datasets/: stage new layer before touching live datasets in add_months

Replace mode='append'-direct-to-live approach with a safer staging
workflow: Part 2 writes the new sorted layer to temp staging directories,
the user verifies, then a separate copy step adds the files to the live
datasets. Live datasets are never touched until the copy step, and the
copy only adds files — nothing is deleted or overwritten.

- sort_and_write gains out_by_subreddit/out_by_author params (replaces
  mode param) so Part 2 can target staging paths
- comments_part2.py, submissions_part2.py: expose new params via Fire
- add_months.sh: rewritten with explicit staging dirs, verify checkpoint,
  and find-based copy step

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

datasets/dumps_helper.py

@@ -256,13 +256,14 @@ def gen_task_list(config, script_name, dumpdir=None, tasklist=None):
 
 # --- Part 2: spark sort + repartition --------------------------------------
 
-def sort_and_write(config, indir=None, mode='overwrite'):
+def sort_and_write(config, indir=None, out_by_subreddit=None, out_by_author=None):
     """Read a directory of per-source parquets, sort and repartition twice
-    (once by subreddit, once by author), and write the two final datasets.
+    (once by subreddit, once by author), and write the two output datasets.
 
-    indir defaults to config['outdir']. mode is passed to parquet write and
-    may be 'overwrite' (default, used by build_from_scratch) or 'append'
-    (used by add_months to layer new data alongside existing files).
+    indir defaults to config['outdir'].
+    out_by_subreddit and out_by_author default to config['output_by_subreddit']
+    and config['output_by_author']. Override them to write to staging directories
+    instead of the live datasets (see add_months.sh).
 
     Pyspark is imported lazily so Part 1 callers don't pay the Spark startup
     cost.
@@ -270,6 +271,9 @@ def sort_and_write(config, indir=None, mode='overwrite'):
     from pyspark.sql import SparkSession, functions as f
 
     indir = indir or config['outdir']
+    out_by_subreddit = out_by_subreddit or config['output_by_subreddit']
+    out_by_author = out_by_author or config['output_by_author']
+
     spark = SparkSession.builder.appName(config['app_name']).getOrCreate()
 
     df = spark.read.parquet(indir, compression='snappy')
@@ -286,12 +290,12 @@ def sort_and_write(config, indir=None, mode='overwrite'):
     sub_keys = config['subreddit_sort_keys']
     df_sub = df.repartition('subreddit').sort(sub_keys, ascending=True)
     df_sub = df_sub.sortWithinPartitions(sub_keys, ascending=True)
-    df_sub.write.parquet(config['output_by_subreddit'], mode=mode, compression='snappy')
+    df_sub.write.parquet(out_by_subreddit, mode='overwrite', compression='snappy')
 
     auth_keys = config['author_sort_keys']
     df_auth = df.repartition('author').sort(auth_keys, ascending=True)
     df_auth = df_auth.sortWithinPartitions(auth_keys, ascending=True)
-    df_auth.write.parquet(config['output_by_author'], mode=mode, compression='snappy')
+    df_auth.write.parquet(out_by_author, mode='overwrite', compression='snappy')
 
 
 def merge_layers(config):