🧑‍💻 Solution on Python that allows parsing and sorting of resumes from popular job websites.

🗃️ Installation

1. Clone the repository:

   git clone https://github.com/AlexTkDev/resume_parsing.git
   cd resume_parsing

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # For Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

1. Script for Parsing Resumes from robota.ua

Description: This script parses resumes from the robota.ua website. Selenium is used to automate the Chrome browser, which runs in headless mode (without displaying the GUI). The script iterates through resume pages and saves the data into a JSON file.

Key Functions:

• setup_selenium(): Configures the Selenium WebDriver to work with Chrome in headless mode.
• fetch_resumes(url, driver): Opens the page at the given URL, locates the resume elements, and extracts information such as title, link, name, details, and publication time.
• save_to_json(data, filename): Saves the data into a JSON file. If the file already exists, the data is appended to it.
• main(pages, skill): The main function that manages the parsing process. It iterates through the specified pages, extracts resumes, and saves them to the resumes_robota_ua.json file.

Example Execution:

  python robota_ua/get_resume.py --pages 2 --skill python

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2. Script for Parsing Resumes from work.ua

Description: This script is designed to parse resumes from the work.ua website using the BeautifulSoup library for HTML parsing. The script extracts resume information and saves it into a JSON file.

Key Functions:

• fetch_resumes(url): Sends an HTTP request to the resume page and extracts information such as title, link, name, details, and publication time.
• save_to_json(data, filename): Saves the data into a JSON file. If the file already exists, the data is appended to it.
• main(pages, skill): The main function that iterates through the specified pages, extracts resumes, and saves them to the resumes_work_ua.json file.

Example Execution:

  python work_ua/get_resume.py --pages 2 --skill python

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3. Script for Fetching HTML Pages Using Selenium

Description: This script is used to load the HTML content of a web page using Selenium and save it to a file. It is suitable for situations where you need to obtain the full HTML of a page, including dynamically loaded elements.

Key Functions:

• get_data_by_selenium(url): Opens the page at the given URL using Selenium WebDriver, waits for all elements to load, and returns the HTML content of the page.
• save_html_to_file(html_content, file_path): Saves the provided HTML content to the specified file.

Example Execution:

    url = "https://robota.ua/candidates/all/ukraine"
    html_data = get_data_by_selenium(url)
    save_html_to_file(html_data, "page_content.html")
    print("HTML saved to 'page_content.html'")

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4. Script for Parsing and Saving Resumes from work.ua by Links in JSON File

Description: This script extracts resume data from URLs listed in a JSON file, formats it, and saves it to text files. It uses the requests library to perform HTTP requests and BeautifulSoup to parse the HTML content of the resume pages. Each resume is saved as a .txt file in a designated directory.

Key Functions:

• get_user_links(file): Extracts all values of the 'link' key from the provided JSON file.
• clean_text(text): Cleans the text by removing unnecessary spaces and newline characters.
• get_separate_resume(url): Sends an HTTP request to the resume page URL, extracts and formats the resume data such as title, name, and details.
• save_to_txt(data, filename): Saves the extracted resume data to a text file.
• main(file): The main function that processes each link extracted from the JSON file. It creates a directory for saving resumes (if it doesn't already exist) and saves each resume in a .txt file named using the user ID extracted from the URL.

Example of running the script:

  python work_ua/get_separate_resume.py --file resumes_work_ua.json

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5. Script for Parsing Resumes from robota.ua Using Selenium

Description: This script extracts resume data from robota.ua using Selenium. It reads candidate links and names from a JSON file, navigates to each resume page, and extracts information such as experience, skills, education, and languages. The extracted data is saved in a text file.

Key Functions:

• setup_selenium(): Configures the Selenium WebDriver to use Chrome in headless mode.
• get_user_data(file): Extracts candidate links and names from a JSON file.
• clean_text(text): Cleans text by removing unnecessary spaces and newline characters.
• get_separate_resume(driver, url): Extracts resume information from the given URL using Selenium, including experience, skills, education, and languages.
• save_to_txt(data, filename): Saves the extracted resume data to a text file.
• main(file): The main function that processes the JSON file with candidate data, extracts resumes, and saves them to text files.

Example of running the script:

  python robota_ua/get_separate_resume.py --file resumes_robota_ua.json

Notes:

• The resumes_robota_ua.json file should contain the candidate links and names.
• The script saves the resumes in the ready-made_resumes directory, creating the directory if it doesn't exist.

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6. Resume Scoring and Sorting Script

Description: This script scores and sorts resumes saved in text files based on their content. It supports resumes from robota.ua and work.ua. The scoring is based on resume completeness, keywords, work experience, education, and additional criteria. The script sorts resumes by score in descending order and saves the results to a text file.

Key Functions:

• score_resume(resume_text): Scores the resume based on its content, including resume sections, keywords, work experience, education, and additional criteria.
• extract_experience_years(resume_text): Extracts the total number of years of experience from the resume text.
• load_resumes(resume_folder): Loads all resumes from the specified folder.
• sort_candidates_by_relevance(resumes): Sorts resumes by score in descending order based on the evaluation.
• main(resume_folder): The main function that loads resumes, scores and sorts them, and then saves the results to sorted_candidates.txt.

Example of running the script:

  python sorting_resume/sorting_resume.py --directory ready-made_resumes

Notes:

• The script expects resumes to be located in the folder specified by the --directory argument.
• Results will be saved in sorted_candidates.txt, containing the resume file name, score, and path to the resume.

7. Collaborate

• If you have any suggestions or improvements, please feel free to contribute.
• Fork this repository.
• Create a new branch with a meaningful name.
• Open a pull request.
• Your changes will be reviewed and merged.
• Thank you for your contribution!