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https://github.com/411a/timezones-dataset

πŸ—ΊοΈ Plenary dataset of countries, timezones, cities, and flags, sorted by shared timezones...
https://github.com/411a/timezones-dataset

countries country-codes country-flags country-list country-names dataset timezone-list timezones

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πŸ—ΊοΈ Plenary dataset of countries, timezones, cities, and flags, sorted by shared timezones...

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### 🌐 Mutual Timezones Dataset: Countries, Country Codes, Cities and Flags

#### πŸ’Œ Thanks to:
* [OpenAI's ChatGPT](https://chat.openai.com): For expediting the process.
* [devhammed](https://gist.github.com/devhammed/78cfbee0c36dfdaa4fce7e79c0d39208): For the `devhammed_countries-flags-codes.json` file.
* [dmfilipenko](https://github.com/dmfilipenko/timezones.json/blob/master/timezones.json): For the `dmfilipenko_timezones.json` file.
* [zeitverschiebung.net](https://zeitverschiebung.net/en/all-time-zones.html): For the timezone data with cities (resulting in `01_scraped-timezones-cities.json`).
* [flagpedia.net](https://flagpedia.net/emoji): For the emoji flags (resulting in `02_scraped-flags.json`).

#### πŸ”° Project Steps:

πŸ’‘ The file names indicate the process themselves.

πŸ‘£ Steps

01: Scraped timezones and cities.

02: Scraped emoji flags.

03: Identified countries with multiple timezones.

04: First, I consulted ChatGPT and provided the content of 03_counted-countries.json to ask for a Python dictionary with capital or widely accepted timezones for countries with multiple timezones. Afterward, I manually researched and verified the results and adapted the city names (values) to match the city names in the JSON from step 01.

05: Created a JSON file (includes multiple timezones for each country).

06: Used the Python dictionary from step 04 to create a JSON file with unique timezones for each country!

#### πŸ’» Used by:
This work is done as part of my personal project, [UtAZBot](https://t.me/UtAZBot), an inline utility Telegram bot built with Rust, to display local times for all countries in sorted order.