- #Boa vs python difference appearance movie
- #Boa vs python difference appearance generator
- #Boa vs python difference appearance full
- #Boa vs python difference appearance series
But remember that anacondas are heavier and bulkier while pythons are longer and more agile. The python, on the other hand, constricts and crushes animals before eating them. The anaconda bites its prey and drowns the poor creature in the water. That is why it can ambush hapless mammals and birds at night. Meanwhile, the python loves to perch on trees and stay on drier land. This allows the snake to see preys while submerged in the water. The anaconda’s eyes are located on top of its head. This giant snake loves to eat mammals and birds only.Īnaconda is aquatic and lives in marshes, swamps, and rivers. The python however is a bit choosy with its choice of food. In fact, some anacondas can overpower a crocodile and eat it whole. As long as the prey can be overpowered, then it is included in the anaconda menu. However, a 20-foot anaconda will outweigh a much longer python. In contrast, the python can grow as long as 33 feet or more. An anaconda can weigh as much as 550 pounds or more and can grow up to 25 feet. On the other hand, the python is no doubt the longest snake in the world. It prowls the thick and dense forest of South Asia, South East Asia, and Sub-Saharan Africa.Īnaconda is the heaviest and the biggest snake in the world. A python belongs to the family Pythonidae. However, anacondas and pythons belong to two different families of snake.Īnacondas belong to the boa family and are found in South America and the Amazon basin. Some people think that anaconda and python are one and the same.
#Boa vs python difference appearance full
The full script is here.Pythons and Anacondas are no doubt the greatest snakes in the world. We then sort the words by their scores and output the top 3 words. format ( word, round ( score, 5 )))įor each document, we store the TF-IDF scores in a dictionary scores mapping word => score using a dict comprehension. Hogg, Chuck Hawks, Leroy Thompson, Renee Smeets and Martin Dougherty have described the Python as the finest production revolver ever made.""" ) bloblist = for i, blob in enumerate ( bloblist ): print ( "Top words in document ". Some firearm collectors and writers such as Jeff Cooper, Ian V. The now discontinued Colt Python targeted the premium revolver market segment. It was first introduced in 1955, the same year as Smith & Wesson's M29. It is sometimes referred to as a "Combat Magnum".
357 Magnum caliber revolver formerly manufactured by Colt's Manufacturing Company of Hartford, Connecticut. reticulatus, is among the longest snakes known.""" ) document3 = tb ( """The Colt Python is a. Python (2004), both also made-for-TV films.""" ) document2 = tb ( """Python, from the Greek word (πύθων/πύθωνας), is a genus of nonvenomous pythons found in Africa and Asia. Python was followed by two sequels: Python II (2002) and Boa vs. It was filmed in Los Angeles, California and Malibu, California. It includes the classic final girl scenario evident in films like Friday the 13th. The film concerns a genetically engineered snake, a python, that escapes and unleashes itself on a small town.
#Boa vs python difference appearance series
The film features several cult favorite actors, including William Zabka of The Karate Kid fame, Wil Wheaton, Casper Van Dien, Jenny McCarthy, Keith Coogan, Robert Englund (best known for his role as Freddy Krueger in the A Nightmare on Elm Street series of films), Dana Barron, David Bowe, and Sean Whalen.
#Boa vs python difference appearance movie
Now to test it out on some real documents taken from Wikipedia.ĭocument1 = tb ( """Python is a 2000 made-for-TV horror movie directed by Richard Clabaugh. tfidf(word, blob, bloblist) computes the TF-IDF score.Add 1 to the divisor to prevent division by zero. We take the ratio of the total number of documents to the number of documents containing word, then take the log of that. The more common a word is, the lower its idf. idf(word, bloblist) computes "inverse document frequency" which measures how common a word is among all documents in bloblist.
#Boa vs python difference appearance generator
A generator expression is passed to the sum() function. n_containing(word, bloblist) returns the number of documents containing word.We use TextBlob for breaking up the text into words and getting the word counts. tf(word, blob) computes "term frequency" which is the number of times a word appears in a document blob, normalized by dividing by the total number of words in blob.log ( len ( bloblist ) / ( 1 + n_containing ( word, bloblist ))) def tfidf ( word, blob, bloblist ): return tf ( word, blob ) * idf ( word, bloblist ) words ) def idf ( word, bloblist ): return math.
words ) def n_containing ( word, bloblist ): return sum ( 1 for blob in bloblist if word in blob. Import math from textblob import TextBlob as tb def tf ( word, blob ): return blob.
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