initial commit

wordplay/wordplay.py

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+import gensim.downloader
+
+EMBEDDING_MODELS = {
+    'small':  'glove-wiki-gigaword-100',   # ~128 MB
+    'medium': 'glove-wiki-gigaword-300',   # ~376 MB
+    'large':  'word2vec-google-news-300',  # ~1.6 GB
+}
+
+
+def load_embeddings(size='small'):
+    "Download (if needed) and load the embedding model for the given size."
+    return gensim.downloader.load(EMBEDDING_MODELS[size])
+
+
+def synonyms(model, word, n=5):
+    pass
+
+
+def average(model, word1, word2):
+    pass
+
+
+def outlier(model, words):
+    pass
+
+
+def sort(model, words):
+    pass