#!/usr/bin/env python3

# two stages:
# 1. from gz to arrow parquet (this script) 
# 2. from arrow parquet to spark parquet (submissions_2_parquet_part2.py)

import json
from datetime import datetime
from multiprocessing import Pool
from itertools import islice
from helper import find_dumps, open_fileset
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq


def parse_submission(post, names = None):
    if names is None:
        names = ['id','author','subreddit','title','created_utc','permalink','url','domain','score','ups','downs','over_18','has_media','selftext','retrieved_on','num_comments','gilded','edited','time_edited','subreddit_type','subreddit_id','subreddit_subscribers','name','is_self','stickied','quarantine','error']

    try:
        post = json.loads(post)
    except (json.decoder.JSONDecodeError, UnicodeDecodeError) as e:
        #        print(e)
        #        print(post)
        row = [None for _ in names]
        row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,post)
        return tuple(row)

    row = []

    for name in names:
        if name == 'created_utc' or name == 'retrieved_on':
            val = post.get(name,None)
            if val is not None:
                row.append(datetime.fromtimestamp(int(post[name]),tz=None))
            else:
                row.append(None)
        elif name == 'edited':
            val = post[name]
            if type(val) == bool:
                row.append(val)
                row.append(None)
            else:
                row.append(True)
                row.append(datetime.fromtimestamp(int(val),tz=None))
        elif name == "time_edited":
            continue
        elif name == 'has_media':
            row.append(post.get('media',None) is not None)

        elif name not in post:
            row.append(None)
        else:
            row.append(post[name])
    return tuple(row)

dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/submissions"

files = list(find_dumps(dumpdir))

pool = Pool(28)

stream = open_fileset(files)

N = 100000

rows = pool.imap_unordered(parse_submission, stream, chunksize=int(N/28))

schema = pa.schema([
    pa.field('id', pa.string(),nullable=True),
    pa.field('author', pa.string(),nullable=True),
    pa.field('subreddit', pa.string(),nullable=True),
    pa.field('title', pa.string(),nullable=True),
    pa.field('created_utc', pa.timestamp('ms'),nullable=True),
    pa.field('permalink', pa.string(),nullable=True),
    pa.field('url', pa.string(),nullable=True),
    pa.field('domain', pa.string(),nullable=True),
    pa.field('score', pa.int64(),nullable=True),
    pa.field('ups', pa.int64(),nullable=True),
    pa.field('downs', pa.int64(),nullable=True),
    pa.field('over_18', pa.bool_(),nullable=True),
    pa.field('has_media',pa.bool_(),nullable=True),
    pa.field('selftext',pa.string(),nullable=True),
    pa.field('retrieved_on', pa.timestamp('ms'),nullable=True),
    pa.field('num_comments', pa.int64(),nullable=True),
    pa.field('gilded',pa.int64(),nullable=True),
    pa.field('edited',pa.bool_(),nullable=True),
    pa.field('time_edited',pa.timestamp('ms'),nullable=True),
    pa.field('subreddit_type',pa.string(),nullable=True),
    pa.field('subreddit_id',pa.string(),nullable=True),
    pa.field('subreddit_subscribers',pa.int64(),nullable=True),
    pa.field('name',pa.string(),nullable=True),
    pa.field('is_self',pa.bool_(),nullable=True),
    pa.field('stickied',pa.bool_(),nullable=True),
    pa.field('quarantine',pa.bool_(),nullable=True),
    pa.field('error',pa.string(),nullable=True)])

with  pq.ParquetWriter("/gscratch/comdata/output/reddit_submissions.parquet_temp",schema=schema,compression='snappy',flavor='spark') as writer:
    while True:
        chunk = islice(rows,N)
        pddf = pd.DataFrame(chunk, columns=schema.names)
        table = pa.Table.from_pandas(pddf,schema=schema)
        if table.shape[0] == 0:
            break
        writer.write_table(table)

    writer.close()