jobbert_knowledge_extraction / create_sample_skills.py
Aqsa-K
embedding and graphs added
f8da2f0
raw
history blame
1.22 kB
# Generating sample folder structure and files with multiple skills per file
import os
# Base folder for the structure
base_folder = "tags"
# Sample data: dates and skills for each date
sample_dates = ["03-01-2024", "04-01-2024", "05-01-2024"]
sample_skills = {
"03-01-2024": [
["Python", "Machine Learning", "Data Analysis"],
["Python", "Deep Learning"],
["Data Science", "AI"]
],
"04-01-2024": [
["Python", "AI", "Data Analysis"],
["Deep Learning", "Machine Learning"],
["AI", "Data Engineering"]
],
"05-01-2024": [
["AI", "Machine Learning", "Python"],
["Data Science", "Deep Learning"],
["Python", "AI", "Cloud Computing"]
]
}
# Create the folder structure and files
for date in sample_dates:
date_folder = os.path.join(base_folder, date)
os.makedirs(date_folder, exist_ok=True)
for i, skills in enumerate(sample_skills[date], start=1):
file_path = os.path.join(date_folder, f"{i}.txt")
with open(file_path, "w", encoding="utf-8") as f:
f.write("\n".join(skills))
print(f"Sample files with multiple skills per file have been generated in the '{base_folder}' folder.")