Cycling Shoe Reports with Strava and TP APIs are the ideal solution for automatically transforming your training data into clear, visual reports ready for analysis.
If you’re a cyclist or triathlete, you know how laborious it can be to manually gather information from Strava and TrainingPeaks. Now imagine having all of this generated automatically, hassle-free.
By integrating these two platforms via API, you can create custom reports that save time, provide greater data accuracy, and provide easy-to-interpret visualizations.
In this article, you’ll learn step-by-step how to obtain your API keys, process your cycling data, and generate reports in PDF or HTML, all automatically. Get ready to revolutionize the way you track your performance.
Why automate your cycling reports?
Let’s delve a little deeper: generating reports manually can be time-consuming and error-prone. Automating this process offers much more than just convenience. Another important point to consider is standardizing your analysis. Using APIs, you can create consistent reports with data such as cadence, power, TSS, heart rate, and distance covered.
It’s also worth noting that by integrating Strava with TrainingPeaks, you keep your data synchronized and can generate weekly, monthly, and even workout-type graphs—all with a professional look and exportability.
Tools You’ll Need
To better understand, let’s look at the basic tools you’ll use:
- Strava API
- TrainingPeaks API
- Python + libraries: requests, pandas, matplotlib, jinja2, fpdf
- Code editor like VS Code or PyCharm
- Task scheduler: CRON or Task Scheduler (Windows)
How to get your API keys
Let’s now explore in more detail how to access the APIs:
Strava
- Visit developers.strava.com
- Register your application and get the client_id and client_secret
- Use OAuth2 to generate your access token
- Store the token in a secure location
TrainingPeaks
- Request API access via technical support
- Wait for approval and receive your credentials
- Implement the OAuth2 flow for authentication
It’s important to note that each platform has daily request limits.
Creating your reports automatically
Now that you have the data, it’s time to transform it all into something visual and useful.
- Make requests with requests
- Use pandas to organize the data
- Create graphs with matplotlib
- HTML generation: jinja2 / PDF: fpdf
- Schedule to run weekly
Include indicators such as:
- Total distance cycled
- Average TSS for the week
- Time in effort zones
- Normalized power
- Comparison with previous weeks
Valuable tips to improve your automation
Want to make your automation even more powerful? Here are some unusual suggestions:
- Automatic sending via email or WhatsApp
- Integration with Google Drive or Dropbox
- Inclusion of custom goals in the report
- Visual design with themed templates
- Monthly history with performance alerts
Examples of cycling shoe reports
Let’s now explore in more detail some examples you can create:
- Weekly performance
- Time by heart rate zones
- Monthly progress comparison
- Race report with analysis by sector
- Cycling shoe usage history (by equipment)
These reports help you understand where you’ve progressed and what you can improve.
How to create engaging visualizations
Visualizing data is as important as collecting it. Here’s how to make them more attractive:
- Use themed colors (e.g., blue for Z2, red for Z5)
- Highlight KPIs in visual boxes
- Use emojis or icons for easier reading
- Create a cover page with the date, name, and weekly goals
- Add high-resolution charts
These details make your report much more professional.
Automating everything with scheduled tasks
It’s also worth noting that all this automation can be run on a recurring basis. To do this:
- Use CRON on Linux/macOS or Scheduler on Windows
- Schedule it to run every Sunday night
- Combine it with scripts that automatically send emails
- Protect your credentials in .env files
- Test locally and monitor logs
- This way, your pedal-shoe reports will always be up-to-date.
Additional resources and useful libraries
Tools that can elevate your project:
- Plotly: interactive charts
- WeasyPrint: PDF directly from HTML with CSS
- Streamlit or Dash: online dashboards
- Google Sheets API: spreadsheet integration
- Jupyter Notebooks: interactive testing environment
These resources help you create more advanced and integrated reports.
Handling API errors and limitations
It’s not all sunshine and roses when dealing with automatic integrations. Some best practices when dealing with APIs:
- HTTP error handling: implement try/except to handle connection failures, expired tokens, or limits reached.
- Data validation: always verify that the returned data is valid and complete before processing.
- Detailed logs: keep logs of accesses, errors, and results for each execution. This facilitates future adjustments.
- Exponential backoff: in case of failure due to excessive requests, use retries with progressive delay.
These practices ensure more robust and reliable automation.
Customization by User Type
You can adapt your reports to different profiles:
- Beginner cyclists: focus on training time evolution, heart rate zones, and consistency.
- Intermediate cyclists: highlight normalized power, TSS variations, and weekly volume.
- Advanced/Competitors: comparison with power targets, analysis by race sectors, and time in zones 4 and 5.
This makes reports more relevant and useful for each athlete.
Data Security and Privacy Cycling Shoe Reports
When dealing with APIs and personal training data, it is essential to protect:
- Tokens and passwords: never expose them in the code; use environment variables or .env files.
- Encrypted backups: if storing data locally, encrypt sensitive files.
- Strong authentication: prefer OAuth2 and never share tokens publicly.
- User consent: if reporting to third parties, ensure authorization to access their accounts.
Security is an essential part of system reliability.
Scaling for Multiple Users (Multi-Athlete)
If you want to create a system that works for multiple athletes, consider:
- Structuring the data with a database (e.g., SQLite, PostgreSQL)
- Using different access tokens for each athlete
- Creating a web interface so each athlete can view their own reports
- Generating individualized PDFs with their name and goals
This model is ideal for coaches or sports advisors.
Alternative metrics you can explore
In addition to the standard metrics, here are other suggestions to enhance your reports:
- IF (Intensity Factor)
- EF (Efficiency Factor)
- Average RPM per workout
- Sum of weekly cumulative elevation
- Standard deviation of power
- Total time above 90% of HRmax
These analyses help reveal important nuances about performance.
Conclusion: Cycling Shoe Reports
If you’ve made it this far, you already understand that automating your cycling reports using the Strava and TrainingPeaks APIs can completely change the way you train.
You’ve seen how to get your API keys, which tools to use, and how to transform raw data into professional PDF or HTML reports. More than just a matter of style, this means saved time, more clarity in your training, and consistent progress based on real data.
Now it’s your turn! Start setting up your integration today. Take advantage of the features already available and make your training routine more efficient, analytical, and intelligent.
Don’t let your data sit idle, turn it into performance.
Experiment, automate, and feel the difference on your next ride!
