The UX of a blacklist with a half billion entries would be so crippling that it would cause a user revolt.
Most people's password-selection strategies are similar enough to other people's (like kbenson's 4000+ hit) that they could spend hours trying to come up with a password that has never been leaked before.
I tried to encourage Troy to suggest to implementors that blacklisting all passwords was a Bad Idea. Instead, he doubled down:
https://twitter.com/TychoTithonus/status/966400790221930496
Please don't use the entire list for blacklisting unless you actively also guide the user in how to generate a random passphrase (if a human must remember it) or a random password (if it will be stored in a password manager).
Instead:
1. Use a high-level password-strength assessment widget like zxcvbn:
https://github.com/dropbox/zxcvbn
2. Configure a blacklist with, say, 10K or 20K of the most common passwords.
3. Hash passwords with bcrypt cost 12 (adjusted to your platform's hashrate capabilities), scrypt, or the appropriate method from the Argon2 family.
But for all that is holy, please don't use Troy's entire corpus - or even the first million - as a blacklist. To quote the old NANOG saw, I encourage all of my competitors to use it. ;)
Edit: And since Troy's API at this writing does not support only querying the top X passwords, there's no way to use the API while avoiding the UX nightmare. So if you want to use this data in a professional manner, but don't want to download the entire corpus, here are the first 20K from his list (of which I've only personally cracked 19965 so far, interestingly; gist will be updated once I get all 20K):
https://gist.github.com/roycewilliams/281ce539915a947a23db17...
Edit 2: Preliminary results indicate that this data may be dirty. The 273rd most common password, according to Troy, is '$HEX'. This is almost certainly an import/conversion artifact, since the '$HEX' prefix is how most cracking suites escape non-ASCII or passwords that contain colons. I expect that there will be more artifacts. Use the data with caution.