Skip to main content

PhpStorm and AngularJS

As the IDE for coding I use Phpstorm 8. The reasons are its quite easy to handle. But I thought it would be great that if it can provide auto-complete AngularJS tags and JavaScript etc. With that when I look into a solution it was a simple thing to do. Simple as Just install the plugin. You can do that by going to file>settings or Ctrl+Alt+S Then you'll get a settings window. This will show a tab named plugins. 

Then in there click the install jetBrains plugin plugins and choose AngularJS then install it. After that Restart the browser and tadaa you are good to go.


Labels

Labels:
Location: Sri Jayawardenepura Kotte, Sri Lanka

Popular posts from this blog

Natural Language Processing with Python NLTK part 5 - Chunking and Chinking

Natural Language Processing Using regular expression modifiers we can chunk out the PoS tagged words from the earlier example. The chunking is done with regular expressions defining a chunk rule. The Chinking defines what we need to exclude from the selection. Here are list of modifiers for Python: {1,3} = for digits, u expect 1-3 counts of digits, or "places" + = match 1 or more ? = match 0 or 1 repetitions. * = match 0 or MORE repetitions $ = matches at the end of string ^ = matches start of a string | = matches either/or. Example x|y = will match either x or y [] = range, or "variance" {x} = expect to see this amount of the preceding code. {x,y} = expect to see this x-y amounts of the preceding code source: https://pythonprogramming.net/regular-expressions-regex-tutorial-python-3/ Chunking import nltk from nltk.tokenize import word_tokenize # POS tagging sent = "This will be chunked. This is for Test. World is awesome. Hello world....
Read more

Natural Language Processing with Python NLTK part 2 - Stop Words

Natural Language Processing Stop words are the words which we ignore due to the fact that they do not generate any specific meaning to the sentence. Words like the, is, at etc. can be removed to extract the meaning of the sentence more easily. So NLTK has introduced us a stop words filter we can easily use. Let's see how it works. from nltk.corpus import stopwords from nltk.tokenize import word_tokenize sent = "As you can see this is the blog of myself which is written by Anjula" w = word_tokenize(sent) # set English stop words stop_words = set(stopwords . words( 'english' )) # list of standard stop words in English print (stop_words) # making empty arrays to store stop words and others stop_words_in_sent = [] non_stop_words = [] # Loop through to get the stop words for x in w: if x not in stop_words: non_stop_words . append(x) else : stop_words_in_sent . append(x) # print result ...
Read more

Natural Language Processing with Python NLTK part 4 - PoS tagging

Natural Language Processing  PoS tagging or Part of Speech tagging is a commonly used mechanism. This will allow NLTK to tag the words that is in your corpus and give the tags accordingly. There are many tags predefined by the NLTK and here are the list. Number Tag Description 1. CC Coordinating conjunction 2. CD Cardinal number 3. DT Determiner 4. EX Existential  there 5. FW Foreign word 6. IN Preposition or subordinating conjunction 7. JJ Adjective 8. JJR Adjective, comparative 9. JJS Adjective, superlative 10. LS List item marker 11. MD Modal 12. NN Noun, singular or mass 13. NNS Noun, plural 14. NNP Proper noun, singular 15. NNPS Proper noun, plural 16. PDT Predeterminer 17. POS Possessive ending 18. PRP Personal pronoun 19. PRP$ Possessive pronoun 20. RB Adverb 21. RBR Adverb, comparative 22. RBS ...
Read more