Tait Hoyem
4 months ago
commit
8b09bba2c4
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### Generated by gibo (https://github.com/simonwhitaker/gibo)
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### https://raw.github.com/github/gitignore/4488915eec0b3a45b5c63ead28f286819c0917de/Python.gitignore
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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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||||
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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/#use-with-ide
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.pdm.toml
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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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@ -0,0 +1,102 @@
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PEOPLE = [
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{
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"name": "Tait Hoyem",
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"has_moodle_account": True,
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"has_taken_a_calculus_class": False,
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"is_student": True,
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"is_cs_student": True,
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"is_ee_student": False,
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"is_cpsc1820_student": True,
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"has_visited_usa": True,
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"is_smart": True,
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"age": 24,
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"enjoys_cpsc1820": False,
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},
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{
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"name": "Jaspreet Kaur",
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"has_moodle_account": True,
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"has_taken_a_calculus_class": True,
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"has_visited_usa": True,
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"is_student": False,
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"is_cs_student": False,
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"is_ee_student": False,
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"is_cpsc1820_student": False,
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"is_smart": True,
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"age": -1,
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"enjoys_cpsc1820": True,
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},
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{
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"name": "Ibrahim Abdulahi",
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"has_moodle_account": True,
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"has_taken_a_calculus_class": False,
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"has_visited_usa": True,
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"is_student": False,
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"is_cs_student": False,
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"is_ee_student": False,
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"is_cpsc1820_student": False,
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"is_smart": True,
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"age": -1,
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"enjoys_cpsc1820": False,
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},
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{
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"name": "Issac Newton",
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"has_moodle_account": True,
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"has_taken_a_calculus_class": False,
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"has_visited_usa": True,
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"is_student": False,
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"is_cs_student": False,
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"is_ee_student": False,
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"is_smart": True,
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"is_cpsc1820_student": False,
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"age": 482,
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"enjoys_cpsc1820": True,
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},
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{
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"name": "Albert Enstein",
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"has_taken_a_calculus_class": True,
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"has_moodle_account": True,
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"has_visited_usa": False,
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"is_student": False,
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"is_cs_student": False,
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"is_ee_student": False,
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"is_smart": True,
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"is_cpsc1820_student": False,
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"age": 125,
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"enjoys_cpsc1820": True,
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},
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{
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"name": "John James",
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"has_taken_a_calculus_class": False,
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"has_moodle_account": True,
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"has_visited_usa": False,
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"is_student": True,
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"is_smart": True,
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"is_cs_student": True,
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"is_ee_student": False,
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"is_cpsc1820_student": True,
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"age": 29,
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"enjoys_cpsc1820": False,
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},
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{
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"name": "Anthony Shih",
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"has_taken_a_calculus_class": False,
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"has_moodle_account": True,
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"has_visited_usa": False,
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"is_student": False,
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"is_cs_student": False,
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"is_ee_student": True,
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"is_cpsc1820_student": True,
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"is_smart": False,
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"age": 19,
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"enjoys_cpsc1820": False,
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},
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]
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def is_student(x):
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return x["is_student"]
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def is_1820_student(x):
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return x["is_cpsc1820_student"]
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STUDENTS = list(filter(is_student, PEOPLE))
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CPSC1820_STUDENTS = list(filter(is_1820_student, PEOPLE))
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@ -0,0 +1,51 @@
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from utils import implies
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FRUITS = [
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{
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"name": "Banana",
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"tropical": True,
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"delicious": True,
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"at_walmart": True,
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},
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{
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"name": "Dragon Fruit",
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"delicious": True,
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"at_walmart": False,
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"tropical": True,
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},
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{
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"name": "Orange",
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"delicious": False,
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"at_walmart": True,
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"tropical": True,
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},
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{
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"name": "Mango",
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"delicious": True,
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"at_walmart": False,
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"tropical": True,
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},
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{
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"name": "Watermelon",
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"delicious": True,
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"at_walmart": True,
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"tropical": True,
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},
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]
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def T(x):
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return x["tropical"]
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def D(x):
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return x["delicious"]
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def W(x):
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return x["at_walmart"]
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U = FRUITS
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# If a tropical fruit is delicious then it is available in Walmart.
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# ∀x [(T(x) ∧ D(x)) → W(x)]
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prop = all(map(lambda x: implies(T(x) and D(x), W(x)), U))
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print("If a tropical fruit is delicious then it is available in Walmart.")
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print("∀x [(T(x) ∧ D(x)) → W(x)]: ", prop)
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from data import STUDENTS, PEOPLE
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def R(x):
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return x["has_moodle_account"]
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def R2(x):
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return x["has_taken_a_calculus_class"]
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def R3(x):
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return not R2(x)
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def M(x):
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return x["has_visited_usa"]
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def S(x):
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return x["is_student"]
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print("Where R(x) is a student who has a mododle account")
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# ∀x R(x)
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prop1 = all(map(R, STUDENTS))
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print("∀x R(x): ", end="")
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print(prop1)
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# ∃x R(x)
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prop2 = any(map(R, STUDENTS))
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print("∃x R(x): ", end="")
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print(prop2)
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print()
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print("Where R(x) is a student that has taken a calculsu course")
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# ∀x P(x)
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prop3 = all(map(R2, STUDENTS))
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print("∀x P(x): ", end="")
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print(prop3)
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# ∃x ¬P(x)
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props4 = any(map(R3, STUDENTS))
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print("∃x ¬P(x): ", end="")
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print(props4)
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print()
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print("Where M(x) is somebody who has been to the USA")
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print("And U = {all students in CPSC 1820")
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# Assume, U = {all students in CPSC 1820}
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# ∃x M(x)
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props5 = any(map(M, STUDENTS))
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print("∃x M(x): ", end="")
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print(props5)
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# Assume, U = {all people}
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# ∃x [S(x) ∧ M(x)]
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props6 = any(map(lambda x: M(x) and S(x), PEOPLE))
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print("∃x [S(x) ∧ M(x)]: ", end="")
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print(props6)
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@ -0,0 +1,2 @@
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def implies(x,y):
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return not (x and not y)
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