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amindadgaramindadgar
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feat: initializing repo!
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‎.dockerignore

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.github/
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.coverage/
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.coverage
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coverage
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venv/
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.env

‎.env.example

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AUTOMATION_DB_COLLECTION=
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AUTOMATION_DB_NAME=
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MONGODB_HOST=
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MONGODB_PASS=
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MONGODB_PORT=
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MONGODB_USER=
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NEO4J_DB=
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NEO4J_HOST=
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NEO4J_PASSWORD=
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NEO4J_PORT=
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NEO4J_PROTOCOL=
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NEO4J_USER=
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RABBIT_HOST=
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RABBIT_PASSWORD=
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RABBIT_PORT=
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RABBIT_USER=
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REDIS_HOST=
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REDIS_PASSWORD=
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REDIS_PORT=
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SAGA_DB_COLLECTION=
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SAGA_DB_NAME=
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SENTRY_DSN=
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SENTRY_ENV=

‎.github/workflows/production.yml

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name: Production CI/CD Pipeline
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on:
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push:
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branches:
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- main
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jobs:
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ci:
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uses: TogetherCrew/operations/.github/workflows/ci.yml@main
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secrets:
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CC_TEST_REPORTER_ID: ${{ secrets.CC_TEST_REPORTER_ID }}
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package_publish:
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needs: ci
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.10"]
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip setuptools wheel twine
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- name: Build package
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run: |
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python setup.py sdist bdist_wheel
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- name: Publish package to PyPI
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}
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run: |
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python -m twine upload dist/*

‎.github/workflows/start.staging.yml

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name: Staging CI/CD Pipeline
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on: pull_request
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jobs:
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ci:
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uses: TogetherCrew/operations/.github/workflows/ci.yml@main
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secrets:
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CC_TEST_REPORTER_ID: ${{ secrets.CC_TEST_REPORTER_ID }}

‎.gitignore

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.DS_Store
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.idea
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*.log
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tmp/
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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/#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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#
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# Emacs
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.org
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coverage/*
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analyzer_lib
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main.ipynb

‎Dockerfile

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# It's recommended that we use `bullseye` for Python (alpine isn't suitable as it conflcts with numpy)
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FROM python:3.10-bullseye AS base
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WORKDIR /project
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COPY . .
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RUN pip3 install -r requirements.txt
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FROM base AS test
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RUN chmod +x docker-entrypoint.sh
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CMD ["./docker-entrypoint.sh"]
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FROM base AS prod
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CMD ["python3", "server.py"]

‎README.md

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# TC-Analyzer-lib
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This repository contains the codes to analyze different platform's data. It includes the scripts to compute heatmaps, memberactivities and graph analytics such as degree centrality, Louvain modularity, local clustering coefficient.
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To install the library you could follow the
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```bash
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pip install tc-analyzer-lib
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```

‎docker-compose.dev.yml

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version: "3.9"
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services:
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redis:
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image: "redis:7.0.12-alpine"
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ports:
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- 6379:6379
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mongo:
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image: "mongo:6.0.8"
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ports:
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- 27017:27017
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environment:
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- MONGO_INITDB_ROOT_USERNAME=root
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- MONGO_INITDB_ROOT_PASSWORD=pass
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rabbitmq:
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image: "rabbitmq:3-management-alpine"
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ports:
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- 5672:5672
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environment:
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- RABBITMQ_DEFAULT_USER=root
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- RABBITMQ_DEFAULT_PASS=pass
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neo4j:
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image: "neo4j:5.9.0"
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ports:
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- 7687:7687
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- 7474:7474
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environment:
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- NEO4J_AUTH=neo4j/password
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- NEO4J_PLUGINS=["apoc", "graph-data-science"]
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- NEO4J_dbms_security_procedures_unrestricted=apoc.*,gds.*

‎docker-compose.example.yml

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version: "3.9"
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services:
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server:
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build:
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context: .
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target: prod
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dockerfile: Dockerfile
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command: python3 server.py
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worker:
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build:
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context: .
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target: prod
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dockerfile: Dockerfile
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command: python3 worker.py

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