Resume

The Python SDK supports the Mindee V1 Resume API.

Product Specifications

Specification	Details
Endpoint Name	resume
Recommended Version	v1.2
Supports Polling/Webhooks	✔️ Yes
Support Synchronous HTTP Calls	❌ No
Geography	🌐 Global

Quick-Start

Using the sample below, we are going to illustrate how to extract the data that we want using the SDK.

Sample Code

#
# Install the Python client library by running:
# pip install mindee
#

from mindee import Client, product, AsyncPredictResponse

# Init a new client
mindee_client = Client(api_key="my-api-key")

# Load a file from disk
input_doc = mindee_client.source_from_path("/path/to/the/file.ext")

# Load a file from disk and enqueue it.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.ResumeV1,
    input_doc,
)

# Print a brief summary of the parsed data
print(result.document)

Sample Output (rST)

########
Document
########
:Mindee ID: 9daa3085-152c-454e-9245-636f13fc9dc3
:Filename: default_sample.jpg

Inference
#########
:Product: mindee/resume v1.1
:Rotation applied: Yes

Prediction
==========
:Document Language: ENG
:Document Type: RESUME
:Given Names: Christopher
:Surnames: Morgan
:Nationality:
:Email Address: [email protected]
:Phone Number: [phone]
:Address: 177 Great Portland Street, London, W5W 6PQ
:Social Networks:
  +----------------------+----------------------------------------------------+
  | Name                 | URL                                                |
  +======================+====================================================+
  | LinkedIn             | linkedin.com/christopher.morgan                    |
  +----------------------+----------------------------------------------------+
:Profession: Senior Web Developer
:Job Applied:
:Languages:
  +----------+----------------------+
  | Language | Level                |
  +==========+======================+
  | SPA      | Fluent               |
  +----------+----------------------+
  | ZHO      | Beginner             |
  +----------+----------------------+
  | DEU      | Beginner             |
  +----------+----------------------+
:Hard Skills: HTML5
              PHP OOP
              JavaScript
              CSS
              MySQL
              SQL
:Soft Skills: Project management
              Creative design
              Strong decision maker
              Innovative
              Complex problem solver
              Service-focused
:Education:
  +-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
  | Domain          | Degree                    | End Month | End Year | School                    | Start Month | Start Year |
  +=================+===========================+===========+==========+===========================+=============+============+
  | Computer Inf... | Bachelor                  |           | 2014     | Columbia University, NY   |             |            |
  +-----------------+---------------------------+-----------+----------+---------------------------+-------------+------------+
:Professional Experiences:
  +-----------------+------------+--------------------------------------+---------------------------+-----------+----------+----------------------+-------------+------------+
  | Contract Type   | Department | Description                          | Employer                  | End Month | End Year | Role                 | Start Month | Start Year |
  +=================+============+======================================+===========================+===========+==========+======================+=============+============+
  |                 |            | Cooperate with designers to creat... | Luna Web Design, New York | 05        | 2019     | Web Developer        | 09          | 2015       |
  +-----------------+------------+--------------------------------------+---------------------------+-----------+----------+----------------------+-------------+------------+
:Certificates:
  +------------+--------------------------------+---------------------------+------+
  | Grade      | Name                           | Provider                  | Year |
  +============+================================+===========================+======+
  |            | PHP Framework (certificate)... |                           |      |
  +------------+--------------------------------+---------------------------+------+

Standard Fields

These fields are generic and used in several products.

BaseField

Each prediction object contains a set of fields that inherit from the generic BaseField class. A typical BaseField object will have the following attributes:

• value (Union[float, str]): corresponds to the field value. Can be None if no value was extracted.

• confidence (float): the confidence score of the field prediction.

• bounding_box ([Point, Point, Point, Point]): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document.

• polygon (List[Point]): contains the relative vertices coordinates (Point) of a polygon containing the field in the image.

• page_id (int): the ID of the page, always None when at document-level.

• reconstructed (bool): indicates whether an object was reconstructed (not extracted as the API gave it).

A Point simply refers to a list of two numbers ([float, float]).

Aside from the previous attributes, all basic fields have access to a custom __str__ method that can be used to print their value as a string.

ClassificationField

The classification field ClassificationField does not implement all the basic BaseField attributes. It only implements value, confidence and page_id.

A classification field's `value is always a `str`. {% endhint %}

StringField

The text field StringField only has one constraint: its value is an Optional[str].

Specific Fields

Fields which are specific to this product; they are not used in any other product.

Certificates Field

The list of certificates obtained by the candidate.

A ResumeV1Certificate implements the following attributes:

• grade (str): The grade obtained for the certificate.

• name (str): The name of certification.

• provider (str): The organization or institution that issued the certificate.

