Clean biapy package files and create binary for CLI

biapy/__init__.py

@@ -1,3 +1,54 @@
-__version__="3.2.0"
+__version__="3.4.0"
 
+import argparse
+import os
+import sys
 from ._biapy import BiaPy
+
+
+def main():
+
+    ##########################
+    #   ARGS COMPROBATION    #
+    ##########################
+
+    # Normal exec:
+    # python -u main.py \
+    #     --config $input_job_cfg_file \        
+    #     --result_dir $result_dir \        
+    #     --name $job_name \          
+    #     --run_id $job_counter \        
+    #     --gpu 0
+    # Distributed:
+    # python -u -m torch.distributed.run \
+    #     --nproc_per_node=2 \  
+    #     main.py \
+    #     --config $input_job_cfg_file \       
+    #     --result_dir $result_dir \        
+    #     --name $job_name \          
+    #     --run_id $job_counter \        
+    #     --gpu 0,1
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--config", required=True, help="Path to the configuration file")
+    parser.add_argument("--result_dir", help="Path to where the resulting output of the job will be stored",
+                        default=os.getenv('HOME'))
+    parser.add_argument("--name", help="Job name", default="unknown_job")
+    parser.add_argument("--run_id", help="Run number of the same job", type=int, default=1)
+    parser.add_argument("--gpu", help="GPU number according to 'nvidia-smi' command", type=str)
+
+    # Distributed training parameters
+    parser.add_argument('--world_size', default=1, type=int,
+                        help='number of distributed processes')
+    parser.add_argument('--local_rank', default=-1, type=int,
+                        help='Node rank for distributed training. Necessary for using the torch.distributed.launch utility.')
+    parser.add_argument('--dist_on_itp', action='store_true')
+    parser.add_argument('--dist_url', default='env://',
+                        help='url used to set up distributed training')
+    parser.add_argument('--dist_backend', type=str, default='nccl', choices=['nccl', 'gloo'],
+                        help='Backend to use in distributed mode')
+    args = parser.parse_args()
+
+    _biapy = BiaPy(**vars(args))
+    _biapy.run_job()
+    sys.exit(0)

main.py

@@ -2,51 +2,7 @@
 import os
 import sys
 
-from biapy import BiaPy
+from biapy import main
 
 if __name__ == '__main__':
-
-    ##########################
-    #   ARGS COMPROBATION    #
-    ##########################
-
-    # Normal exec:
-    # python -u main.py \
-    #     --config $input_job_cfg_file \        
-    #     --result_dir $result_dir \        
-    #     --name $job_name \          
-    #     --run_id $job_counter \        
-    #     --gpu 0
-    # Distributed:
-    # python -u -m torch.distributed.run \
-    #     --nproc_per_node=2 \  
-    #     main.py \
-    #     --config $input_job_cfg_file \       
-    #     --result_dir $result_dir \        
-    #     --name $job_name \          
-    #     --run_id $job_counter \        
-    #     --gpu 0,1
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--config", required=True, help="Path to the configuration file")
-    parser.add_argument("--result_dir", help="Path to where the resulting output of the job will be stored",
-                        default=os.getenv('HOME'))
-    parser.add_argument("--name", help="Job name", default="unknown_job")
-    parser.add_argument("--run_id", help="Run number of the same job", type=int, default=1)
-    parser.add_argument("--gpu", help="GPU number according to 'nvidia-smi' command", type=str)
-
-    # Distributed training parameters
-    parser.add_argument('--world_size', default=1, type=int,
-                        help='number of distributed processes')
-    parser.add_argument('--local_rank', default=-1, type=int,
-                        help='Node rank for distributed training. Necessary for using the torch.distributed.launch utility.')
-    parser.add_argument('--dist_on_itp', action='store_true')
-    parser.add_argument('--dist_url', default='env://',
-                        help='url used to set up distributed training')
-    parser.add_argument('--dist_backend', type=str, default='nccl', choices=['nccl', 'gloo'],
-                        help='Backend to use in distributed mode')
-    args = parser.parse_args()
-
-    _biapy = BiaPy(**vars(args))
-    _biapy.run_job()
-    sys.exit(0)
+    main()

pyproject.toml

@@ -1,14 +1,16 @@
 [build-system]
-requires = ["setuptools>=45", "wheel", "setuptools_scm>=6.2", "numpy>=1.24.3"]
+requires = ["setuptools"]
 build-backend = "setuptools.build_meta"
 
 [project]
 name = "biapy"
-version = "3.3.8"
+version = "3.4.0"
 description = "BiaPy: Bioimage analysis pipelines in Python"
 readme = "README.md"
+requires-python = ">=3.10"
 authors = [{ name = "Daniel Franco-Barranco", email = "[email protected]" }]
-license = { file = "LICENSE" }
+maintainers = [{ name = "Daniel Franco-Barranco", email = "[email protected]" }]
+license = { file = "LICENSE.md" }
 classifiers = [
     "License :: OSI Approved :: MIT License",
     "Environment :: GPU :: NVIDIA CUDA :: 11.8",
@@ -34,11 +36,19 @@ dependencies = [
     "bioimageio.core==0.5.9",
     "imagecodecs>=2024.1.1",
     "pytorch-msssim>=1.0.0",
+    "numpy>=1.26.4",
 ]
-requires-python = ">=3.10"
 
 [project.scripts]
-spam-cli = "biapy:BiaPy"
+biapy = "biapy:main"
 
 [project.urls]
-Homepage = "https://github.com/BiaPyX/BiaPy"
+"Homepage" = "https://biapyx.github.io"
+"Source" = "https://github.com/BiaPyX/BiaPy"
+"Forum" = "https://forum.image.sc/tag/biapy"
+
+[tool.setuptools]
+include-package-data = true
+
+[tool.setuptools.packages.find]
+include = ['biapy*']