shutterstock-analysis 0.0.2

The internet's very first python package supports analyzing the Shutterstock public data, which helps creators optimize their creative portfolio and earn more income with less effort.

shutterstock_analysis

The internet's first python package supports analyzing the Shutterstock public data, which helps creators optimize their creative portfolio and earn more income with less effort.

shutterstock_analysis relies on public APIs, similar to how you use the web browser to access Shutterstock service to provide you the underlay insights. It is FREE and has NO LIMITATIONS.

You can support this project on Patreon (or Momo in Vietnam) based on how you feel it is helpful. Scroll the end of this page for more details.

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II. REFERENCES

2.1. How to use this package?

• Install the stable version: pip install shutterstock_analysis
• You can install the latest shutterstock_analysis version from source with the following command: pip install git+https://github.com/thinh-vu/shutterstock_analysis.git@main

(*) You might need to insert a ! before your command when running terminal commands on Google Colab.

• To start using functions, you need to import them: from shutterstock_analysis import *

2.2. Function references

You can also read the function suggestion on your IDE which loads the documentation from the doc string. It's fairly simple, trust me!

2.2.1. Image search

• Get image search results from multiple Shutterstock result pages:

  search_df = image_search('ha giang', page_limit=10)

• Get bulk photos details:

  bulk_photo_detail = bulk_photo_detail(search_df, limit=100)

2.2.2. Creative video search

Although the data for the Editorial video is available, I decided to skip that option since it's not practical for my use case. Do feel free to develop it on your own if it's needed.

• Get video search results from multiple Shutterstock result pages:

  search_df = image_search('ha giang', page_limit=10)

• Get bulk videos details:

  bulk_photo_detail = bulk_photo_detail(search_df, limit=100)

2.2.3. Export data:

• This is the simplest way to export data from python to a CSV file which you can analyze easily either with Excel or Google Sheets.

  • Export search results: search_df.to_csv('YOUR_PATH_TO_FILE.csv', index=False)

  • Export photo details: bulk_photo_detail.to_csv('YOUR_PATH_TO_FILE.csv', index=False)

Limitations

• Support photo and video searches:

  • Photo Search (Non-Editorial and Editorial)
  • Video Creative Search. Skip Editorial Video search.

• Need to avoid abusing the API, which might lead to the service provider blocking the bot traffic.

III. APENDICES

Photo search query structure:

Default photo search

https://www.shutterstock.com/_next/data/abgKsgPYfFDoIqIr0JlX0/en/_shutterstock/search/ha-giang.json?image_type=photo&term=ha-giang

Default Search UI:

Advanced photo search

https://www.shutterstock.com/_next/data/abgKsgPYfFDoIqIr0JlX0/en/_shutterstock/search/ha-giang.json?image_type=photo&term=ha-giang&page=2&&contributor=Big+Pearl&category=Nature&sort=newest&release=editorial&mreleased=true&exclude=car%2C+bike&artistsInclude=VN&authentic=true

Advanced Search UI

Video creative search query structure

Default Video search

https://www.shutterstock.com/_next/data/qaf5FoOwtgZ0aXCZ3JlVY/en/_shutterstock/video/search/ha-giang.json?term=ha-giang

Advanced Video Creative search

https://www.shutterstock.com/_next/data/qaf5FoOwtgZ0aXCZ3JlVY/en/_shutterstock/video/search/ha-giang.json?term=ha-giang&page=2&sort=newest&res=4k&aspect_ratio=16%3A9&duration=0-90&fps=30&mreleased=true&people_number=2&contributor=bui+minh+vu&artistsInclude=VN&exclude=car%2C+bike&release=editorial&category=Nature&safe=off

IV. 🙋‍♂️ CONTACT INFORMATION

You can contact me at one of my social network profiles:

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If you want to support my open-source projects, you can "buy me a coffee" via Patreon or Momo e-wallet (VN). Your support will help to maintain my blog hosting fee & to develop high-quality content.