Dans le cadre du cours «Développeur Python. Basic »a préparé une traduction de matériel utile pour vous.
Nous invitons également tout le monde à un webinaire ouvert sur le thème "Trois baleines: map (), filter () et zip ()" . Pouvez-vous écrire du code qui nécessite des boucles mais pas de boucles? Peut. Serait-ce plus rapide que si nous utilisions des boucles en Python? Peut. Pour mettre en œuvre le plan, vous aurez besoin de connaître les mots «callback», «iterator» et «lambda». Ce sera difficile, mais intéressant. Rejoignez-nous.
Nous ajoutons des algorithmes de clustering à l'aide de scikit-learn, Keras et d'autres packages à Photonai. Nous allons vous montrer comment @dataclass
améliorer votre code Python avec 12 exemples . Pour ce faire, nous utilisons le code du package Photonai pour le Machine Learning.
Mettre à niveau vers Python 3.7 ou version ultérieure
@dataclass
Python 3.7. Python 3.7 Docker-, /.bashrc_profile
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devdir='<path-to-projects>/photon/photonai/dockerSeasons/dev/'
testdir='<path-to-projects>/photon/photonai/dockerSeasons/test/'
echo $devdir
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export testdir
export devdir
#
alias updev="(cd $devdir; docker-compose up) &"
alias downdev="(cd $devdir; docker-compose down) &"
alias builddev="(cd $devdir; docker-compose build) &"
#
alias uptest="(cd $testdir; docker-compose up) & "
alias downtest="(cd $testdir; docker-compose down) &"
alias buildtest="cd $testdir; docker-compose build) &"
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https://medium.com/swlh/future-proof-your-python-code-20ef2b75e9f5
https://realpython.com/python-type-checking/
https://docs.python.org/3/library/typing.html
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photon/photonai/base/hyperpipe.py
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### Example #1
class Data:
def __init__(self, X=None, y=None, kwargs=None):
self.X = X
self.y = y
self.kwargs = kwargs
1, =>
from dataclasses import dataclass
from typing import Dict
import numpy as np
@dataclass
class Data:
X: np.ndarray = None # The field declaration: X
y: np.array = None # The field declaration: y
kwargs: Dict = None # The field declaration: kwargs
: , . any
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eq()
?
### Example #2
data1 = Data()
data2 = Data()
data1 == data1
2, =>
True
! repr()
str
?
### Example #3
print(data1)
data1
, =>
Data(X=None, y=None, kwargs=None)
Data(X=None, y=None, kwargs=None)
! hash()
init
?
Example #4
@dataclass(unsafe_hash=True)
class Data:
X: np.ndarray = None
y: np.array = None
kwargs: Dict = None
data3 = Data(1,2,3)
{data3:1}
4, =>
{Data(X=1, y=2, kwargs=3): 1}
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inspect
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### Example #5
from inspect import signature
print(signature(data3.__init__))
5, =>
(X: numpy.ndarray = None, y: <built-in function array> = None,
kwargs: Dict = None) -> None
!
photon/photonai/base/hyperpipe.py
### Example #6
class CrossValidation:
def __init__(self, inner_cv, outer_cv,
eval_final_performance, test_size,
calculate_metrics_per_fold,
calculate_metrics_across_folds):
self.inner_cv = inner_cv
self.outer_cv = outer_cv
self.eval_final_performance = eval_final_performance
self.test_size = test_size
self.calculate_metrics_per_fold = calculate_metrics_per_fold
self.calculate_metrics_across_folds =
calculate_metrics_across_folds
self.outer_folds = None
self.inner_folds = dict()Example #6 Output=>
6, =>
from dataclasses import dataclass
@dataclass
class CrossValidation:
inner_cv: int
outer_cv: int
eval_final_performance: bool = True
test_size: float = 0.2
calculate_metrics_per_fold: bool = True
calculate_metrics_across_folds: bool = False
Note:(Example #6) As any signature, keyword arguments fields with default values must be declared last.
Note:(Example #6) class CrossValidation: Readability has increased substantially by using @dataclass and type hinting.
### Example #7
cv1 = CrossValidation()
7, =>
TypeError: __init__() missing 2 required positional arguments: 'inner_cv' and 'outer_cv'
Note:(Example #7) inner_cv and outer_cv are positional arguments. With any signature, you declare a non-default field after a default one. (Hint: If this were allowed, inheritance from a parent class breaks.)((Why? Goggle interview question #666.))
### Example #8
cv1 = CrossValidation(1,2)
cv2 = CrossValidation(1,2)
cv3 = CrossValidation(3,2,test_size=0.5)
print(cv1)
cv3
8, =>
CrossValidation(inner_cv=1, outer_cv=2, eval_final_performance=True, test_size=0.2, calculate_metrics_per_fold=True, calculate_metrics_across_folds=False)
CrossValidation(inner_cv=3, outer_cv=2, eval_final_performance=True, test_size=0.5, calculate_metrics_per_fold=True, calculate_metrics_across_folds=False)
### Example #9
cv1 == cv2
9, =>
True
### Example #10
cv1 == cv3
10, =>
False
### Example #11
from inspect import signature
print(signature(cv3.__init__))
cv3
11, =>
(inner_cv: int, outer_cv: int, eval_final_performance: bool = True, test_size: float = 0.2, calculate_metrics_per_fold: bool = True, calculate_metrics_across_folds: bool = False) -> None
CrossValidation(inner_cv=3, outer_cv=2, eval_final_performance=True, test_size=0.5, calculate_metrics_per_fold=True, calculate_metrics_across_folds=False)
Note: (Example #11) The inspect function shows the signature of the class object while the__str__ default shows the instance state variables and their values.
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self.outer_folds = None
self.inner_folds = dict()
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CrossValidation
:
### Example 12
from dataclasses import dataclass
@dataclass
class CrossValidation:
inner_cv: int
outer_cv: int
eval_final_performance: bool = True
test_size: float = 0.2
calculate_metrics_per_fold: bool = True
calculate_metrics_across_folds: bool = False
def __post_init__(self):
self.outer_folds = None
self.inner_folds = dict()
@dataclass
:
https://realpython.com/python-data-classes/
https://blog.usejournal.com/new-buzzword-in-python-is-here-dataclasses-843dd1d372a5
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«Python Developer. Basic».
« : map(), filter() zip()».