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@@ -15,6 +15,18 @@ The application can run in one of two modes:
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In practice, you will likely need to run at least one instance of each mode. We provide a single codebase and Docker image, but the mode can be set at runtime.
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## 💻 Requirements
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> NOTE:<br>
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> 🐳 = required for running with Docker.<br>
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> 🐍 = required for running with Python.
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- 🐳🐍 [GNU Make](https://www.gnu.org/software/make/manual/make.html) is used to simplify the commands and GitHub Actions. This approach is recommended to simplify the command line experience. This is built in for MacOS and Linux. For Windows, setup is simpler with [Chocolatey](https://chocolatey.org/install) and installing the provided [make package](https://chocolatey.org/packages/make). The other Windows option is [manually installing make](http://gnuwin32.sourceforge.net/packages/make.htm).
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- 🐍 [Python 3.8](https://www.python.org/downloads/) is <ins>**required**</ins> to develop this API. If developer uses multiple versions of python, [pyenv](https://github.com/pyenv/pyenv) is suggested to assist version management.
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- 🐍 [pipenv](https://github.com/pypa/pipenv) is used to configure the python environment. Installation instructions can be found [here](https://github.com/pypa/pipenv#installation).
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_These requirements line up with [electionguard-python](https://github.com/microsoft/electionguard-python/blob/main/README.md#-requirements)._
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## 🐳 Running with Docker
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If you run Docker and want to get started quickly, we provide a Dockerfile and docker-compose.yml.
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## 🐍 Running with Python
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### Requirements
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_These requirements line up with [electionguard-python](https://github.com/microsoft/electionguard-python/blob/main/README.md#-requirements)._
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-[Python 3.8](https://www.python.org/downloads/) is <ins>**required**</ins> to develop this API. If developer uses multiple versions of python, [pyenv](https://github.com/pyenv/pyenv) is suggested to assist version management.
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-[GNU Make](https://www.gnu.org/software/make/manual/make.html) is used to simplify the commands and GitHub Actions. This approach is recommended to simplify the command line experience. This is built in for MacOS and Linux. For Windows, setup is simpler with [Chocolatey](https://chocolatey.org/install) and installing the provided [make package](https://chocolatey.org/packages/make). The other Windows option is [manually installing make](http://gnuwin32.sourceforge.net/packages/make.htm).
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-[pipenv](https://github.com/pypa/pipenv) is used to configure the python environment. Installation instructions can be found [here](https://github.com/pypa/pipenv#installation).
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### Quick Start
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Using [**make**](https://www.gnu.org/software/make/manual/make.html), installation and startup can be run with one command:
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## 🧪 Testing
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A Postman collection is available to test the API located in the `/tests` folder. This can be imported into Postman for easy testing. This suite works on a local run server or the preconfigured docker settings.
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A Postman collection is available to test the API located in the `/tests` folder. You can do a few things with this:
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-[Import into Postman](https://learning.postman.com/docs/getting-started/importing-and-exporting-data/#importing-data-into-postman) for easy manual testing.
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- Run locally with the [Newman CLI](https://github.com/postmanlabs/newman).
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- Run the APIs and tests entirely in Docker by running:
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