The goal of this project is to raise awareness of the level of carbon emissions emitted by ultra-wealthy individuals, with the ultimate goal of discouraging such emission-intensive behavior. This will be accomplished by scheduling automated collection of data from publicly available flight logs of wealthy individuals, feeding that data through a calculator, and posting to a social media account a record of the amount of carbon emitted into the atmosphere.
A “nice-to-have” bit of additional functionality would include a comparison to a more relatable form of carbon emission. An example social media post might read: “Warren Buffet just put 45 tons of CO2 into the atmosphere flying from Omaha to Nashville. That’s the equivalent of driving from Los Angeles to New York 3 times.”
If you are using this code and come across any bugs, please feel free to report them by creating an issue in Github and applying the "bug" label.
If you would like to commit to this repository, please feel free to create your own fork. Pull Requests from forked branches will be reviewed thoroughly before merging.
Make sure you have Docker installed. In the root directory of the project, run docker build ..
Then run docker images and copy the ID of the image you've just created.
Finally, run docker run -it --mount type=bind,source=${PWD},target=/project IMAGEID_GOES_HERE bash to create the container.
This will bind your local /app directory with the /app directory in the container and present you with a bash shell within the Docker container.
In the Docker bash shell, navigate to the /app folder.
The current iteration of this software runs on stand-in data and allows the user to specify which test data to run the script with. Valid arguments are:
- test_data_1
- test_data_2
- test_data_3
- test_data_4
A command that specifies which data object to use would look like this: python main.py test_data_1. Alternatively, if no arugment is supplied, the program will select from the four options at random. If the script is successful, it will output the unique URL of the X/twitter post created.
Note: because X/twitter does not allow word-for-word duplicate posts, each execution of the script has a chance of failing if the post text generated is the same as an existing post.