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new: [lemmatized/verbatim] displaying verbatim or lemmatized version is now an option
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2 changed files with 17 additions and 5 deletions
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@ -13,6 +13,8 @@ Analysis features are :
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- Mention frequency (everything prefixed with an @ symbol)
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- Out-Of-Vocabulary (OOV) word frequency meaning any words outside English dictionary
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Verbs and nouns are in their lemmatized form by default but the option `--verbatim` allows to keep the original inflection.
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# requirements
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- Python >= 3.6
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@ -22,7 +24,7 @@ Analysis features are :
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# how to use napkin
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~~~~
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usage: napkin.py [-h] [-v V] [-f F] [-t T] [-s] [-o O]
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usage: napkin.py [-h] [-v V] [-f F] [-t T] [-s] [-o O] [-l L] [--verbatim]
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Extract statistical analysis of text
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@ -32,7 +34,10 @@ optional arguments:
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-f F file to analyse
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-t T maximum value for the top list (default is 100) -1 is no limit
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-s display the overall statistics (default is False)
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-o O output format (default is csv)
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-o O output format (default is csv), json
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-l L language used for the analysis (default is en)
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--verbatim Don't use the lemmatized form, use verbatim. (default is the
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lematized form)
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~~~~
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# example usage of napkin
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@ -14,7 +14,8 @@ parser.add_argument('-f', help="file to analyse")
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parser.add_argument('-t', help="maximum value for the top list (default is 100) -1 is no limit", default=100)
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parser.add_argument('-s', help="display the overall statistics (default is False)", default=False, action='store_true')
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parser.add_argument('-o', help="output format (default is csv), json", default="csv")
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parser.add_argument("-l", help="language used for the analysis (default is en)", default="en")
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parser.add_argument('-l', help="language used for the analysis (default is en)", default="en")
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parser.add_argument('--verbatim', help="Don't use the lemmatized form, use verbatim. (default is the lematized form)", default=False, action='store_true')
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args = parser.parse_args()
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if args.f is None:
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@ -51,11 +52,17 @@ redisdb.hset("stats", "token", doc.__len__())
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for token in doc:
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if token.pos_ == "VERB" and not token.is_oov:
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redisdb.zincrby("verb:napkin", 1, token.lemma_)
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if not args.verbatim:
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redisdb.zincrby("verb:napkin", 1, token.lemma_)
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else:
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redisdb.zincrby("verb:napkin", 1, token.text)
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redisdb.hincrby("stats", "verb:napkin", 1)
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continue
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if token.pos_ == "NOUN" and not token.is_oov:
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redisdb.zincrby("noun:napkin", 1, token.lemma_)
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if not args.verbatim:
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redisdb.zincrby("noun:napkin", 1, token.lemma_)
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else:
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redisdb.zincrby("noun:napkin", 1, token.text)
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redisdb.hincrby("stats", "noun:napkin", 1)
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continue
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