Writing to partitioned dataset using the writer

I'm trying to overwrite a table using data from another table (with the same schema). I keep running into the issue that both datasets are partitioned and the writer does not like that (same case with the copy_to function).

Here is what I'm trying to do:

ERROR:dataiku.core.dataset_write:Exception caught while writing
Traceback (most recent call last):
  File "/data/dataiku/install/dataiku-dss-12.3.1/python/dataiku/core/dataset_write.py", line 353, in run
    self.streaming_api.wait_write_session(self.session_id)
  File "/data/dataiku/install/dataiku-dss-12.3.1/python/dataiku/core/dataset_write.py", line 296, in wait_write_session
    raise Exception(u'An error occurred during dataset write (%s): %s' % (id, decoded_resp["message"]))
Exception: An error occurred during dataset write (D9uuBrAH9P): RuntimeException: A partition ID must be provided, because the dataset myproject.target_table is partitioned

I'm getting this error, even though I would think the writer has a partition because of the "set_write_partition":

# Set the datasets
dataset_target = dataiku.Dataset(dataset, project_key=project_key_target)
dataset_source = dataiku.Dataset(dataset, project_key=project_key_source)

# Overwrite target dataset with source data
with dataset_target.get_writer() as writer:
  for p in dataset_source.list_partitions():
    dataset_source.read_partitions = [p]
    df = dataset_source.get_dataframe()
    dataset_target.set_write_partition(str(p))
    writer.write_dataframe(df)
  writer.close()

Does anyone know how I could resolve this? I also though about subverting the issue by removing the partitioning from the datasets altogether and replacing them after the copy but can imagine more going wrong there so would like to avoid that if possible.

Any help is appreciated, thanks in advance!