SET UP
installation: using the following command pip install django-crontab
add it to installed apps in django settings.py:
INSTALLED_APPS = (
‘django_crontab’,
…
)
now create a new method that should be executed by cron every 5 minutes, f.e. in myapp/cron.py:
def cron()
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
dataset = pd.read_csv('myapp/data/KBfinal.csv')
y = dataset.iloc[:, [1]].values
y1 = dataset.iloc[:, [2]].values
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
corpus = []
for i in range(0,len(dataset)):
c1=[]
review = re.sub('[^a-zA-Z]', ' ', str(dataset['0'][i]))
review = review.lower()
review = review.split()
ps = PorterStemmer()
review = [word for word in review if not word in set(stopwords.words('english'))]
review = ' '.join(review)
corpus.append(review)
from sklearn.feature_extraction.text import TfidfVectorizer,CountVectorizer
vectorizer = TfidfVectorizer(stop_words='english')
X = vectorizer.fit_transform(corpus)
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state = 0)
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier(n_estimators = 25, criterion = 'entropy', random_state = 0)
classifier.fit(X, y.ravel())
print('MACHINE LEARNING SUCESSFULLLL')
import pickle
pickl = {
'vectorizer': vectorizer,
'classifier': classifier,
}
pickle.dump( pickl, open( 'myapp/model/models1' + ".p", "wb" ) )
with open('myapp/model/parrot.pkl', 'wb') as f:
pickle.dump(corpus, f)
with open('myapp/model/y.pkl', 'wb') as ff:
pickle.dump(y, ff)
with open('myapp/model/y1.pkl', 'wb') as fff:
pickle.dump(y1, fff)
now add this to your settings.py:
CRONJOBS = (‘*/5 * * * *’, ‘myapp.cron.cron’)