Online version of scikit-learn's TfidfVectorizer
Intrinsically you can not use TF IDF in an online fashion, as the IDF of all past features will change with every new document - which would mean re-visiting and re-training on all the previous documents, which would no-longer be online. 
There may be some approximations, but you would have to implement them yourself.
I'm looking to use scikit-learn's HashingVectorizer because it's a great fit for online learning problems (new tokens in text are guaranteed to map to a "bucket").  Unfortunately the implementation included in scikit-learn doesn't seem to include support for tf-idf features.  Is passing the vectorizer output through a TfidfTransformer the only way to make online updates work with tf-idf features, or is there a more elegant solution out there?