REST API to SQL (with Python) | Full Data Project |

Publicado el: 30 agosto 2025
en el canal de: Stephen | Data
7,891
285

💻 Build an ETL pipeline that fetches data from a REST API and loads it into a SQL database (MySQL) using Python.

Follow along at your own pace - feel free to drop any questions or feedback you have in the comments below.

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📩 Join the waitlist for my private data community here (opening soon!):

https://data100.carrd.co/

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Become a data analyst using

Analyst Builder - https://www.analystbuilder.com/?via=s...

(Note - I earn a commission when you purchase any qualifying items via these links.

This does *not* cost you anything, but helps in creating more content!)

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📲 Socials:

TikTok -   / sdw.online  
Instagram -   / sdw.online  
LinkedIn -   / stephen-david-williams-860428123  
Facebook - https://www.facebook.com/profile.php?...
GitHub - https://github.com/sdw-online
Twitter/X -   / sdw_online  

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🎁 Free Resources:

Tableau Visual Vocabulary - https://www.tableau.com/en-gb/solutio...

Here are some of the free resources I’ve created that you may find useful for your own data projects:

My articles/ blogs -   / sdw-online  
How I broke into data - https://datapro.carrd.co/

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📩 Installation links:

Download these resources mentioned in the project:

SSMS - https://learn.microsoft.com/en-us/sql...
Power BI - https://powerbi.microsoft.com/en-us/d...

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🎶 Music used:

Morning Routine by Ghostrifter Official |   / ghostrifter-official  
Music promoted by https://www.chosic.com/free-music/all/
Creative Commons CC BY-SA 3.0
https://creativecommons.org/licenses/...

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⏲️ Timestamps:

Intro (00:00:00)
ETL pipeline architecture (00:00:08)
Scope the project (00:00:37)
Build mock-up in Excel (00:08:35)
Outline the steps (00:12:29)
API Football overview (RapidAPI) (00:18:10)
Read API docs (00:19:40)
Create GitHub repo (00:22:14)
Create files (00:25:25)
Load libraries into Jupyter notebook (00:27:10)
Grab API credentials (00:29:10)
Send GET request to API (00:36:37)
Explore API response (00:38:18)
Set up rows + cols for dataframe (00:44:54)
Loop through each PL team (00:45:37)
Build dataframe with Pandas (00:52:18)
Grab MySQL credentials (00:53:22)
Connect to server with Python (00:54:42)
Create user in MySQL (00:56:31)
Create database + table in MySQL (00:58:42)
Retry server connection to MySQL (01:02:46)
Connect to database with Python (01:03:49)
Upsert data into PL table (01:09:04)
Check results (01:18:37)
Outro (01:21:15)


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