "AAA" and "BBB" (length 3), their original order relative to each other was preserved.

Now you know how the sort() method works, so let's dive into mutation and how it can affect your program.

? Mutation and Risks

As promised, let's see how the process of mutation works behind the scenes:

When you define a list in Python, like this:

a = [1, 2, 3, 4]

You create an object at a specific memory location. This location is called the "memory address" of the object, represented by a unique integer called an id.

You can think of an id as a "tag" used to identify a specific place in memory:

You can access a list's id using the id() function, passing the list as argument:

>>> a = [1, 2, 3, 4] >>> id(a) 60501512

When you mutate the list, you change it directly in memory. You may ask, why is this so risky?

It's risky because it affects every single line of code that uses the list after the mutation, so you may be writing code to work with a list that is completely different from the actual list that exists in memory after the mutation.

This is why you need to be very careful with methods that cause mutation.

In particular, the sort() method mutates the list. This is an example of its effect:

Here is an example:

# Define a list >>> a = [7, 3, 5, 1] # Check its id >>> id(a) 67091624 # Sort the list using .sort() >>> a.sort() # Check its id (it's the same, so the list is the same object in memory) >>> id(a) 67091624 # Now the list is sorted. It has been mutated! >>> a [1, 3, 5, 7]

The list was mutated after calling .sort().

Every single line of code that works with list a after the mutation has occurred will use the new, sorted version of the list. If this was not what you intended, you may not realize that other parts of your program are working with the new version of the list.

Here is another example of the risks of mutation within a function:

# List >>> a = [7, 3, 5, 1] # Function that prints the elements of the list in ascending order. >>> def print_sorted(x): x.sort() for elem in x: print(elem) # Call the function passing 'a' as argument >>> print_sorted(a) 1 3 5 7 # Oops! The original list was mutated. >>> a [1, 3, 5, 7]

The list a that was passed as argument was mutated, even if that wasn't what you intended when you initially wrote the function.

? Tip: If a function mutates an argument, it should be clearly stated to avoid introducing bugs into other parts of your program.

? Summary of the sort() Method

  • The sort() method lets you sort a list in ascending or descending order.
  • It takes two keyword-only arguments: key and reverse.
  • reverse determines if the list is sorted in ascending or descending order.
  • key is a function that generates an intermediate value for each element, and this value is used to do the comparisons during the sorting process.
  • The sort() method mutates the list, causing permanent changes. You need to be very careful and only use it if you do not need the original version of the list.

Loodan väga, et teile meeldis minu artikkel ja see oli teile kasulik. Nüüd saatesort()Pythoni projektidessellemeetodigatöötada. Vaadake minu veebikursusi. Jälgi mind Twitteris. ⭐️