Python3 SQLAlchemy Alembic SQLite Pandas Requests
I created Strava CLI at the end of Phase 3 while attending the Flatiron School bootcamp. One of the constraints my instructor imposed was that we build a Python application with a command line interface. As an avid Strava user myself, my idea was to comprise a database of personal, live data that can be synced regularly. It is the culmination of a 3 week journey of learning Python. My focus was on leveraging the power of Object Oriented Programming to control & transform data, utilizing an Object Relational Mapping methodology and making use of SQL to communicate with a database. Here is a diagram of the relationships established between the tables for this project:
The application utilizes the publicly available Strava API for fetching profile and activities data into the application with the help of Requests module. The data is then stored locally in a SQLite database. SQL queries and commands are handled through the powerful module SQLAlchemy. Version control on DB was implemented through Alembic. With the help of Pandas module, I then used the data to aggregate some additional stats that are not part of the original Strava app.
❖ Building a React Frontend
❖ Creating a sign up/login workflow that obtains an API token
❖ Upgrading the database to PostgreSQL
❖ Deployment
Upon starting the app, the user is asked to select a username from a list. Then, they are presented with 6 main options:
These will be henceforth referred to as top-level options.
Upon selecting the first top-level option, the user is presented with information about the selected profile, like so:
❖ An option to edit profile details is offered, which allows change to weight, bio and location. Changes are reflected in database.
Upon selecting the second top-level option, the user is presented with information about aggregated stats sorted and displayed by the type of activity, like so:
❖ This is a feature that is not offered by the Strava API.
Upon selecting the third top-level option, the user is presented with a choice between:
❖ Viewing All Achievements - this is a list of all achievements that have been created in the database with various parameters. Upon selecting this option, the list with each earnable Achievement's name appears.
❖ Viewing Achievements Earned specific to the profile:
❖ This option is referencing a table that is a join of 3 others: Profile, Activities & Achievements.
❖ To "earn" an achievement a user needs to upload/complete an activity that satisfies certain criteria as described in the Achievement.
Upon selecting the fourth top-level option, the user is presented with a choice between:
❖ Viewing All Activities - this is a list of all activities uploaded by the user and stored in the database.
❖ Viewing Activities by Type - this is a list of activities filtered by Activity Type. Another option is presented for selection of Activity Type.
❖ Viewing Last 10 Activities - this is a list of the last 10 uploaded activities.
Upon selecting the fifth top-level option, a function is fired that fetches new data, recalculates and repopulates the tables so that they are up-to-date with the data from Strava. User is then prompted to restart the app to load the updated data. A Last Updated indicator is presented on the same line for user's consideration.
Bye Felicia!
You're welcome to explore the app through Github or fork/clone it to test yourself. Below are the steps for running the app on your local machine:
❖ Before you start, make sure you obtain your own Strava API Key
❖ Clone/fork the repo.
❖ After you've done so, make sure you are running Python 3.11
❖ Navigate to the Root folder where the Pipfile file is located.
❖ Run pipenv install then enter the shell with pipenv shell
❖ Type python main.py to start the application.
Please reach out if you have suggestions, run into hurdles or have questions regarding the setup.