Add code for running tf-idf at the weekly level.

[cdsc_reddit.git] / tf_comments.py

diff --git a/tf_comments.py b/tf_comments.py
index cb3b6288c37079b20f5355cbdf54d28bf1f29495..526bac2bdabe284ec9550bfe290cadb13e438a1b 100755 (executable)
--- a/tf_comments.py
+++ b/tf_comments.py
@@ -1,11 +1,11 @@
 #!/usr/bin/env python3
+import pandas as pd
 import pyarrow as pa
 import pyarrow.dataset as ds
 import pyarrow.parquet as pq
 from itertools import groupby, islice, chain
 import fire
 from collections import Counter
-import pandas as pd
 import os
 import datetime
 import re
@@ -22,7 +22,6 @@ urlregex = re.compile(r"[-a-zA-Z0-9@:%._\+~#=]{1,256}\.[a-zA-Z0-9()]{1,6}\b([-a-
 # compute term frequencies for comments in each subreddit by week
 def weekly_tf(partition, mwe_pass = 'first'):
     dataset = ds.dataset(f'/gscratch/comdata/output/reddit_comments_by_subreddit.parquet/{partition}', format='parquet')
-
     if not os.path.exists("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/"):
         os.mkdir("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/")
 
@@ -31,8 +30,9 @@ def weekly_tf(partition, mwe_pass = 'first'):
 
     ngram_output = partition.replace("parquet","txt")
 
-    if os.path.exists(f"/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/{ngram_output}"):
-        os.remove(f"/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/{ngram_output}")
+    if mwe_pass == 'first':
+        if os.path.exists(f"/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/{ngram_output}"):
+            os.remove(f"/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/{ngram_output}")
     
     batches = dataset.to_batches(columns=['CreatedAt','subreddit','body','author'])
 
@@ -167,14 +167,20 @@ def weekly_tf(partition, mwe_pass = 'first'):
             pddf = pddf.loc[pddf.is_token == True, schema.names]
             author_pddf = author_pddf.rename({'term':'author'}, axis='columns')
             author_pddf = author_pddf.loc[:,author_schema.names]
-
             table = pa.Table.from_pandas(pddf,schema=schema)
             author_table = pa.Table.from_pandas(author_pddf,schema=author_schema)
-            if table.shape[0] == 0:
+            do_break = True
+
+            if table.shape[0] != 0:
+                writer.write_table(table)
+                do_break = False
+            if author_table.shape[0] != 0:
+                author_writer.write_table(author_table)
+                do_break = False
+
+            if do_break:
                 break
-            writer.write_table(table)
-            author_writer.write_table(author_table)
-            
+
         writer.close()
         author_writer.close()