Python NLP: TypeError: not all arguments converted during string formatting

Question

I tried the code on "Processing natural language with python", but a type error occurred.

import nltk from nltk.corpus import brown suffix_fdist = nltk.FreqDist() for word in brown.words(): word = word.lower() suffix_fdist.inc(word[-1:]) suffix_fdist.inc(word[-2:]) suffix_fdist.inc(word[-3:]) common_suffixes = suffix_fdist.items()[:100] def pos_features(word): features = {} for suffix in common_suffixes: features['endswith(%s)' % suffix] = word.lower().endswith(suffix) return features pos_features('people') 

error below:

 Traceback (most recent call last): File "/home/wanglan/javadevelop/TestPython/src/FirstModule.py", line 323, in <module> pos_features('people') File "/home/wanglan/javadevelop/TestPython/src/FirstModule.py", line 321, in pos_features features['endswith(%s)' % suffix] = word.lower().endswith(suffix) TypeError: not all arguments converted during string formatting 

Can anyone help me find out where I am going wrong?

Answer 1

suffix is a tuple because .items() returns (key, value) tuples. When you use%, if the right side is a tuple, the values ​​will be unpacked and replaced for each% format in order. The error you get complains that the tuple has more records than% formats.

You probably only need the key (the actual suffix), in which case you should use suffix[0] or .keys() only to get the dictionary keys.