added plot close to free memory

keyphrase_extraction.py

@@ -33,10 +33,12 @@ def get_top_key_phrases(text, top_n, save_output):
     phrases = list(zip(*phrases_ranking.items()))[0]
     scores = list(zip(*phrases_ranking.items()))[1]
     keyword_df = pd.DataFrame({'words': phrases[:top_n], 'scores': scores[:top_n]})
+    plt.title("Word Count")
     plt.figure(figsize=(8, 24))
     sns.catplot(data=keyword_df, x='words', y='scores', kind='bar', palette='blend:#7AB,#EDA', aspect=1.5)
     plt.xticks(rotation=-10, fontsize=6)
     plt.savefig(save_output, dpi=300)
+    plt.close()
 
 def display_key_phrases(text, save_output):
     doc = nlp(text)

keyword_extraction.py

@@ -36,10 +36,12 @@ def keyword_extract(doc, kw_model, n_grams, save_output='results/'):
     words = list(zip(*keyword_onegram))[0]
     scores = list(zip(*keyword_onegram))[1]
     keyword_df = pd.DataFrame({'words': words, 'scores': scores})
+    plt.title("Word Count")
     plt.figure(figsize=(8, 24))
     sns.catplot(data=keyword_df, x='words', y='scores', kind='bar', palette='blend:#7AB,#EDA', aspect=1.5)
     plt.xticks(rotation=-10, fontsize=6)
     plt.savefig(save_output, dpi=300)
+    plt.close()
 
 if __name__ == '__main__':
     kw_model = KeyBERT()

word.py

@@ -32,10 +32,13 @@ def show_gram_plot(doc, n_grams, top_words=10, save_output='results/'):
     count_tokens = Counter(tokens).most_common(top_words)
     words, count = zip(*count_tokens)
     tokens_df = pd.DataFrame({'word': words, 'count': count})
+    plt.title("Word Count")
     plt.figure(figsize=(8, 24))
     sns.catplot(data=tokens_df, x='word', y='count', kind='bar', palette='blend:#7AB,#EDA')
     plt.xticks(rotation=-10, fontsize=6)
     plt.savefig(save_output, dpi=300)
+    plt.close()
+
 
 if __name__ == '__main__':
     lemmatized_docs = preprocess_text([doc])