fix: temporarily disable multiprocessing and ready prepatch

PHT-Medic · Jul 17, 2023 · c339bb5 · c339bb5
1 parent a08e074
commit c339bb5
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Showing 3 changed files with 15 additions and 11 deletions.
diff --git a/.github/containerscan/allowedlist.yaml b/.github/containerscan/allowedlist.yaml
@@ -1,5 +1,6 @@
 general:
   vulnerabilities:
+    - CVE-2023-3640
     - CVE-2023-31248
     - CVE-2023-29007
     - CVE-2023-25652

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pht-train-container-library"
-version = "2.0.6"
+version = "2.0.6a0"
 description = "Python library for handling containerized PHT trains"
 authors = ["Michael Graf <michael.graf@uni-tuebingen.com>"]
 readme = "README.md"

diff --git a/train_lib/docker_util/validate_master_image.py b/train_lib/docker_util/validate_master_image.py
@@ -1,5 +1,4 @@
 import hashlib
-import multiprocessing as mp
 import tarfile
 from io import BytesIO
 
@@ -127,17 +126,21 @@ def _get_file_hashes(
                     bytes_arr.extend(layer_file.read())
                     layer_tars.append((bytes_arr, path_exceptions))
 
-        # init and execute (a)synchronous multiprocessing for hashing function
-        pool = mp.Pool(num_cpus) if num_cpus != -1 else mp.Pool(mp.cpu_count())
-        # results = []
-        # def collect_result(result):
-        #     global results
-        #     results.append(result)
-        # pool.map_async(_apply_hash_function_to_layers, layers, callback=collect_result)
-        results = pool.map(_apply_hash_function_to_layers, layer_tars)
-        pool.close()
+        # # init and execute (a)synchronous multiprocessing for hashing function #TODO
+        # pool = mp.Pool(num_cpus) if num_cpus != -1 else mp.Pool(mp.cpu_count())
+        # # results = []
+        # # def collect_result(result):
+        # #     global results
+        # #     results.append(result)
+        # # pool.map_async(_apply_hash_function_to_layers, layers, callback=collect_result)
+        # results = pool.map(_apply_hash_function_to_layers, layer_tars)
+        # pool.close()
         # pool.join()
 
+        results = [
+            _apply_hash_function_to_layers(layer_tar) for layer_tar in layer_tars
+        ]
+
         # aggregate multiprocessing results
         for result in results:
             # integrate hash results into full image hash