add nuitka build (dev)

Author: niklases

build_with_nuitka.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+python -m pip install -U nuitka
+conda install libpython-static
+sudo apt install patchelf
+python -m nuitka gui/qt_window.py \
+    --mode=standalone \
+    --enable-plugin=pyside6 \
+    --include-data-dir=pypef/ml/AAindex=pypef/ml/. \
+    #--include-distribution-metadata \
+    #--onefile

gui/qt_window.py

@@ -6,6 +6,10 @@
 from PySide6 import QtCore, QtWidgets
 from PySide6.QtCore import QSize
 pypef_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
+from pypef.main import run_main
+
+
+EXEC_API_OR_CLI = ['api', 'cli'][0]
 
 
 def capture(command):
@@ -322,6 +326,7 @@ def pypef_mklsts(self):
         csv_variant_file = QtWidgets.QFileDialog.getOpenFileName(self, "Select variant CSV File")[0]
         if wt_fasta_file and csv_variant_file:
             self.version_text.setText("Running MKLSTS...")
+            #self.exec_pypef_cli(f'mklsts --wt {wt_fasta_file} --input {csv_variant_file}')
             self.exec_pypef(f'mklsts --wt {wt_fasta_file} --input {csv_variant_file}')
 
 
@@ -441,15 +446,25 @@ def pypef_onehot_supervised_train_test(self):
             self.version_text.setText("Hybrid (DCA-supervised) model training and testing...")
             self.exec_pypef(f'ml --encoding onehot --ls {training_file} --ts {test_file} '
                             f'--threads {self.n_cores} --regressor {self.regression_model}')
-    
 
     def exec_pypef(self, cmd):
+        if EXEC_API_OR_CLI == 'api':
+            return self.exec_pypef_api(cmd)
+        elif EXEC_API_OR_CLI == 'cli':
+            return self.exec_pypef(cmd)
+        else:
+            raise SystemError("Choose between 'api' or 'cli'!")
+
+    def exec_pypef_cli(self, cmd):
         print(cmd)  # TODO remove
         self.process.start(f'python', ['-u', f'{self.pypef_root}/run.py'] + cmd.split(' '))
         self.process.finished.connect(self.process_finished)
         if self.c > 0:
             self.textedit_out.append("=" * 104 + "\n")
 
+    def exec_pypef_api(self, cmd):
+        run_main(argv=cmd)
+        pass
 
     def process_finished(self):
         self.version_text.setText("Finished...") 

pypef/hybrid/hybrid_model.py

@@ -1193,13 +1193,14 @@ def performance_ls_ts(
                     f"{len(test_variants)} (after removing substitutions "
                     f"at gap positions)."
         )
-        if llm.lower().startswith('esm'):
-            llm_dict = esm_setup(train_sequences)
-            x_llm_test = llm_embedder(llm_dict, test_sequences)
-        elif llm.lower() == 'prosst':
-            llm_dict = prosst_setup(
-                wt_seq, pdb_file, sequences=train_sequences)
-            x_llm_test = llm_embedder(llm_dict, test_sequences)
+        if llm is not None:
+            if llm.lower().startswith('esm'):
+                llm_dict = esm_setup(train_sequences)
+                x_llm_test = llm_embedder(llm_dict, test_sequences)
+            elif llm.lower() == 'prosst':
+                llm_dict = prosst_setup(
+                    wt_seq, pdb_file, sequences=train_sequences)
+                x_llm_test = llm_embedder(llm_dict, test_sequences)
         else:
             llm_dict = None
             x_llm_test = None

pypef/main.py

@@ -414,13 +414,13 @@ def validate(args):
         exit(e)
 
 
-def run_main():
+def run_main(argv=None):
     """
     Entry point for pip-installed version.
     Arguments are created from Docstring using docopt that 
     creates an argument dict.
     """
-    arguments = docopt(__doc__, version=__version__)
+    arguments = docopt(__doc__, argv=argv, version=__version__)
     start_time = time.time()
     logger.debug(f'main.py __name__: {__name__}, version: {__version__}')
     logger.debug(str(argv)[1:-1].replace("\'", "").replace(",", ""))