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    "info": {
        "author": "Joseph Pallipadan",
        "author_email": "pallipadanjoseph@gmail.com",
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        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "## Overview\n*namsor-client* is a python package that serves as a wrapper for the Namsor classification API.\nThe API can determine the likely gender, ethnicity and country of origin of an individual with a particular name.\n\n## Installation\n\n```pip install namsor-client```\n\n## Usage\n\n```python\nfrom namsorclient import NamsorClient\nfrom namsorclient.country_codes import CountryCodes\nfrom namsorclient.request_objects import *\n\n\n# Create an instance of NamsorClient and pass in your API key as an argument.\nclient = NamsorClient(\"Insert API key\")\n\n# Access the gender (GET) endpoint with function that returns a response of type GenderResponse.\nresponse = client.gender(\"Lelouch\",\"Lamperouge\")\n\n# Access the different parts of the response for this particular endpoint.\n\nprint(response.ID)\nprint(response.first_name)\nprint(response.last_name)\nprint(response.likely_gender)\nprint(response.gender_scale)\nprint(response.score)\nprint(response.probability_calibrated)\n\n# Refer to the Responses section to view all different variables of each different Response.\n\n\n# Access the genderBatch (POST) endpoint\ngender_batch = GenderBatch()\n\n# Add items, with required arguments, to the batch you want\ngender_batch.addItem(\"Lelouch\",\"Lamperouge\",\"A2773\")\ngender_batch.addItem(\"Gon\",\"Freecs\", \"M9835\")\ngender_batch.addItem(\"Jonathan\",\"Joestar\", \"M6104\")\n\n# Use classify function with required API Key argument and receive responses in the form of a list.\nresponse_list = gender_batch.classify(\"Insert API key\")\n\nprint(response_list[2].likely_gender)\n\n# Refer to the Batches section to look at the different types of batches and view the type of responses that will be returned when a batch is classified.\n```\n\n\nUse the `export_to_excel` function to create a file with the required file name to represent the batch's data in spreadsheet form. \n```python \ngender_batch.export_to_excel(\"File Name.xlsx\")\n```\n**Result:**\n![GitHub Logo](spreadsheet_example.png)\n## API\n\n- **gender(first_name: str, last_name: str)**\n*Infer the likely gender of a name.*\n\n    - ```first_name: The desired first name. ```\n    - ```last_name: The desired last name. ```\n    - *Returns*: ```GenderResponse ```\n  \n- **genderGeo(first_name: str, last_name: str, country_code: CountryCodes)**\n*Infer the likely gender of a name, given a local context (ISO2country code).*\n\n    - ```first_name: The desired first name.```\n    - ```last_name: The desired last name.```\n    - ```country_code: The country code to aid with classification.```\n    - *Returns*: ```GenderResponse```\n\n- **genderFullGeo(full_name: str, country_code: CountryCodes)**\n*Infer the likely gender of a full name, given a local context (ISO2 country code).*\n\n    - ```full_name: The name to be classified.```\n    - ```country_code: The country code to aid with classification.```\n    - *Returns*: ```GenderResponse```\n\n- **genderFull(full_name: str)**\n*Infer the likely gender of a full name, ex. John H. Smith*\n\n    - ```full_name: The name to be classified.```\n    - *Returns*: ```GenderResponse```\n\n- **usRaceEthnicity(first_name: str, last_name: str)**\n*Infer a US resident's likely race/ethnicity according to US Census taxonomy W_N(white, non latino), HL (hispano latino),  A (asian, non latino), B_NL (black, non latino).*\n\n    - ```first_name: The desired first name.```\n    - ```last_name: The desired last name.```\n    - *Returns*: ```OriginResponse```\n        \n- **usRaceEthnicityZIP5(first_name: str, last_name: str, zip5_code: str)**\n*Infer a US resident's likely race/ethnicity according to US Census taxonomy, usingZIP5code info. Output is W_NL (white, non latino), HL (hispano latino),  A (asian,non latino, B_NL (black, non latino).*\n\n    - ```first_name: The desired first name```\n    - ```last_name: The desired last name```\n    - ```zip5_code: The zip code to aid with classification```\n    - *Returns*: ```OriginResponse```\n    \n\n- **diaspora(first_name: str, last_name: str, country_code: CountryCodes)**\n*Infer the likely ethnicity/diaspora of a personal name, given a country of residence ISO2 code*\n\n    - ```first_name: The desired first name. ```\n    - ```last_name: The desired last name. ```\n    - ```country_code: The country code to aid with classification.