def test_get_stopwords_norwegian():
# arrange - get stopwords outwith function
stops_nb_direct = list(STOP_WORDS_NB)
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, _ = get_stopwords()
# assert
assert stops_nb_direct == stopwords_nb_func
def test_get_stopwords_english():
# arrange - get stopwords outwith function
stops_en_direct = list(STOP_WORDS_EN)
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, stopwords_en_func = get_stopwords()
# assert
assert stops_en_direct == stopwords_en_func
def test_get_stopwords_english():
# arrange - get stopwords outwith function
from spacy.lang.en.stop_words import STOP_WORDS
stops_en_direct = list(STOP_WORDS)
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, stopwords_en_func = get_stopwords()
# assert
assert stops_en_direct == stopwords_en_func
def test_get_stopwords_full():
# arrange - get stopwords outwith function
stops_en_direct = list(STOP_WORDS_EN)
stops_nb_direct = list(STOP_WORDS_NB)
stopwords = stops_en_direct + stops_nb_direct
stopwords_direct = [str(i) for i in stopwords]
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, _ = get_stopwords()
# assert
assert stopwords_direct == stopwords_func
def test_get_stopwords_full():
# arrange - get stopwords outwith function
from spacy.lang.en.stop_words import STOP_WORDS
stops_en_direct = list(STOP_WORDS)
from spacy.lang.nb.stop_words import STOP_WORDS
stops_nb_direct = list(STOP_WORDS)
stopwords = stops_en_direct + stops_nb_direct
stopwords_direct = [str(i) for i in stopwords]
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, _ = get_stopwords()
# assert
assert stopwords_direct == stopwords_func
def test_keyphrase_extraction():
# arange
example_text = './examples/example_data/en_historynlp.txt'
with open(example_text, "r") as file:
text = file.read()
all_stopwords, stopwords_nb, stopwords_en = stdt.get_stopwords()
# act
keyphrases = kw.keyphrase_list(
text,
stopwords=stopwords_en,
with_scores=False,
)
# assert
assert keyphrases[0] == "word embeddings"
NOTE: This is an example to show how to run the procedure however due to the small dataset used
the results are likely to be non-sensical.
"""
import enlp.understanding.topics as tp
import enlp.processing.stdtools as stdt
import spacy
###############################################################################
# Load example text and get stopwords
with open("example_data/en_nlptexts.txt", "r") as file:
text=file.read()
all_stopwords, stopwords_nb, stopwords_en = stdt.get_stopwords()
###############################################################################
# Preprocess text - for this example we have a very small corpus to allow the documentation
# to build therefore we will split the single document into paragraphs for processing to
# imitate multiple document input and we will also remove stopwords and punctuation as the text is too small.
# Split text into paragraphs to imitate documents
docs = text.split('\n\n')
# Remove \n and replace with space
docs = [d.replace('\n',' ') for d in docs]
# Because example text is small, remove stopwords and punctuation
en = spacy.load('en_core_web_md')
stopwords, stops_nb, stops_en = stdt.get_stopwords()
"""
Removing Stopwords
==================
XXX
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as pltgs
from enlp.processing.stdtools import get_stopwords
plt.close(
'all'
) # very important for read the docs to avoid it crashing due to memory
###############################################################################
# Some text
# act - get functions idea of stopwords
stopwords_func, stopwords_nb_func, stopwords_en_func = get_stopwords()
print(stopwords_en_func[:5])
"""
Keyphrase Extraction (English)
==============================
The following example uses a python implementation of the Rapid Automatic Keyword Extraction algorithm to extract
keyphrases from a text.
"""
import pandas as pd
from enlp.processing.stdtools import get_stopwords
from enlp.understanding.keywords import keyphrase_list
###############################################################################
# Load example text and get stopwords
with open("example_data/en_historynlp.txt", "r") as file:
text = file.read()
all_stopwords, stopwords_nb, stopwords_en = get_stopwords()
###############################################################################
# Extract keyphrases
keyphrases = keyphrase_list(
text,
stopwords=stopwords_en,
)
print(pd.DataFrame(keyphrases, columns=['score', 'keyphrase']).head(10))
def all_stopwords():
stopwords, stops_nb, stops_en = get_stopwords()
return stopwords
def norwegian_stopwords():
stopwords, stops_nb, stops_en = get_stopwords()
return stops_nb
def english_stopwords():
stopwords, stops_nb, stops_en = get_stopwords()
return stops_en