Spacy Lemmatizer Issue/consistency

I'm currently using spaCy for NLP purpose (mainly lemmatization and tokenization). The model used is en-core-web-sm (2.1.0). The following code is run to retrieve a list of words

Solution 1:

The issue was analysed by the spaCy team and they've come up with a solution. Here's the fix : https://github.com/explosion/spaCy/pull/3646

Basically, when the lemmatization rules were applied, a set was used to return a lemma. Since a set has no ordering, the returned lemma could change in between python session.

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For example in my case, for the noun "leaves", the potential lemmas were "leave" and "leaf". Without ordering, the result was random - it could be "leave" or "leaf".