- Assumes user has a command line with capability to run Bash scripts
- Assumes user has Python 3 installed. Python script has not been tested with Python 2.
- User has access to Twitter API and has authorized
twurl
- User has libraries.io API key
Set the following environment variables to the appropriate values
TWITTER_HANDLE
- the Twitter handle of the account you want to followLIB_IO_API_KEY
- your libraries.io API keyPYPI_PACKAGE
- the PyPI package you'd like info aboutGITHUB_ORG
- the GitHub organization of the repo you are exploringGITHUB_REPO
- the GitHub repo you are exploring
Optional environment variables
GITHUB_ORG_COMPARE
- the name of a second GitHub org you're using when comparing statsGITHUB_REPO_COMPARE
- the name of a second GitHub repo (in theGITHUB_ORG_COMPARE
org)
Clone this repo and change into the directory. Once you've set the environment variables in the Setup section, run the project-stats script with the following command:
bash project-stats.sh
Note: The when the project-stats.sh
script is run, the results are saved in JSON files in a folder named with today's date, in a subdirectory named for the Epoch time that the stats were gathered - one for each curl command in the script. See the limitations section for more info about possible pain points regarding those files. If you want these files saved in a different location, either modify the script, or call the script from the location where you'd like them saved.
When the command has finshed running, you can explore your data manually.
Or, you can run a python script that prints out some aggregate statistics. This script is a work in progress, and its limitations are noted. To run the Python script, run:
python gather-stats.py
- As long as the curl command is valid, it will execute. If the command returns an error response, that will be printed in the *.json file.
- The output files of project-stats.sh will be in a folder named with today's date in YYYY-MM-DD format. If that folder does not exist, it will be created. If it does exist, it will be used. This may not be the best place. Feel free to adjust the output location and modify the script as you see fit. The output files will be in a subdirectory within that folder named for the Epoch time value the stats were collected at - this is done to avoid collision.Feel free to use an Epoch time converter if you need to see precisely what time that file was created.
- Python script only prints values, it does not save the aggregate values anywhere for future consumption.
Please open up issues and submit PRs, but know that this is a side project and may not be addressed in a timely fashion.