Comprehensive Strava Data Scraper Tool that is able to scrape historic data per rider per second recorded

I'm seeking an experienced developer to build a modern data scraper tool for Strava, a digital platform for cyclists. Your solution should be designed to diligently pull, parse, and export relevant data in a CSV file format, paving a hassle-free data analysis road for me.

The user should be able to specify for which rider(s) he wants to pull information. It should be possible to enter dateranges (if nothing is entered by default everything until the first record recorded should be scraped).

Specifically, the scraper should be able to collect information such as:

- Ride distances
- Ride durations
- Ride dates
- Real Power data
- Estimated Power data (this is usually provided when real power data is not available)
- Heart rate
- Cadence
- Speed
- Temperature

Note: these data points may require to scroll on the page to record the all the datapoints per second!!
Second note: the amount of data that is shown can vary per activity and per rider. Some will has estimated power data, some will have real power data and in some instances there will no power data at all shown. So the scraper will have to record whatever data is available on screen and put it in the correct category.

Filters and criteria are crucial in my project as they ensure data relevance and accuracy. The program should allow me to filter records by:

- Ride distance range
- Ride duration range
- Specific dates
- Power threshold
- Heart rate threshold
- Cadence threshold

Ideal Skills and Experience:

- Previous experience in data scraping, particularly for athletic or fitness platforms
- Proficient in a suitable programming language for scraping (Python, Javascript, etc)
- Knowledge in working with CSV files should be impeccable
- A comprehensive understanding of Strava's API and its limitations

With your skills, I hope to get faster and smarter results from my Strava data. Let's ride ahead with this!