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Subtext-0.0.2


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توضیحات

A package to make NLP easy, fast, and fun
ویژگی مقدار
سیستم عامل OS Independent
نام فایل Subtext-0.0.2
نام Subtext
نسخه کتابخانه 0.0.2
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Hyeonwook Kang
ایمیل نویسنده -
آدرس صفحه اصلی -
آدرس اینترنتی https://pypi.org/project/Subtext/
مجوز -
# Subtext 0.0.2 A package to make NLP fast and easy for beginners. - Efficient text prediction - Text pairing, equivalent to that of **NLTK**'s n-gram. - Syllable Identification - Find frequencies of words in given text - Find matching words in two arrays I still have a lot of plans for this package, for that reason, there would be a lot of frequent updates in the near future. The updates would include optimizations & more functions, so stay tuned. ## Install ``` pip install subtext ``` # Usage First import the program using: ```python import subtext ``` ## Predict A function that predicts the next x number of words based on the given string and phrase ### Parameters The function's parameters are: ```python subtext.predict(string, phrase, n=0, case_insensitive=False) ``` * **String**: Main text * **Phrase**: The key phrase (prompt). The function would try to predict what would come after the given phrase. * **n**: The number of words it would return. It's automomatically set to 0, which would return all predictions regardless of their corresponding word counts. * **case_insensitive**: Set this to ```True``` if you want to. ### Actual usage So, let's try to use this. ```python string="I am a string. I am also a human being, but most importantly, I am a string." print(predict(string, "I am", n=1)) ``` This would output ``` {'a': 2, 'also': 1} ``` But, if you change the ```n``` value, ```python print(predict(string, "I am", n=2)) ``` It would output ``` {'a string.': 2, 'also a': 1} ``` ## Pair This function splits a string into pairs of strings. ### Parameters ```python subtext.pair(string, n) ``` - **string** is the string you're trying to split into pairs - **n** stands for the number of strings in each pair. (Equivalent to that of the ```n``` value in n-gram) ### Usage Let's set our string to: ```python string="Sometimes, I just go out and eat sand. I don't know why" ``` Don't ask. Let's turn this into pairs of 2: ```python print(pair(string, 2)) ``` Which outputs ``` [['Sometimes,', 'I'], ['I', 'just'], ['just', 'go'], ['go', 'out'], ['out', 'and'], ['and', 'eat'], ['eat', 'sand.'], ['sand.', 'I'], ['I', "don't"], ["don't", 'know'], ['know', 'why']] ``` ## Identify Syllables ```python subtext.syllables("carbonmonoxide") ``` This outputs: ```python car-bon-mon-ox-ide ``` But take note that this only works with lowercase strings. ## Countwords ### Parameters The function's parameters are: ```python subtext.countwords(string, case_insensitive=False) ``` Change that to ```True``` if you want it to be case-insensitive. ### Actual usage Get yourself a nice string ```python string = "Sometimes I wonder, 'Am I stupid?' then I realize, yeah. yeah, I am stupid." ``` Then put it in the function: ```python x = subtext.countwords(string) print(x) ``` It should print: ``` {'I': 4, 'Sometimes': 1, 'wonder,': 1, "'Am": 1, "stupid?'": 1, 'then': 1, 'realize,': 1, 'yeah.': 1, 'yeah,': 1, 'am': 1, 'stupid.': 1} ``` ## Matchingwords A function that finds & counts matching words in two strings ### Actual usage So in this case, our strings are: ```python string1, string2 = "God, I love drawing, drawing is my favourite thing to do", "God, I hate drawing, drawing is my least favourite thing to do" ``` If we run this through matchingwords, we would get: ``` {'God,': 1, 'I': 1, 'drawing,': 1, 'drawing': 1, 'is': 1, 'my': 1, 'favourite': 1, 'thing': 1, 'to': 1, 'do': 1} ```


زبان مورد نیاز

مقدار نام
>=3.6 Python


نحوه نصب


نصب پکیج whl Subtext-0.0.2:

    pip install Subtext-0.0.2.whl


نصب پکیج tar.gz Subtext-0.0.2:

    pip install Subtext-0.0.2.tar.gz