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from io import StringIO | |
import core.pipelines as pipelines_functions | |
from inspect import getmembers, isfunction, signature | |
from newspaper import Article | |
from PyPDF2 import PdfFileReader | |
import streamlit as st | |
import pandas as pd | |
import pytesseract | |
from PIL import Image | |
def get_pipelines(): | |
pipeline_names, pipeline_funcs = list( | |
zip(*getmembers(pipelines_functions, isfunction)) | |
) | |
pipeline_names = [ | |
" ".join([n.capitalize() for n in name.split("_")]) for name in pipeline_names | |
] | |
pipeline_func_parameters = [ | |
{key: value.default for key, value in signature(pipe_func).parameters.items()} | |
for pipe_func in pipeline_funcs | |
] | |
return pipeline_names, pipeline_funcs, pipeline_func_parameters | |
def extract_text_from_url(url: str): | |
article = Article(url) | |
article.download() | |
article.parse() | |
return article.text | |
def extract_text_from_file(file): | |
# read text file | |
if file.type == "text/plain": | |
# To convert to a string based IO: | |
stringio = StringIO(file.getvalue().decode("utf-8")) | |
# To read file as string: | |
file_text = stringio.read() | |
return file_text | |
# read pdf file | |
elif file.type == "application/pdf": | |
pdfReader = PdfFileReader(file) | |
count = pdfReader.numPages | |
all_text = "" | |
for i in range(count): | |
try: | |
page = pdfReader.getPage(i) | |
all_text += page.extractText() | |
except: | |
continue | |
file_text = all_text | |
return file_text | |
# read csv file | |
elif file.type == "text/csv": | |
csv = pd.read_csv(file) | |
# get columns of type string | |
string_columns = csv.select_dtypes(include=["object"]).columns | |
# get data from columns and join it together | |
file_text = "" | |
for row in csv[string_columns].values.tolist(): | |
# remove NaNs | |
row = [x for x in row if str(x) != "nan"] | |
for column in row: | |
txt = "" | |
if isinstance(column, list): | |
try: | |
txt = " ".join(column) | |
except: | |
continue | |
elif isinstance(column, str): | |
txt = column | |
else: | |
continue | |
file_text += " " + txt | |
return file_text | |
# read image file (OCR) | |
elif file.type == "image/jpeg": | |
return pytesseract.image_to_string(Image.open(file)) | |
else: | |
st.warning(f"File type {file.type} not supported") | |
return None | |