FusionCV

Send a pdf to the api and get structered data for your CVs.

Usage

/parse Endpoint:

Subscribe and start parsing your CVs!

• Payload:
  
  You can either send the PDF via public link or through encoded string.
  • pdf_link (string): A valid public link or s3 path to the CV file (pdf or docx).
  • data_bytes (string): the extracted text from the PDF in base64 encoded bytes.
    • Example for the expected data ‘data_bytes’:

    import base64
    with open(cv_link, 'rb') as f:
        pdf = f.read()
    
    data_bytes = base64.b64encode(pdf).decode()
    

  • isbytes (boolean): True or False, is the PDF data is sent in base64 string (‘data_bytes’ parameter)

Example:

{
    "pdf_link": "https://drive.google.com/uc?export=download&id=1WvAVlrkahxdSA-fV-ajdFt-XHRb2GZ7R",
    "data_bytes": "",
    "isbytes": false
}

• Response::
  

  NOTE: a field is None if not found

  • status (string): ‘Success’ or ‘Error’
    • ‘Success’ if operations is done without error
    • ‘Error’ if an error is encountered
  • msg (string): message showing the error in case of error
    • Empty string in case of Success
  • data (dictionary): The output in case of Success operation, empty dict in case of error
    Output Structure:
    • name (string): name of the applicant
    • objective (string): objective written by the applicant if found
    • summary (string): objective written by the applicant if found
    • profession (string): the applicant’s job title
    • total_years_experience (integer): an integer of the total number of years of work experience
    • skills (list of strings): list of hard and soft skills found in the CV
    • work_experience (list of dictionaries): holds work experience/s found in the CV
      Keys of a single work experience dictionary:
      • workplace (string): name of place of work
      • startDate (dictionary): start date of the job
      • endDate (float): end date of the job
      • jobTitle (float): the applicant role or job title
      • jobDescription (float): description of the job responsibilities
    • location_country (string): country location found in the CV
    • location_state (string): state location found in the CV
    • education_level (string): highest education degree
    • education (string): field of education
    • education_organization (string): name of university/institute…etc.
    • education_grade (string): grade acheived
    • certifications (list of strings): list of certificates and courses
    • publications (list of strings): list of published research papers
    • websites (list of strings): list of any provided links in the CV
    • e-mail (list of strings): list of provided emails
    • linkedin (string): linkedin account if found in the CV
    • languages (list of strings): list of languages provided by the applicant
    • phone_numbers (list of strings): list of phone numbers found in the CV

Example:

{
    "status": "Success",
    "data": {
        "name": "Jason Miller",
        "objective": null,
        "summary": "Experienced Amazon Associate with five years’ tenure in a shipping yard setting, maintaining an average picking/packing speed of 98%. Holds a zero error% score in adhering to packing specs and 97% error-free ratio on packing records. Completed a certificate in Warehouse Sanitation and has a valid commercial driver’s license.",
        "profession": "Amazon Associate",
        "total_years_experience": 5,
        "skills": [
            "Packing",
            "Picking",
            "Counting",
            "Record keeping",
            "Warehouse Sanitation",
            "Inventory management",
            "Cleaning equipment"
        ],
        "work_experience": [
            {
                "workplace": "Amazon",
                "startDate": "2021-01-01",
                "endDate": "2022-07-01",
                "jobTitle": "Amazon Warehouse Associate",
                "jobDescription": "Performed all warehouse laborer duties such as packing, picking, counting, record keeping, and maintaining a clean area. Consistently maintained picking/packing speeds in the 98th percentile. Picked all orders with 100% accuracy despite high speeds. Maintained a clean work area, meeting 97.5% of the inspection requirements."
            },
            {
                "workplace": "Dunrea Laboratories",
                "startDate": "2019-01-01",
                "endDate": "2020-12-01",
                "jobTitle": "Laboratory Inventory Assistant",
                "jobDescription": "Full-time lab assistant in a small, regional laboratory tasked with participating in Kaizen Events, Gemba walks, and 5S to remove barriers and improve productivity. Filled the warehouse helper job description, which involved picking, packing, shipping, inventory management, and cleaning equipment. Saved 12% on UPS orders by staying on top of special deals. Cut down storage waste by 23% by switching to a Kanban system."
            }
        ],
        "location_country": "United States",
        "location_state": "CA",
        "education_level": "Associates Degree",
        "education": "Logistics and Supply Chain Fundamentals",
        "education_organization": "Atlanta Technical College",
        "education_grade": null,
        "certifications": [
            "Warehouse Sanitation"
        ],
        "publications": [],
        "websites": [
            "https://www.linkedin.com/",
            "https://www.pinterest.es/resumeviking/",
            "https://www.resumeviking.com/templates/",
            "https://resume.io/?id=cpdokyF1"
        ],
        "e-mail": [
            "email@email.com"
        ],
        "linkedin": null,
        "languages": [
            "English",
            "Spanish"
        ],
        "phone_numbers": [
            "3868683442"
        ]
    
    },
    "msg": ""
}