Spaces:
Build error
Build error
File size: 2,616 Bytes
6db7601 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | import os
import re
import pickle
from datetime import datetime
import pandas as pd
def save_analysis_to_history(analysis_results, resume_data, job_role):
"""Save the current analysis results to history
Args:
analysis_results (dict): The analysis results from the Groq API
resume_data (dict): The resume data including filename and text
job_role (str): The target job role
Returns:
dict: The history entry that was created
"""
# Create a history entry
history_entry = {
"filename": resume_data["filename"],
"job_role": job_role,
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"ats_score": analysis_results["ats_score"],
"keyword_match": analysis_results["keyword_match"],
"format_score": analysis_results["format_score"],
"readability_score": analysis_results["readability_score"]
}
return history_entry
def format_timestamp(timestamp_str):
"""Format a timestamp string for display
Args:
timestamp_str (str): Timestamp string in format '%Y-%m-%d %H:%M:%S'
Returns:
str: Formatted timestamp for display
"""
try:
dt = datetime.strptime(timestamp_str, "%Y-%m-%d %H:%M:%S")
return dt.strftime("%b %d, %Y at %I:%M %p")
except:
return timestamp_str
def get_score_color(score):
"""Get a color based on a score value
Args:
score (int): Score value (0-100)
Returns:
str: Hex color code
"""
if score >= 80:
return "#4CAF50" # Green
elif score >= 60:
return "#FFC107" # Yellow/Amber
else:
return "#F44336" # Red
def clean_text(text):
"""Clean and normalize text for analysis
Args:
text (str): Raw text
Returns:
str: Cleaned text
"""
# Remove extra whitespace
text = re.sub(r'\s+', ' ', text).strip()
# Remove special characters that might interfere with analysis
text = re.sub(r'[^\w\s.,;:!?\-\(\)]', ' ', text)
return text
def export_analysis_to_csv(history_data, filename="resume_analysis_history.csv"):
"""Export analysis history to a CSV file
Args:
history_data (list): List of history entries
filename (str): Output filename
Returns:
str: Path to the saved file
"""
# Convert to DataFrame
df = pd.DataFrame(history_data)
# Save to CSV
output_path = os.path.join(os.getcwd(), filename)
df.to_csv(output_path, index=False)
return output_path |