Bump version to 1.2.0 and switch to ruff for formatting (#1395)

* apply ruff to latest main

* apply ruff to latest main

* bump version number

Author: JanFSchulte

.pre-commit-config.yaml

@@ -1,13 +1,12 @@
 exclude: (^hls4ml\/templates\/(vivado|quartus)\/(ap_types|ac_types)\/|^test/pytest/test_report/)
 
 repos:
-- repo: https://github.com/psf/black-pre-commit-mirror
-  rev: 25.9.0
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  rev: v0.14.3
   hooks:
-  - id: black
-    language_version: python3
-    args: ['--line-length=125',
-           '--skip-string-normalization']
+    - id: ruff
+      args: [--fix]
+    - id: ruff-format
 
 - repo: https://github.com/tox-dev/pyproject-fmt
   rev: v2.11.0
@@ -29,11 +28,6 @@ repos:
   - id: requirements-txt-fixer
   - id: trailing-whitespace
 
-- repo: https://github.com/PyCQA/isort
-  rev: 7.0.0
-  hooks:
-  - id: isort
-
 - repo: https://github.com/asottile/pyupgrade
   rev: v3.21.0
   hooks:
@@ -47,7 +41,9 @@ repos:
     exclude: docs/conf.py
     additional_dependencies: [flake8-bugbear, flake8-print]
     args: ['--max-line-length=125',  # github viewer width
-           '--extend-ignore=E203,T201',  # E203 is not PEP8 compliant
+           '--extend-ignore=E203,T201,F401',
+           # E203 is not PEP8 compliant
+           # F401 included in ruff (behaves slightly differently for noqa flags)
            '--per-file-ignores=hls4ml/model/optimizer/passes/bit_exact.py:E741',
            # i for #int w/o sign, I for #int w/ sign when massively processing bw conversions
     ]

CITATION.cff

@@ -4,8 +4,8 @@ type: software
 authors:
 - given-names: "FastML Team"
 title: "hls4ml"
-version: "v1.1.0"
-date-released: "2025-03-17"
+version: "v1.2.0"
+date-released: "2025-10-31"
 doi: 10.5281/zenodo.1201549
 repository-code: "https://github.com/fastmachinelearning/hls4ml"
 url: "https://fastmachinelearning.org/hls4ml"

README.md

@@ -75,7 +75,7 @@ If you use this software in a publication, please cite the software
   title        = {fastmachinelearning/hls4ml},
   year         = 2025,
   publisher    = {Zenodo},
-  version      = {v1.1.0},
+  version      = {v1.2.0},
   doi          = {10.5281/zenodo.1201549},
   url          = {https://github.com/fastmachinelearning/hls4ml}
 }

docs/conf.py

@@ -100,7 +100,7 @@ def get_pypi_version(package, url_pattern=URL_PATTERN):
 
 # -- Extension configuration -------------------------------------------------
 html_show_sourcelink = False
-html_logo = "img/hls4ml_logo_navbar.png"
+html_logo = 'img/hls4ml_logo_navbar.png'
 
 html_theme_options = {
     'canonical_url': '',
@@ -121,7 +121,7 @@ def get_pypi_version(package, url_pattern=URL_PATTERN):
 html_context = {
     'display_github': True,  # Integrate GitHub
     'github_user': 'fastmachinelearning',  # Username
-    'github_repo': "hls4ml",  # Repo name
+    'github_repo': 'hls4ml',  # Repo name
     'github_version': 'main',  # Version
     'conf_py_path': '/docs/',  # Path in the checkout to the docs root
 }

hls4ml/__init__.py

@@ -4,8 +4,8 @@
     from ._version import version as __version__
     from ._version import version_tuple
 except ImportError:
-    __version__ = "unknown version"
-    version_tuple = (0, 0, "unknown version")
+    __version__ = 'unknown version'
+    version_tuple = (0, 0, 'unknown version')
 
 
 def reseed(newseed):

hls4ml/backends/catapult/catapult_backend.py

@@ -251,7 +251,7 @@ def build(
         ccs_args = f'"reset={reset} csim={csim} synth={synth} cosim={cosim} validation={validation}'
         ccs_args += f' export={export} vsynth={vsynth} fifo_opt={fifo_opt} bitfile={bitfile} ran_frame={ran_frame}'
         ccs_args += f' sw_opt={sw_opt} power={power} da={da} vhdl={vhdl} verilog={verilog} bup={bup}"'
-        ccs_invoke = catapult_exe + ' -product ultra -shell -f build_prj.tcl -eval \'set ::argv ' + ccs_args + '\''
+        ccs_invoke = catapult_exe + " -product ultra -shell -f build_prj.tcl -eval 'set ::argv " + ccs_args + "'"
         print(ccs_invoke)
         os.system(ccs_invoke)
         os.chdir(curr_dir)
@@ -455,9 +455,9 @@ def init_global_pooling2d(self, layer):
     @layer_optimizer(Softmax)
     def init_softmax(self, layer):
         if layer.model.config.get_config_value('IOType') == 'io_parallel':
-            assert (
-                len(layer.get_input_variable().shape) == 1
-            ), 'Softmax with io_parallel strategy cannot be used on multidimensional tensors.'
+            assert len(layer.get_input_variable().shape) == 1, (
+                'Softmax with io_parallel strategy cannot be used on multidimensional tensors.'
+            )
 
     @layer_optimizer(Embedding)
     def init_embed(self, layer):

hls4ml/backends/catapult/passes/broadcast_stream.py

@@ -6,7 +6,7 @@
 
 
 class Broadcast(Layer):
-    '''Inserted between layers for broadcasting.'''
+    """Inserted between layers for broadcasting."""
 
     def initialize(self):
         shape = self.attributes['target_shape']

hls4ml/backends/catapult/passes/conv_stream.py

@@ -3,7 +3,7 @@
 
 
 class GenerateConvStreamingInstructions(OptimizerPass):
-    '''Generates the instructions for streaming implementation of CNNs'''
+    """Generates the instructions for streaming implementation of CNNs"""
 
     def match(self, node):
         is_match = (

hls4ml/backends/catapult/passes/convolution_winograd.py

@@ -7,10 +7,10 @@
 
 
 class ApplyWinogradKernelTransformation(OptimizerPass):
-    '''
+    """
     Transforms the weights of a Conv2D kernel to a format suitable for Wingorad convolution
     For further information, refer to Lavin & Gray, 2015 - Fast Algorithms for Convolutional Neural Networks
-    '''
+    """
 
     def match(self, node):
         node_matches = isinstance(node, (Conv1D, Conv2D))

hls4ml/backends/catapult/passes/fifo_depth_optimization.py

@@ -82,9 +82,9 @@ def transform(self, model):
 
         if len(data['children']) == 0:
             print(
-                "FIFO depth optimization found no FIFOs implemented using BRAMs in the design, no optimization is possible."
+                'FIFO depth optimization found no FIFOs implemented using BRAMs in the design, no optimization is possible.'
             )
-            print("Consider increasing profiling_fifo_depth.")
+            print('Consider increasing profiling_fifo_depth.')
             return False
 
         n_elem = len(data['children'][0]['children'][0]['children'])