markdown_files/BBC_Weather_API_with_Python.md

metadata

title: BBC Weather API with Python
original_url: >-
  https://tds.s-anand.net/#/bbc-weather-api-with-python?id=bbc-weather-location-id-with-python
downloaded_at: '2025-06-08T23:24:13.538036'

BBC Weather location ID with Python

You’ll learn how to get the location ID of any city from the BBC Weather API – as a precursor to scraping weather data – covering:

• Understanding API Calls: Learn how backend API calls work when searching for a city on the BBC weather website.
• Inspecting Web Interactions: Use the browser’s inspect element feature to track API calls and understand the network activity.
• Extracting Location IDs: Identify and extract the location ID from the API response using Python.
• Using Python Libraries: Import and use requests, json, and urlencode libraries to make API calls and process responses.
• Constructing API URLs: Create structured API URLs dynamically with constant prefixes and query parameters using urlencode.
• Building Functions: Develop a Python function that accepts a city name, constructs the API call, and returns the location ID.

To open the browser Developer Tools on Chrome, Edge, or Firefox, you can:

• Right-click on the page and select “Inspect” to open the developer tools
• OR: Press F12
• OR: Press Ctrl+Shift+I on Windows
• OR: Press Cmd+Opt+I on Mac

Here are links and references:

• BBC Location ID scraping - Notebook
• BBC Weather - Palo Alto (location ID: 5380748)
• BBC Locator Service - Los Angeles
• Learn about the requests package. Watch Python Requests Tutorial: Request Web Pages, Download Images, POST Data, Read JSON, and More

BBC Weather data with Python

You’ll learn how to scrape the live weather data of a city from the BBC Weather API, covering:

• Introduction to Web Scraping: Understand the basics of web scraping and its legality.
• Libraries Overview: Learn the importance of requests and BeautifulSoup.
• Fetching HTML: Use requests to fetch HTML content from a web page.
• Parsing HTML: Utilize BeautifulSoup to parse and navigate the HTML content.
• Identifying Data: Inspect HTML elements to locate specific data (e.g., high and low temperatures).
• Extracting Data: Extract relevant data using BeautifulSoup‘s find_all() function.
• Data Cleanup: Clean extracted data to remove unwanted elements.
• Post-Processing: Use regular expressions to split large strings into meaningful parts.
• Data Structuring: Combine extracted data into a structured pandas DataFrame.
• Handling Special Characters: Replace unwanted characters for better data manipulation.
• Saving Data: Save the cleaned data into CSV and Excel formats.

Here are links and references:

• BBC Weather scraping - Notebook
• BBC Locator Service - Mumbai
• BBC Weather - Mumbai (location ID: 1275339)
• BBC Weather API - Mumbai (location ID: 1275339)
• Learn about the json package. Watch Python Tutorial: Working with JSON Data using the json Module
• Learn about the BeautifulSoup package. Watch Python Tutorial: Web Scraping with BeautifulSoup and Requests
• Learn about the pandas package. Watch
  • Python Pandas Tutorial (Part 1): Getting Started with Data Analysis - Installation and Loading Data
  • Python Pandas Tutorial (Part 2): DataFrame and Series Basics - Selecting Rows and Columns
• Learn about the re package. Watch Python Tutorial: re Module - How to Write and Match Regular Expressions (Regex)
• Learn about the datetime package. Watch Python Tutorial: Datetime Module - How to work with Dates, Times, Timedeltas, and Timezones

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