diff --git a/beam/pipelines.py b/beam/pipelines.py
new file mode 100644
index 0000000..2563d7f
--- /dev/null
+++ b/beam/pipelines.py
@@ -0,0 +1,162 @@
+"""Various opinionated Beam pipelines for testing different functionality."""
+
+import apache_beam as beam
+from apache_beam.coders import coders
+from . import arrayrecordio
+from . import dofns
+from . import example
+from . import options
+
+
+## Grab CLI arguments.
+## Override by passing args/pipeline_options to the function manually.
+def_args, def_pipeline_options = options.get_arguments()
+
+
+def example_to_tfrecord(
+    num_shards=1,
+    args=def_args,
+    pipeline_options=def_pipeline_options):
+  """Beam pipeline for creating example TFRecord data.
+
+  Args:
+    num_shards: Number of files
+    args: Custom arguments
+    pipeline_options: Beam arguments in dict format
+
+  Returns:
+    Beam Pipeline object
+  """
+
+  p1 = beam.Pipeline(options=pipeline_options)
+  initial = (p1
+             | 'Create' >> beam.Create(example.generate_movie_examples())
+             | 'Write' >> beam.io.WriteToTFRecord(
+                 args['output'],
+                 coder=coders.ToBytesCoder(),
+                 num_shards=num_shards,
+                 file_name_suffix='.tfrecord'))
+
+  return p1, initial
+
+
+def example_to_arrayrecord(
+    num_shards=1,
+    args=def_args,
+    pipeline_options=def_pipeline_options):
+  """Beam pipeline for creating example ArrayRecord data.
+
+  Args:
+    num_shards: Number of files
+    args: Custom arguments
+    pipeline_options: Beam arguments in dict format
+
+  Returns:
+    Beam Pipeline object
+  """
+
+  p1 = beam.Pipeline(options=pipeline_options)
+  initial = (p1
+             | 'Create' >> beam.Create(example.generate_movie_examples())
+             | 'Write' >> arrayrecordio.WriteToArrayRecord(
+                 args['output'],
+                 coder=coders.ToBytesCoder(),
+                 num_shards=num_shards,
+                 file_name_suffix='.arrayrecord'))
+
+  return p1, initial
+
+
+def convert_tf_to_arrayrecord_disk(
+    num_shards=1,
+    args=def_args,
+    pipeline_options=def_pipeline_options):
+  """Convert TFRecords to ArrayRecords using sink/sharding functionality.
+
+  THIS ONLY WORKS FOR DISK ARRAYRECORD WRITES
+
+  Args:
+    num_shards: Number of files
+    args: Custom arguments
+    pipeline_options: Beam arguments in dict format
+
+  Returns:
+    Beam Pipeline object
+  """
+
+  p1 = beam.Pipeline(options=pipeline_options)
+  initial = (p1
+             | 'Read TFRecord' >> beam.io.ReadFromTFRecord(args['input'])
+             | 'Write ArrayRecord' >> arrayrecordio.WriteToArrayRecord(
+                 args['output'],
+                 coder=coders.ToBytesCoder(),
+                 num_shards=num_shards,
+                 file_name_suffix='.arrayrecord'))
+
+  return p1, initial
+
+
+def convert_tf_to_arrayrecord_disk_match_shards(
+    args=def_args,
+    pipeline_options=def_pipeline_options):
+  """Convert TFRecords to matching number of ArrayRecords.
+
+  THIS ONLY WORKS FOR DISK ARRAYRECORD WRITES
+
+  Args:
+    args: Custom arguments
+    pipeline_options: Beam arguments in dict format
+
+  Returns:
+    Beam Pipeline object
+  """
+
+  p1 = beam.Pipeline(options=pipeline_options)
+  initial = (p1
+             | 'Start' >> beam.Create([args['input']])
+             | 'Read' >> beam.io.ReadAllFromTFRecord(with_filename=True))
+
+  file_count = (initial
+                | 'Group' >> beam.GroupByKey()
+                | 'Count Shards' >> beam.combiners.Count.Globally())
+
+  write_files = (initial
+                 | 'Drop Filename' >> beam.Map(lambda x: x[1])
+                 | 'Write ArrayRecord' >> arrayrecordio.WriteToArrayRecord(
+                     args['output'],
+                     coder=coders.ToBytesCoder(),
+                     num_shards=beam.pvalue.AsSingleton(file_count),
+                     file_name_suffix='.arrayrecord'))
+
+  return p1, write_files
+
+
+def convert_tf_to_arrayrecord_gcs(
+    overwrite_extension=False,
+    file_path_suffix='.arrayrecord',
+    args=def_args,
+    pipeline_options=def_pipeline_options):
+  """Convert TFRecords to ArrayRecords in GCS 1:1.
+  
+  Args:
+    overwrite_extension: Boolean making DoFn attempt to overwrite extension
+    file_path_suffix: Intended suffix for overwrite or append
+    args: Custom arguments
+    pipeline_options: Beam arguments in dict format
+
+  Returns:
+    Beam Pipeline object
+  """
+
+  p1 = beam.Pipeline(options=pipeline_options)
+  initial = (p1
+             | 'Start' >> beam.Create([args['input']])
+             | 'Read' >> beam.io.ReadAllFromTFRecord(with_filename=True)
+             | 'Group' >> beam.GroupByKey()
+             | 'Write to ArrayRecord in GCS' >> beam.ParDo(
+                 dofns.ConvertToArrayRecordGCS(),
+                 args['output'],
+                 file_path_suffix=file_path_suffix,
+                 overwrite_extension=overwrite_extension))
+
+  return p1, initial