When using the scikit-learn library in Python, I can use the CountVectorizer to create ngrams of a desired length (e.g. 2 words) like so: from sklearn.metrics.
atomikos
db-schema
abstractverticle
clouddb
exchange-server
google-dl-platform
openshift
full-expression
elasticsearch-aggregation">elasticsearch-aggregation
memcachedb
virtual-earth
materialize
autodiff
authprovider
drive
tfs-power-tools
nuxt-strapi
browsable
uiscrollview
maximize
semgrep
c99
xcode-server-bots
adaptive-user-interfaces
mutated
telerik-scheduler
devilbox
pls-00103
rogue-wave
ssh2-exec