diff --git a/languedoc.py b/languedoc.py
--- a/languedoc.py
+++ b/languedoc.py
@@ -3,11 +3,12 @@ import re
 import random
 import itertools
 
+from shared import identify, extract_ngram_freqs, TOP_NGRAM_COUNT
+
 random.seed(19181028)
 
 CROSSVALIDATION_SOURCE_COUNT = 5
 TEST_LENS = [8, 16, 32, 64]
-TOP_NGRAM_COUNT = 6000
 
 
 def preprocess(text):
@@ -15,22 +16,6 @@ def preprocess(text):
 	return text.lower()
 
 
-def extract_ngram_freqs(text, k):
-	n = len(text)
-	d = dict()
-
-	for i in range(0, n-k+1):
-		key = text[i:i+k]
-		if key.isspace():
-			continue
-
-		d[key] = d.get(key, 0) + 1
-
-	count = sum(d.values())
-
-	return {key: val/count for (key, val) in d.items()}
-
-
 def merge_ngram_freqs(freqs):
 	n = len(freqs)
 	res = dict()
@@ -141,12 +126,6 @@ def cross_validate(sample_sets):
 	return score / max_score, (score, max_score)
 
 
-def identify(text, models):
-	sample = Sample(text=text)
-
-	return min(map(lambda m: (m.compare(sample), m.language), models))[1]
-
-
 DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 LANG_DIRS = sorted([x.path for x in os.scandir(DATA_DIR)])
 
diff --git a/shared.py b/shared.py
new file mode 100644
--- /dev/null
+++ b/shared.py
@@ -0,0 +1,70 @@
+import itertools
+
+TOP_NGRAM_COUNT = 5000
+
+
+def extract_ngram_freqs(text, k):
+	n = len(text)
+	d = dict()
+
+	for i in range(0, n-k+1):
+		key = text[i:i+k]
+		if key.isspace():
+			continue
+
+		d[key] = d.get(key, 0) + 1
+
+	count = sum(d.values())
+
+	return {key: val/count for (key, val) in d.items()}
+
+
+class Sample:
+	def __init__(self, language="??", text=""):
+		self.language = language
+		self.frequencies = dict()
+		self._ranked_ngrams = dict()
+
+		if text:
+			self._extract(text)
+
+	def _extract(self, text):
+		for k in range(1, 4):
+			self.frequencies.update(extract_ngram_freqs(text, k))
+
+	@property
+	def ranked_ngrams(self):
+		if not self._ranked_ngrams:
+			ordered_ngrams = sorted(self.frequencies.items(), key=lambda kv: -kv[1])[:TOP_NGRAM_COUNT]
+			self._ranked_ngrams = dict(zip([key for (key, freq) in ordered_ngrams], itertools.count(0)))
+
+		return self._ranked_ngrams
+
+	def compare(self, other):
+		"""take k most common
+		use frequencies x order
+		use letter, digrams, trigrams
+		use absolute x square"""
+		"""make a set difference of keys, multiply its size by the max score"""
+		res = sum(abs(v-other.ranked_ngrams.get(k, len(other.ranked_ngrams))) for (k, v) in self.ranked_ngrams.items()) + \
+					sum(abs(v-self.ranked_ngrams.get(k, len(self.ranked_ngrams))) for (k, v) in other.ranked_ngrams.items())
+
+		return res
+
+	def print_overview(self):
+		print(f"Sample({self.language}):")
+
+		for freqs in self.frequencies:
+			x = [
+				(k, round(v, 3))
+				for (k, v) in sorted(freqs.items(), key=lambda kv: -kv[1])
+			]
+			print("  ", x[:8], "...", x[-8:])
+
+		print()
+
+
+def identify(text, models):
+	sample = Sample(text=text)
+
+	return sorted(models, key=lambda m: m.compare(sample))[0].language