MagicalAPI Python SDK

MagicalAPI Python SDK lets developers integrate AI-powered resume parsing, resume scoring, resume matching, and LinkedIn public data extraction into Python applications. MagicalAPI.com
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Table of Contents

• What is MagicalAPI?
• What you can build
• Features
• Services
• About the Project
• Getting Started
• Usage
• Contributing
• License

What is MagicalAPI?

MagicalAPI is your AI edge in careers and data insights, Your ultimate tool for Resume Parsing, LinkedIn data and more. It offers services like:

• Resume Parsing: Extract structured data from resumes.
• LinkedIn Data Extraction: Scrape and analyze LinkedIn profiles.
• Career Insights: Gain AI-driven recommendations for career development.

What you can build

• Resume parsing pipelines for HR platforms
• Candidate scoring and job matching workflows
• LinkedIn profile enrichment tools
• Recruiting automation systems
• ATS integrations

Features

• Resume Parsing: Parse resumes to extract key information like skills, experience, and education.
• LinkedIn Profile Scraping: Extract data from LinkedIn profiles for analysis.
• Career Insights: Leverage AI to get actionable career recommendations.
• Type-Annotated and Async: Built for modern Python with type hints and asynchronous support.

Supported APIs

• Resume Parser
• Resume Checker(Review)
• Resume Matcher(Score)
• LinkedIn Profile Scraper
• LinkedIn Company Scraper

About The Project

This is a Python client that provides easy access to the MagicalAPI.com services, fully type-annotated and asynchronous.

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Getting Started

This is an example of how you can install the client and use it in your own scripts and projects.

Installation

Install the package using pip

pip install magicalapi

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Usage

Here are some samples of how to use the client for each service. At first, you have to create an object of AsyncClient like this:

frommagicalapi.clientimportAsyncClientAPI_KEY="mag_123456"client=AsyncClient(api_key=API_KEY)

You can pass the API_KEY on the code, or put it on a .env file and the client will read from there.

Config .env File

Example of using .env file, all settings start with the prefix MAG_ and are case insensitive, so MAG_EXAMPLE, Mag_example, and mag_EXAMPLE are equal.

# .env
MAG_API_KEY="mag_1234567"

So now you can leave api_key parameter empty.

frommagicalapi.clientimportAsyncClientclient=AsyncClinet()

Using Webhooks (Optional)

For asynchronous response delivery, you can provide a webhook_url when initializing the client. The API will send the response to your webhook endpoint instead of using the polling mechanism.

frommagicalapi.clientimportAsyncClient# Your webhook must be whitelisted in MagicalAPI panelwebhook_url="https://your-domain.com/webhook"client=AsyncClient(webhook_url=webhook_url)

Important: Webhook domains must be registered in the MagicalAPI panel. For setup guide, see the webhook documentation and example.

Here is an example of how to parse a resume using Resume Parser service:

importasynciofrommagicalapi.clientimportAsyncClientfrommagicalapi.errorsimportAPIServerError, APIServerTimedoutfrommagicalapi.types.baseimportErrorResponseresume_url= (
"https://resume-resource.com/wp-content/uploads/00123-sales-professional-resume.pdf"
)
output_file_name="resume_parser.json"asyncdefmain():
try:
# the api_key will load from the .env fileasyncwithAsyncClient() asclient:
response=awaitclient.resume_parser.get_resume_parser(url=resume_url)
ifisinstance(response, ErrorResponse):
# got error from apiprint("Error :", response.message)
else:
# got response successfullyprint("credists :", response.usage.credits)
# save response in json filewithopen(output_file_name, "w") asfile:
file.write(response.model_dump_json(indent=3))
print(f"response saved to {output_file_name}")
except (APIServerError, APIServerTimedout) ase:
# handling server errorsprint(e)
exceptExceptionase:
print("An error occurred:", str(e))
asyncio.run(main())

All of the methods in the client have type hints and help to simply use.

For full examples, please see the Examples Directory

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Contributing

Contributions are what makes the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Here is the Contributing Guidelines. Don't forget to give the project a star! Thanks again!

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License

Distributed under the MIT License. See LICENSE for more information.

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