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docker-python/test_build.py at master · Atlas7/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
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
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"
)
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