docker-python/test_build.py at master · Slyderek/docker-python · GitHub

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# This script should run without errors whenever we update the

# kaggle/python container. It checks that all our most popular packages can

# be loaded and used without errors.

import numpy as np

print("Numpy imported ok")

print("Your lucky number is: " + str(np.random.randint(100)))

import pandas as pd

print("Pandas imported ok")

from sklearn import datasets

print("sklearn imported ok")

iris = datasets.load_iris()

X, y = iris.data, iris.target

from sklearn.ensemble import RandomForestClassifier

rf1 = RandomForestClassifier()

rf1.fit(X,y)

print("sklearn RandomForestClassifier: ok")

from sklearn.linear_model import LinearRegression

boston = datasets.load_boston()

X, y = boston.data, boston.target

lr1 = LinearRegression()

lr1.fit(X,y)

print("sklearn LinearRegression: ok")

from xgboost import XGBClassifier

xgb1 = XGBClassifier(n_estimators=3)

xgb1.fit(X[0:70],y[0:70])

print("xgboost XGBClassifier: ok")

import matplotlib.pyplot as plt

plt.plot(np.linspace(0,1,50), np.random.rand(50))

plt.savefig("plot1.png")

print("matplotlib.pyplot ok")

from mpl_toolkits.basemap import Basemap

print("Basemap ok")

import plotly.plotly as py

import plotly.graph_objs as go

print("plotly ok")

from ggplot import *

print("ggplot ok")

import theano

print("Theano ok")

from keras.models import Sequential

from keras.layers.core import Dense, Dropout, Activation, Flatten

from keras.layers.convolutional import Convolution2D, MaxPooling2D

from keras.optimizers import SGD

print("keras ok")

import nltk

from nltk.stem import WordNetLemmatizer

print("nltk ok")

import tensorflow as tf

hello = tf.constant('TensorFlow ok')

sess = tf.Session()

print(sess.run(hello))

import cv2

img = cv2.imread('plot1.png',0)

print("OpenCV ok")

from skimage.io import imread

print("skimage ok")

docker-python/test_build.py at master · Slyderek/docker-python · GitHub

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