Teamwork project with v-nafise
At first the app needs to extract storyline text of movies via web crawlling using :
- BeautifulSoap
- RegEx
Then analysing and extracting the keywords of the prepared text through TextRank algorithm + text proccessing like tokenizing, deleting stopwords and lemmatizing are implemented on story-line text of each movie
After that trying to find the common keywords employed on each movie's storyline text And to show the result by a weighted graph in which the weight refers to the number of common keywords and the nodes are movies, using :
- Netwokrx
Finally the weighted graph is stored in a csv file.
output example of 250 movie's common words computed graph:
A Python program scraping the special offers of products and showing the results in a web using django framework
technologies used in this app are:
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craping with BeautifulSoup library
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using regex for extracting exact details
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saving files into json and csv format file
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using django fixtures for populating database with the data derived from previous steps