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contributing.md

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The bottom line. Follow your Nose, or our Nose. Write-run-love tests :fist:.
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##Setup
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## Setup
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###Fork, Clone, Setup Your Version of the Plotly Python API
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### Fork, Clone, Setup Your Version of the Plotly Python API
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First, you'll need to *get* our project. This is the appropriate *clone* command (if you're unfamiliar with this process, https://help.github.com/articles/fork-a-repo):
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git clone https://github.com/plotly/python-api.git
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```
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###Submodules
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### Submodules
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Second, this project uses git submodules! They're both helpful and, at times, difficult to work with. The good news is you probably don't need to think about them! Just run the following shell command to make sure that your local repo is wired properly:
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make readme
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```
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###Making a Development Branch
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### Making a Development Branch
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Third, *don't* work in the `master` branch. As soon as you get your master branch ready, run:
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... where you should give your branch a more descriptive name than `my-dev-branch`
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###Pull Request When Ready
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### Pull Request When Ready
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Once you've made your changes (and hopefully written some tests...), make that pull request!
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##Suggestions
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## Suggestions
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###Local Python
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### Local Python
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Setting up Python versions that *don't* require you to use `sudo` is a good idea. In addition, the core Python on your machine may not be the Python that we've developed in! Here are some nice guides for Mac, Windows, and Linux:
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- http://docs.python-guide.org/en/latest/starting/install/osx/
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- http://docs.python-guide.org/en/latest/starting/install/win/
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- http://docs.python-guide.org/en/latest/starting/install/linux/
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###Virtualenv
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### Virtualenv
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Virtualenv is a way to create Python environments on your machine that know nothing about one another. This is really helpful for ironing out dependency-problems arising from different versions of packages. Here's a nice guide on how to do this: http://docs.python-guide.org/en/latest/dev/virtualenvs/
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###Alter Your PYTHONPATH
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### Alter Your PYTHONPATH
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The PYTHONPATH variable in your shell tells Python where to look for modules. Since you'll be developing, it'll be a pain to need to *install* Python every time you need to test some functionality (or at least ensure you're running code from the right directory...). You can easily make this change from a shell:
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```bash
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Note, that's non-permanent. When you close the shell, that variable definition disappears. Also, `path/to/local/repo` is *your* specific repository path (e.g., `/Users/andrew/projects/python-api`).
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###Why?
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### Why?
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Now you can run the following code and be guaranteed to have a working development version that you can make changes to on-the-fly, test, and be confident will not break on other's machines!
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export PYTHONPATH="/path/to/local/repo:$PYTHONPATH"
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```
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##Dependencies
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## Dependencies
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There's a short list of core dependencies you'll need installed in your Python environment to have any sort of fun with Plotly's Python API (see `requirements.txt`). Additionally, you're likely to have even more fun if you install some other requirements (see `optional-requirements.txt`).
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###Dependencies and Virtualenv
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### Dependencies and Virtualenv
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If you decided to follow the suggestion about about the Virtualenv *and* you've run `source bin/activate` within your new virtualenv directory to activate it--you can run the following to install the core dependencies:
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pip install -r optional-requirements.txt
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```
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##Testing
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## Testing
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We take advantage of two tools to run tests:
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* [`tox`](https://tox.readthedocs.io/en/latest/), which is both a virtualenv management and test tool.
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* [`nose`](https://nose.readthedocs.org/en/latest/), which is is an extension of Python's unittest
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###Running Tests with `nose`
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### Running Tests with `nose`
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Since our tests cover *all* the functionality, to prevent tons of errors from showing up and having to parse through a messy output, you'll need to install `optional-requirements.txt` as explained above.
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nosetests plotly/tests/test_plotly/test_plot.py
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```
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###Running tests with `tox`
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### Running tests with `tox`
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Running tests with tox is much more powerful, but requires a bit more setup.
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tox -- -a '!slow','!matplotlib'
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```
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###Writing Tests
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### Writing Tests
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You're *strongly* encouraged to write tests that check your added functionality.
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