Update dependencies

.github/actions/create-dev-database/docker-compose.yml

@@ -3,7 +3,7 @@ version: "3"
 services:
 
   database:
-    image: ghcr.io/marxide/postgres-q3c:latest
+    image: ghcr.io/mauch/postgres-q3c:latest
     container_name: vast-dev-db
     ports:
       - "127.0.0.1:${DB_PORT}:5432"

.github/workflows/test-suite.yml

@@ -37,7 +37,7 @@ jobs:
 
       - uses: snok/install-poetry@v1
         with:
-          version: 2.0.1
+          version: 2.3.2
           virtualenvs-create: true
           virtualenvs-in-project: true
       - name: cache deps

CHANGELOG.md

@@ -1,5 +1,6 @@
 # Changelog
 
+
 All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), with an added `List of PRs` section and links to the relevant PRs on the individual updates. This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

pyproject.toml

@@ -7,40 +7,40 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.11.0,<3.13"
-astropy = "^7.0"
+astropy = "7.2"
 astroquery = "==0.4.7"
 bokeh = "3.6.2" # must align with @bokeh/bokehjs version in package.json
 channels = "^3.0.5"
 cloudpickle = "^3.1"
 colorcet = "^2.0.6"
 crispy-bootstrap4 = "2024.10"
 datashader = "^0.17"
-dask = {extras = ["complete"], version = "^2025.1.0"}
+dask = {extras = ["complete"], version = "2025.1.0"}
 dill = "^0"
-distributed = "^2025.1.0"
-Django = "^5.1"
+distributed = "2025.1.0"
+Django = "5.2.12"
 django-crispy-forms = "^2.3"
 django-environ = "^0.12.0"
 django-postgres-copy = "^2.7.6"
 django-q2 = "^1.7.6"
-django-tagulous = "^2.1.0"
+django-tagulous = { git = "https://github.com/valentijnscholten/django-tagulous", branch = "django-5.2" }
 djangorestframework = "^3.15.0"
 djangorestframework-datatables = "0.7.2"
 forced-phot = { git = "https://github.com/askap-vast/forced_phot.git", tag = "v0.2.0" }
 gevent = { version = "^24", optional = true }
 gunicorn = { version = "^20.0.4", optional = true }
 holoviews = "^1.20"
 Jinja2 = "^3.1"
-llvmlite = "^0.43"
+llvmlite = "0.46"
 matplotlib = "^3.10"
 networkx = "^2.8"
-numba = "^0.60"
-numpy = "^2.0"
-pandas = "^2.2"
+numba = "0.64"
+numpy = "2.4.3"
+pandas = "2.3.3"
 psutil = "^5.9"
 psycopg2 = "^2.9.10"
 pyarrow = "^18.1"
-scipy = "^1.15"
+scipy = "1.17.1"
 shortuuid = "^1.0"
 social-auth-app-django = "^5.4.2"
 social-auth-core = "^4.5.4"

vast_pipeline/pipeline/association.py

@@ -178,7 +178,7 @@ def one_to_many_basic(
 
     new_original_related = pd.DataFrame(
         not_original[["source", "new_source_id"]]
-        .groupby("source")
+        .groupby("source")[["source", "new_source_id"]]
         .apply(lambda grp: grp["new_source_id"].tolist())
     )
 
@@ -234,12 +234,12 @@ def one_to_many_basic(
     # Get all the indexes required for each original
     # `source_skyc1` value
     source_df_index_to_copy = pd.DataFrame(
-        duplicated_skyc2.groupby("source").apply(
+        duplicated_skyc2.groupby("source")["source"].apply(
             lambda grp: sources_df[
                 sources_df["source"] == grp.name
             ].index.values.tolist()
         )
-    )
+    ).rename(columns={"source": 0})
 
     # source_df_index_to_copy
     # +----------+-------+
@@ -420,7 +420,7 @@ def one_to_many_advanced(
     # to the original related column.
     new_original_related = pd.DataFrame(
         not_original[["source_skyc1", "new_source_id"]]
-        .groupby("source_skyc1")
+        .groupby("source_skyc1")[["source_skyc1", "new_source_id"]]
         .apply(lambda grp: grp["new_source_id"].tolist())
     )
 
@@ -477,13 +477,12 @@ def one_to_many_advanced(
     # Get all the indexes required for each original
     # `source_skyc1` value
     source_df_index_to_copy = pd.DataFrame(
-        duplicated_skyc1.groupby("source_skyc1").apply(
+        duplicated_skyc1.groupby("source_skyc1")["source_skyc1"]
+        .apply(
             lambda grp: sources_df[
                 sources_df["source"] == grp.name
-            ].index.values.tolist()
-        )
-    )
-
+            ].index.values.tolist())
+    ).rename(columns={"source_skyc1": 0})
     # source_df_index_to_copy
     # +----------------+-------+
     # |   source_skyc1 | 0     |
@@ -664,7 +663,8 @@ def many_to_one_advanced(temp_srcs: pd.DataFrame) -> pd.DataFrame:
     # 'one'. Below for each 'one' group we gather all the ids of the many
     # sources.
     new_relations = pd.DataFrame(
-        duplicated_skyc2.groupby("index_old_skyc2").apply(
+        duplicated_skyc2.groupby("index_old_skyc2")[["index_old_skyc2", "source_skyc1"]]
+        .apply(
             lambda grp: grp["source_skyc1"].tolist()
         )
     ).rename(columns={0: "new_relations"})

vast_pipeline/pipeline/new_sources.py

@@ -248,7 +248,7 @@ def parallel_get_new_high_sigma(
     def process_group(df_group):
         return get_image_rms_measurements(df_group, edge_buffer=edge_buffer)
 
-    out = df[cols].groupby("img_diff_rms_path") \
+    out = df[cols].groupby("img_diff_rms_path")[cols] \
                   .apply(
                     process_group,
                     meta={'source': str, 'true_sigma': float}) \

vast_pipeline/pipeline/utils.py

@@ -978,7 +978,8 @@ def get_src_skyregion_merged_df(
     skyreg_df = skyreg_df.drop(["x", "y", "z", "width_ra", "width_dec"], axis=1)
 
     skyreg_df = skyreg_df.join(
-        pd.DataFrame(images_df.groupby("skyreg_id").apply(get_names_and_epochs)),
+        pd.DataFrame(images_df.groupby("skyreg_id")[["skyreg_id", "name", "epoch", "datetime"]]
+                              .apply(get_names_and_epochs)),
         on="id",
     )
 

webinterface/settings.py

@@ -51,13 +51,6 @@
     "vast_pipeline",
 ] + env("EXTRA_APPS", cast=list, default=[])
 
-SERIALIZATION_MODULES = {
-    "xml": "tagulous.serializers.xml_serializer",
-    "json": "tagulous.serializers.json",
-    "python": "tagulous.serializers.python",
-    "yaml": "tagulous.serializers.pyyaml",
-}
-
 MIDDLEWARE = [
     "django.middleware.security.SecurityMiddleware",
     "whitenoise.middleware.WhiteNoiseMiddleware",