multipliers = 
for i in range(5):
return i * x
for multiplier in create_multipliers():
return [lambda x : i * x for i in range(5)]
for multiplier in create_multipliers_lambda():
return [lambda x, i=i : i * x for i in range(5)]
for multiplier in create_multipliers_fix():
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it’s not a perfect language, but it’s the one in the lead position and continuously approaching and being the most complete, feature rich and thoughtful language, suitable for most large entreprise grade build out and even with future support, expansion and scaling lookout in mind.
python is growing popular, personally, mainly due to it’s lower entry barrier. however, the lower entry is in existence partially due to it has historically (“not yet”) never been extremly cautiously designed.
while a lot mature languages has a big community/collective intelligence to form the princeples/guidance before the features/design/establish of implemetations, which secured a robust/stable/scablable language and ecosystem, python is not born nor in existance like that.
it’s easy to start with, but not equally means good to start building on. just a persoanl thought at the momoent.
a peek of the depency mangement state alone(with only two versions of the python at the moment):
(i am happy to build on and with python, however, just 2 cents, it’s not yet ready for all entreprise.)
Have tried to build an AI bot since almost 3 years back, finally did a prototype, in case anybody would like to do something similar:
Java, Spring Boot, Spring, SQLlite, PostGre, Scala, Python, Anaconda, Scikit Learn, EWS, BootStrap, AngularJS/JQuery/HTML/CSS, Symphony API, Cisco API,
- I have built a scala web crawler, to download all historical support issues.
- at the same time, have manually cleaned up/read through each of the thousand of support issues, put in corresponding resolutions corresponding to each
- have leveraged on anaconda & scikit learn, to NLP, to tokenize each support issue (text), remove stop words, stemmed each, remove punctuations
- have leveraged on anaconda & scikit learn, bag each token of the text as feature vs class, to feed into linear regression classifier, tried SLDA, so far working at 72% accuracy
- have exposed AI as a service
- have leveraged EWS to read in all issues, post to AI service
- have built a web user interface, on top of HTML5 + JQuery + Bootstrap, to show the support emails + AI responded resolutions
- have a option on UI, to provide user feedback to AI, to keep its intelligence updated
- leverage on Java Mail API, EWS, Chat API, phone API, to post alerts for critical issues