Merge branch 'feature/improve_ci' into 'master'

Tidy up CI failures in tag script

See merge request minknow/mkr-file-format!4

Author: 0x55555555

.gitlab-ci.yml

@@ -12,7 +12,7 @@ tag_version_check:
   stage: pre-flight
   only:
     - tags
-  image: ${PYTHON_IMAGE}
+  image: git.oxfordnanolabs.local:4567/minknow/images/build-x86_64-gcc9:latest
   script:
     - mkr_version="$(cmake -P ci/get_tag_version.cmake 2>&1)"
     - tag_version="${CI_COMMIT_TAG/#v/}"

benchmarks/tools/find_and_get_mkr.py

@@ -3,7 +3,6 @@
 import argparse
 import multiprocessing as mp
 from pathlib import Path
-import pickle
 from queue import Empty
 from uuid import UUID
 
@@ -33,9 +32,7 @@ def process_read(get_columns, read, read_ids, extracted_columns):
             col.append(getattr(read, c))
 
 
-def do_batch_bulk_work(
-    filename, batches, select_read_ids, get_columns, c_api, result_q
-):
+def do_batch_work(filename, batches, get_columns, c_api, result_q):
     read_ids = []
     extracted_columns = {"read_id": read_ids}
 
@@ -47,19 +44,13 @@ def do_batch_bulk_work(
     result_q.put(pd.DataFrame(extracted_columns))
 
 
-def do_batch_search_work(
-    filename, batches, select_read_ids_pickled, get_columns, c_api, result_q
-):
+def do_search_work(files, select_read_ids, get_columns, c_api, result_q):
     read_ids = []
     extracted_columns = {"read_id": read_ids}
+    for file in files:
+        file = mkr_format.open_combined_file(file, use_c_api=c_api)
 
-    select_read_ids = pickle.loads(select_read_ids_pickled)
-
-    file = mkr_format.open_combined_file(filename, use_c_api=c_api)
-    for batch in batches:
-        for read in filter(
-            lambda x: x.read_id in select_read_ids, file.get_batch(batch).reads()
-        ):
+        for read in file.select_reads(UUID(s) for s in select_read_ids):
             process_read(get_columns, read, read_ids, extracted_columns)
 
     result_q.put(pd.DataFrame(extracted_columns))
@@ -82,36 +73,34 @@ def run(input_dir, output, select_read_ids=None, get_columns=[], c_api=False):
     files = list(input_dir.glob("*.mkr"))
     print(f"Searching for read ids in {[str(f) for f in files]}")
 
-    fn_to_call = do_batch_bulk_work
-    if select_read_ids is not None:
-        fn_to_call = do_batch_search_work
-
-    select_read_ids = pickle.dumps(
-        set(UUID(s) for s in select_read_ids) if select_read_ids is not None else None
-    )
-
     processes = []
-    for filename in files:
-        file = mkr_format.open_combined_file(filename, use_c_api=c_api)
-        batches = list(range(file.batch_count))
-        approx_chunk_size = max(1, len(batches) // runners)
+    if select_read_ids is not None:
+        approx_chunk_size = max(1, len(select_read_ids) // runners)
         start_index = 0
-        while start_index < len(batches):
-            select_batches = batches[start_index : start_index + approx_chunk_size]
+        while start_index < len(select_read_ids):
+            select_ids = select_read_ids[start_index : start_index + approx_chunk_size]
             p = mp.Process(
-                target=fn_to_call,
-                args=(
-                    filename,
-                    select_batches,
-                    select_read_ids,
-                    get_columns,
-                    c_api,
-                    result_queue,
-                ),
+                target=do_search_work,
+                args=(files, select_ids, get_columns, c_api, result_queue),
             )
             p.start()
             processes.append(p)
-            start_index += len(select_batches)
+            start_index += len(select_ids)
+    else:
+        for filename in files:
+            file = mkr_format.open_combined_file(filename, use_c_api=c_api)
+            batches = list(range(file.batch_count))
+            approx_chunk_size = max(1, len(batches) // runners)
+            start_index = 0
+            while start_index < len(batches):
+                select_batches = batches[start_index : start_index + approx_chunk_size]
+                p = mp.Process(
+                    target=do_batch_work,
+                    args=(filename, select_batches, get_columns, c_api, result_queue),
+                )
+                p.start()
+                processes.append(p)
+                start_index += len(select_batches)
 
     print("Wait for processes...")
     items = []