```\n    - *Returns*: ```DiasporaResponse ```\n\n- **parseName(full_name: str)**\n*Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John, given an ISO2 country of residence.*\n\n    - ```full_name: The full name to be parsed. ```\n    - *Returns*: ```ParseNameResponse ```\n\n- **parseNameGeo(full_name: str, country_code: CountryCodes)**\n*Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John, given an ISO2 country of residence.*\n\n    - ```full_name: The full name to be parsed. ```\n    - ```country_code: The country code to aid with classification.```\n    - *Returns*: ```ParseNameResponse ```\n\n- **origin(first_name: str, last_name: str)**\n*Infer the likely country of origin of a personal name. Assumes names as they are in the country of origin. For US, CA, AU, NZ and other melting-pots : use 'diaspora' instead.*\n\n    - ```first_name: The desired first name. ```\n    - ```last_name: The desired last name. ```\n    - *Returns*: ```OriginResponse ```\n\n- **country(full_name: str)**\n*Infer the likely country of residence of a personal full name, or one surname. Assumes names as they are in the country of residence OR the country of origin.*\n\n    - ```full_name: The name whose country of residence should be determined. ```\n    - *Returns*: ```OriginResponse ```\n\n\n\n## Responses\n- **GenderResponse**\n  - ```ID```\n  - ```first_name```\n  - ```last_name```\n  - ```likely_gender```\n  - ```gender_scale```\n  - ```score```\n  - ```probability_calibrated```\n- **GenderFullResponse**\n  - ```ID```\n  - ```name```\n  - ```likely_gender```\n  - ```gender_scale```\n  - ```score```\n- **OriginResponse**\n  - ```ID```\n  - ```first_name```\n  - ```last_name```\n  - ```likely_gender```\n  - ```score```\n  - ```country_origin```\n  - ```country_origin_alt```\n  - ```region_origin```\n  - ```top_region_origin```\n  - ```sub_region_origin```\n- **CountryResponse**\n  - ```ID```\n  - ```name```\n  - ```score```\n  - ```country```\n  - ```country_alt```\n  - ```region```\n  - ```top_region```\n  - ```sub_region```\n- **RaceEthnicityResponse**\n  - ```ID```\n  - ```first_name```\n  - ```last_name```\n  - ```race_ethnicity```\n  - ```race_ethnicity_alt```\n  - ```score```\n- **DiasporaResponse**\n  - ```ID```\n  - ```first_name```\n  - ```last_name```\n  - ```score```\n  - ```ethnicity```\n  - ```ethnicity_alt```\n  - ```lifted```\n  - ```country```\n- **ParseNameResponse**\n  - ```ID```\n  - ```name```\n  - ```name_parser_type```\n  - ```name_parser_type_alt```\n  - ```first_last_name```\n  - ```score```\n\n## Batches\nThe wrapper also exposes batch functions for each of the different classifications. These are to be used when multiple items need to be classified together.\n\n- ```GenderBatch``` --> `classify` *function returns* `GenderResponse` *list*     \n- ```GenderGeoBatch``` -->  `classify` *function returns* `GenderResponse` *list*\n- ```ParsedGenderBatch``` --> `classify` *function returns* `GenderResponse` *list*\n- ```ParsedGenderGeoBatch``` --> `classify` *function returns* `GenderResponse` *list*\n- ```GenderFullBatch``` --> `classify` *function returns* `GenderFullResponse` *list*\n- ```GenderFullGeoBatch``` --> `classify` *function returns* `GenderFullResponse` *list*\n- ```OriginBatch``` --> `classify` *function returns* `OriginResponse` *list*\n- ```CountryBatch``` --> `classify` *function returns* `CountryResponse` *list*\n- ```US_RaceEthnicityBatch``` --> `classify` *function returns* `RaceEthnicityResponse` *list*\n- ```US_ZipRaceEthnicityBatch``` --> `classify` *function returns* `RaceEthnicityResponse` *list*\n- ```DiasporaBatch``` --> `classify` *function returns* `DiasporaResponse` *list*\n- ```ParseNameBatch``` --> `classify` *function returns* `ParsedNameResponse` *list*\n- ```ParseNameGeoBatch``` --> `classify` *function returns* `ParsedNameResponse` *list*\n\n\n## Country Codes\nWhenever a country code needs to be passed to any function, the `CountryCodes` class should be used. It exposes an enum with all recognized country codes of the world marked by the respective country's name.\n\n## Contributing\nTo contribute to this repository, fork it and make changes. To run tests, cd into namsorclient and \nrun ```python -m pytest```. If all tests pass, sumbit a pull request. Note that the faker and xlrd modules are required for testing.",
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