Model/model_data/utils.py
2023-09-05 16:33:50 +01:00

49 lines
1.4 KiB
Python

import boto3
import pandas as pd
from io import BytesIO
import re
from textblob import TextBlob
# Pre-compile the regular expression
PERCENTAGE_PATTERN = re.compile(r'^\d+%?$')
def is_percentage_or_number(s):
# re.match returns None if the string does not match the pattern
return PERCENTAGE_PATTERN.match(s) is not None
def correct_spelling(text):
words = text.split()
corrected_words = []
for word in words:
if is_percentage_or_number(word):
corrected_words.append(word)
else:
blob = TextBlob(word) # create a TextBlob object
corrected_word = blob.correct() # use the correct method to correct spelling
corrected_words.append(str(corrected_word)) # convert corrected word back to string
corrected_text = ' '.join(corrected_words)
return corrected_text
def save_dataframe_to_s3_parquet(df, bucket_name, file_key):
"""
Save a pandas DataFrame to S3 as a Parquet file.
:param df: The pandas DataFrame.
:param bucket_name: Name of the S3 bucket.
:param file_key: Key of the file (including directory path within the bucket).
"""
# Convert the DataFrame to a Parquet format in memory
parquet_buffer = BytesIO()
df.to_parquet(parquet_buffer)
# Create the boto3 client
client = boto3.client('s3')
# Upload the Parquet file to S3
client.put_object(Bucket=bucket_name, Key=file_key, Body=parquet_buffer.getvalue())