X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/blobdiff_plain/f28effe2c38ce2f7656901861c90e36fdfcdb04c..c0da8f4dbfc62b3b8af0212281eb219d14079d1e:/tf_comments.py diff --git a/tf_comments.py b/tf_comments.py old mode 100644 new mode 100755 index 85eebec..211647e --- a/tf_comments.py +++ b/tf_comments.py @@ -1,3 +1,4 @@ +#!/usr/bin/env python3 import pyarrow as pa import pyarrow.dataset as ds import pyarrow.parquet as pq @@ -35,6 +36,7 @@ def weekly_tf(partition, mwe_pass = 'first'): batches = dataset.to_batches(columns=['CreatedAt','subreddit','body','author']) + schema = pa.schema([pa.field('subreddit', pa.string(), nullable=False), pa.field('term', pa.string(), nullable=False), pa.field('week', pa.date32(), nullable=False), @@ -64,7 +66,16 @@ def weekly_tf(partition, mwe_pass = 'first'): subreddit_weeks = groupby(rows, lambda r: (r.subreddit, r.week)) - mwe_tokenize = MWETokenizer().tokenize + if mwe_pass != 'first': + mwe_dataset = pd.read_feather(f'/gscratch/comdata/users/nathante/reddit_multiword_expressions.feather') + mwe_dataset = mwe_dataset.sort_values(['phrasePWMI'],ascending=False) + mwe_phrases = list(mwe_dataset.phrase) + mwe_phrases = [tuple(s.split(' ')) for s in mwe_phrases] + mwe_tokenizer = MWETokenizer(mwe_phrases) + mwe_tokenize = mwe_tokenizer.tokenize + + else: + mwe_tokenize = MWETokenizer().tokenize def remove_punct(sentence): new_sentence = [] @@ -119,8 +130,11 @@ def weekly_tf(partition, mwe_pass = 'first'): else: # remove stopWords + sentences = map(mwe_tokenize, sentences) sentences = map(lambda s: filter(lambda token: token not in stopWords, s), sentences) - return chain(* sentences) + for sentence in sentences: + for token in sentence: + yield token def tf_comments(subreddit_weeks): for key, posts in subreddit_weeks: @@ -142,19 +156,19 @@ def weekly_tf(partition, mwe_pass = 'first'): outchunksize = 10000 - with pq.ParquetWriter("/gscratch/comdata/users/nathante/reddit_tfidf_test.parquet_temp/{partition}",schema=schema,compression='snappy',flavor='spark') as writer, pq.ParquetWriter("/gscratch/comdata/users/nathante/reddit_tfidf_test_authors.parquet_temp/{partition}",schema=author_schema,compression='snappy',flavor='spark') as author_writer: + with pq.ParquetWriter(f"/gscratch/comdata/users/nathante/reddit_tfidf_test.parquet_temp/{partition}",schema=schema,compression='snappy',flavor='spark') as writer, pq.ParquetWriter(f"/gscratch/comdata/users/nathante/reddit_tfidf_test_authors.parquet_temp/{partition}",schema=author_schema,compression='snappy',flavor='spark') as author_writer: + while True: + chunk = islice(outrows,outchunksize) + chunk = (c for c in chunk if c.subreddit is not None) pddf = pd.DataFrame(chunk, columns=["is_token"] + schema.names) - print(pddf) - author_pddf = pddf.loc[pddf.is_token == False] + + author_pddf = pddf.loc[pddf.is_token == False, schema.names] + 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] - - pddf = pddf.loc[pddf.is_token == True, schema.names] - print(pddf) - print(author_pddf) table = pa.Table.from_pandas(pddf,schema=schema) author_table = pa.Table.from_pandas(author_pddf,schema=author_schema) if table.shape[0] == 0: @@ -166,12 +180,12 @@ def weekly_tf(partition, mwe_pass = 'first'): author_writer.close() -def gen_task_list(): +def gen_task_list(mwe_pass='first'): files = os.listdir("/gscratch/comdata/output/reddit_comments_by_subreddit.parquet/") with open("tf_task_list",'w') as outfile: for f in files: if f.endswith(".parquet"): - outfile.write(f"source python3 tf_comments.py weekly_tf {f}\n") + outfile.write(f"python3 tf_comments.py weekly_tf --mwe-pass {mwe_pass} {f}\n") if __name__ == "__main__": fire.Fire({"gen_task_list":gen_task_list,