c

requirements.txt

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+et_xmlfile==2.0.0
+openpyxl==3.1.5

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+requirements.txt
+setup.py
+ultralytics.egg-info
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other info into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+mlruns/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# Profiling
+*.pclprof
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+.idea
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# VSCode project settings
+.vscode/
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# datasets and projects (ignore /datasets dir at root only to allow for docs/en/datasets dir)
+/datasets
+runs/
+wandb/
+.DS_Store
+
+# Neural Network weights -----------------------------------------------------------------------------------------------
+weights/
+*.weights
+*.pt
+*.pb
+*.onnx
+*.engine
+*.mlmodel
+*.mlpackage
+*.torchscript
+*.tflite
+*.h5
+*.mnn
+*_saved_model/
+*_web_model/
+*_openvino_model/
+*_paddle_model/
+*_ncnn_model/
+*_imx_model/
+pnnx*
+
+# Autogenerated files for tests
+/ultralytics/assets/
+
+# calibration image
+calibration_*.npy

README.md

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+example usage : 
+
+
+``` python
+file_path = "./1.xlsx"
+sheet_name = "Sheet"
+with XL(file_path) as excel_to_dict:
+    data = excel_to_dict.sheet_to_dict(sheet_name)
+print(data)
+```

xl/main.py

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+import openpyxl
+
+class XL:
+    def __init__(self, file_path: str):
+        """
+        Initialize the class with the path to the Excel file.
+        """
+        self.file_path = file_path
+        self.workbook = None
+
+    def __enter__(self):
+        """
+        Open the workbook when entering the context.
+        """
+        self.workbook = openpyxl.load_workbook(self.file_path)
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """
+        Close the workbook when exiting the context.
+        """
+        if self.workbook:
+            self.workbook.close()
+
+    def sheet_to_dict(self, sheet_name: str):
+        """
+        Convert a sheet's data to a dictionary, removing rows with None values.
+        """
+        if not self.workbook:
+            raise ValueError("Workbook is not loaded. Ensure you use 'with' to open the file.")
+        
+        if sheet_name not in self.workbook.sheetnames:
+            raise ValueError(f"Sheet '{sheet_name}' not found in the workbook.")
+        
+        sheet = self.workbook[sheet_name]
+        headers = [cell.value for cell in sheet[1] if cell.value is not None]
+        
+        data_list = []
+        for row in sheet.iter_rows(min_row=2, values_only=True):
+            row_dict = {headers[i]: cell for i, cell in enumerate(row) if i < len(headers)}
+            # Remove keys with None values
+            row_dict = {key: value for key, value in row_dict.items() if value is not None}
+            if row_dict:  # Only include non-empty rows
+                data_list.append(row_dict)
+        
+        return data_list