exercises.md

Possible Exercises

Document Summary

Use the following algorithm to add a Summarize(text string, count int) []string method to our nlp package.

1. For every word in the sentence count how many times it appears in the document.
   • This is known as token frequency or tf.
2. For every sentence in the document, give is a score which is the sum of all the token frequencies for the tokens in the sentence.
   • e.g. if we have the following token frequencies: please=1, reinstall=3, universe=3, and=10, reboot=2. Then the score of the sentence Please reinstall universe and reboot is 1 + 3 + 3 + 10 + 2 = 19
3. Return the count top scored sentences (this is known as sentence extraction)

Tasks

• Test your function. Have directory with texts to summarize and expected output.
• Create testable example for Summarize
• Create a benchmark for your server under load, you can use vegeta to generate load
• Tag a new version of your code. Create a test to see it's go getable
• Publish a docker image for nlpd to docker hub
• Add gRPC front end nlpd. Have an option to run either HTTP server or gRPC or both.
  • Make sure metrics still work in gRPC only mode
• Head over to godoc and check how your package documentation looks. See it in the eyes of a new user and fix it
• Use http/httptest to test your HTTP handlers

Publish

• Build nlpd executable for Linux, Windows & OSX
• Create a CI for your project. You can use CircleCI or travis
• Add a CI badge to your project README.md
• Have the CI job embed build nlpd with version from git tag