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Weather Data Collector

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This project includes a Python application that retrieves, processes, and stores daily weather data for specific cities using the "WeatherAPI." It also integrates this data with a MongoDB database and exports it to a CSV file.

Table of Contents

• Project Description
• Getting Started
• Usage
• GitHub Actions Workflow
• Requirements
• Contributing
• Raw Data Example
• Processed Data

Project Description

This project fetches daily weather data for Turkish cities using the "WeatherAPI" and stores it in a MongoDB database. It also converts this data into a CSV file and integrates it with current data.

Dependencies

• WeatherAPI: API KEY
• MongoDB: Cluster/DB URI KEY
• GitHub Actions (to schedule and workflow)

Getting Started

You can get started with the project by either cloning it to your local machine or downloading it as a ZIP file.

git clone https://github.com/ardasamett/WeatherDataCollector.git

Usage

(Please make sure to pay attention to dependencies.)

To run the project manually, follow these steps:

1. Navigate to the project directory: cd WeatherDataCollector
2. Run the main.py to collect weather data: python main.py
3. Run the datamanager.py to process and store the data: python datamanager.py

GitHub Actions Workflow

This project uses GitHub Actions to automate the process of collecting and storing weather data. The workflow is defined in the actions.yml file.

Here's a brief overview of the workflow steps:

• It sets up the required Python environment.
• Starts the specified version of MongoDB.
• Executes main.py to collect weather data.
• Executes datamanager.py to process and store the data.
• Commits any changes to the repository and pushes them to the main branch.

This automation ensures that the weather data is regularly updated and integrated into the project.

Requirements

To run the project manually, you'll need the following dependencies:

• Python 3.9 or higher
• Pandas library
• MongoDB database
• WeatherAPI API key

You can install the requirements using the following command:

pip install -r requirements.txt

Contributing

To contribute to the project, you can follow these steps:

1. Open or contribute to an existing issue.
2. Submit your code changes via a pull request.
3. Wait for the review process and make necessary updates if required.

Raw Data Example

Here's an example of the raw weather data on MongoDB collected for a city:

{
  "_id": "2023-09-10",
  "Data": {
    "Van": {
      "location": {
        "name": "Van",
        "region": "Van",
        "country": "Turkey",
        "lat": 38.49,
        "lon": 43.38,
        "tz_id": "Europe/Istanbul",
        "localtime_epoch": 1694294429,
        "localtime": "2023-09-10 0:20"
      },
      "current": {
        "last_updated_epoch": 1694294100,
        "last_updated": "2023-09-10 00:15",
        "temp_c": 19.0,
        "temp_f": 66.2,
        "is_day": 0,
        "condition": {
          "text": "Partly cloudy",
          "icon": "//cdn.weatherapi.com/weather/64x64/night/116.png",
          "code": 1003
        },
        "wind_mph": 6.9,
        "wind_kph": 11.2,
        "wind_degree": 200,
        "wind_dir": "SSW",
        "pressure_mb": 1016.0,
        "pressure_in": 30.0,
        "precip_mm": 0.0,
        "precip_in": 0.0,
        "humidity": 46,
        "cloud": 25,
        "feelslike_c": 19.0,
        "feelslike_f": 66.2,
        "vis_km": 10.0,
        "vis_miles": 6.0,
        "uv": 1.0,
        "gust_mph": 7.6,
        "gust_kph": 12.2
      }
    }
  }
}

Processed Data

Here is the processed weather data for some cities:

| City | LocalTime | Temperature_C | Wind_Speed_kph | Humidity | Condition | | -------------- | ---------------- | ------------- | -------------- | -------- | --------- | | Adana | 2023-09-10 15:35 | 33.0 | 22.0 | 49 | Sunny | | Adiyaman | 2023-09-10 15:35 | 31.3 | 23.4 | 11 | Sunny | | Afyonkarahisar | 2023-09-10 15:35 | 25.0 | 3.6 | 28 | Sunny | | Agri | 2023-09-10 15:35 | 18.0 | 14.4 | 17 | Sunny | | Aksaray | 2023-09-10 15:35 | 25.1 | 26.3 | 20 | Sunny |

... .. .