Python application that automates the collection of attendance information of the members of an institution's gym. Using web scraping techniques, the code extracts participants' presence data for each day, providing valuable insights into the facility's usage frequency over time.
- Access to the gym's website: The system is capable of connecting to the gym's website and navigating through relevant pages for data extraction.
- Frequency data collection: Using web scraping techniques, the system identifies relevant elements on the website, such as attendance for the selected period (today, yesterday, current month, last month, current week, last week, etc.).
- Data storage: The extracted data is organized and stored in a XLSX file, for further analysis.
- Automated scheduling: The system can be configured to perform data extraction at regular intervals (daily, weekly, etc.), allowing continuous updates of frequency data.
- Trend analysis: In addition to data extraction, the project can include analysis modules that enable the identification of patterns and trends over time, providing valuable information for gym management.
- Efficient automation: Manual extraction of frequency data can be laborious and error-prone, while the project offers an automated and reliable method.
- Informed decision-making: With access to accurate participant frequency data, gym administration can make more informed decisions regarding peak hours, resource planning, and customer retention strategies.
- Improved operational efficiency: With insights into facility demand and usage, it is possible to optimize resource allocation and enhance the overall efficiency of the gym.
 Bruno Cavalcanti Santos |
 Victor Gomes |
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