init
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.gitignore
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.gitignore
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*.pdf
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output
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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.pdm.toml
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.pdm-python
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.pdm-build/
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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3
README.md
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3
README.md
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# dgp2
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Parses PDF schedule cards, extracting PIS codes and headcodes before using the OwlBoard API to build a list of PIS codes. Submitting the completed list to Git.
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11
main.py
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main.py
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# Open all PDF files in the working directory.
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# Loop through data and remove duplicate codes.
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# Check for existing codes via OwlBoard API.
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# Validate existing codes and submit issue if not correct.
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# Use the train list to search for stopping pattern of any absent codes.
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# Format file and commit to git
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55
parse_pdf.py
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55
parse_pdf.py
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import PyPDF2
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import re
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## re Patterns
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schedule_pattern = r"(?<=NOTES)(.*?)(?=NOTES|$)" # Split Schedule Cards
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train_start_pattern = r"\b\d[A-Z]\d{2}\s+\d{5}\s+\d{2}\.\d{2}(?:\s+\d{2}\.\d{2})?\s+[A-Za-z &]+" # Defines start of train section
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train_first_line_pattern = r"(?P<headcode>\d[A-Z]\d{2})\s+(?P<gsmr_code>\d{5})\s+(?P<time0>\d{2}\.\d{2})(?:\s+(?P<time1>\d{2}\.\d{2}))?\s+(?P<location>[A-Za-z0-9& ]+)" # Extracts Train Data
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train_pis_line_pattern = r"\(PIS Code\s*:\s*(?P<pis_code>\d+)\s*\)" # Extracts PIS Code
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# Extract Schedule Cards to list of strings
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def extract_pdf_text(file_path):
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with open(file_path, 'rb') as file:
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pdf_reader = PyPDF2.PdfReader(file)
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page_texts = []
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for page in pdf_reader.pages:
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text = page.extract_text()
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if text:
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page_texts.append(text)
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full_text = " ".join(page_texts)
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return full_text
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# Does everything - should be split in to functional functions
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def parse_pdf_file(filename):
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pdf_text = extract_pdf_text(filename)
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schedule_cards = re.findall(schedule_pattern, pdf_text, re.DOTALL)
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print(f"{len(schedule_cards)} Schedule Cards parsed")
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# Split into individual trains
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parsed_schedule_cards = []
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for schedule_card in schedule_cards:
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train_sections = re.split(f"(?={train_start_pattern})", schedule_cards[0])
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train_sections = [section.strip() for section in train_sections if section.strip()]
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parsed_schedule_cards.append(train_sections)
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# Process data from each individual train
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train_data = []
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for parsed_schedule_card in parsed_schedule_cards:
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for train in parsed_schedule_card:
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first_line_match = re.match(train_first_line_pattern, train)
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if first_line_match:
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train_entry = first_line_match.groupdict()
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pis_code_match = re.search(train_pis_line_pattern, train)
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train_entry["pis_code"] = pis_code_match.group("pis_code") if pis_code_match else None
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train_data.append(train_entry)
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return train_data
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1
requirements.txt
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1
requirements.txt
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PyPDF2==3.0.1
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