• year (str): The year when a certificate was issued or received. Fields which are specific to this product; they are not used in any other product.

Education Field

The list of the candidate's educational background.

A ResumeV1Education implements the following attributes:

• degree_domain (str): The area of study or specialization.

• degree_type (str): The type of degree obtained, such as Bachelor's, Master's, or Doctorate.

• end_month (str): The month when the education program or course was completed.

• end_year (str): The year when the education program or course was completed.

• school (str): The name of the school.

• start_month (str): The month when the education program or course began.

• start_year (str): The year when the education program or course began. Fields which are specific to this product; they are not used in any other product.

Languages Field

The list of languages that the candidate is proficient in.

A ResumeV1Language implements the following attributes:

• language (str): The language's ISO 639 code.

• level (str): The candidate's level for the language. Possible values include:

  • Native

  • Fluent

  • Proficient

  • Intermediate

  • Beginner

Fields which are specific to this product; they are not used in any other product.

Professional Experiences Field

The list of the candidate's professional experiences.

A ResumeV1ProfessionalExperience implements the following attributes:

• contract_type (str): The type of contract for the professional experience. Possible values include:

  • Full-Time

  • Part-Time

  • Internship

  • Freelance

• department (str): The specific department or division within the company.

• description (str): The description of the professional experience as written in the document.

• employer (str): The name of the company or organization.

• end_month (str): The month when the professional experience ended.

• end_year (str): The year when the professional experience ended.

• role (str): The position or job title held by the candidate.

• start_month (str): The month when the professional experience began.

• start_year (str): The year when the professional experience began. Fields which are specific to this product; they are not used in any other product.

Social Networks Field

The list of social network profiles of the candidate.

A ResumeV1SocialNetworksUrl implements the following attributes:

• name (str): The name of the social network.

• url (str): The URL of the social network.

Attributes

The following fields are extracted for Resume V1:

Address

address (StringField): The location information of the candidate, including city, state, and country.

print(result.document.inference.prediction.address.value)

Certificates

certificates (List[ResumeV1Certificate]): The list of certificates obtained by the candidate.

for certificates_elem in result.document.inference.prediction.certificates:
    print(certificates_elem.value)

Document Language

document_language (StringField): The ISO 639 code of the language in which the document is written.

print(result.document.inference.prediction.document_language.value)

Document Type

document_type (ClassificationField): The type of the document sent.

Possible values include:

• 'RESUME'

• 'MOTIVATION_LETTER'

• 'RECOMMENDATION_LETTER'

print(result.document.inference.prediction.document_type.value)

Education

education (List[ResumeV1Education]): The list of the candidate's educational background.

for education_elem in result.document.inference.prediction.education:
    print(education_elem.value)

Email Address

email_address (StringField): The email address of the candidate.

print(result.document.inference.prediction.email_address.value)

Given Names

given_names (List[StringField]): The candidate's first or given names.

for given_names_elem in result.document.inference.prediction.given_names:
    print(given_names_elem.value)

Hard Skills

hard_skills (List[StringField]): The list of the candidate's technical abilities and knowledge.

for hard_skills_elem in result.document.inference.prediction.hard_skills:
    print(hard_skills_elem.value)

Job Applied

job_applied (StringField): The position that the candidate is applying for.

print(result.document.inference.prediction.job_applied.value)

Languages

languages (List[ResumeV1Language]): The list of languages that the candidate is proficient in.

for languages_elem in result.document.inference.prediction.languages:
    print(languages_elem.value)

Nationality

nationality (StringField): The ISO 3166 code for the country of citizenship of the candidate.

print(result.document.inference.prediction.nationality.value)

Phone Number

phone_number (StringField): The phone number of the candidate.

print(result.document.inference.prediction.phone_number.value)

Profession

profession (StringField): The candidate's current profession.

print(result.document.inference.prediction.profession.value)

Professional Experiences

professional_experiences (List[ResumeV1ProfessionalExperience]): The list of the candidate's professional experiences.

for professional_experiences_elem in result.document.inference.prediction.professional_experiences:
    print(professional_experiences_elem.value)

Social Networks

social_networks_urls (List[ResumeV1SocialNetworksUrl]): The list of social network profiles of the candidate.

for social_networks_urls_elem in result.document.inference.prediction.social_networks_urls:
    print(social_networks_urls_elem.value)

Soft Skills

soft_skills (List[StringField]): The list of the candidate's interpersonal and communication abilities.

for soft_skills_elem in result.document.inference.prediction.soft_skills:
    print(soft_skills_elem.value)

Surnames

surnames (List[StringField]): The candidate's last names.

for surnames_elem in result.document.inference.prediction.surnames:
    print(surnames_elem.value)