🖊️ add contributing guide + changelog

CHANGELOG.md

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+
+
+# v 0.8.0
+
+## Major changes
+
+### Faster aggregation 🐎 
+the `lttbc` dependency is removed; and we added our own (faster) lttb C implementation. Additionally we provide a Python fallback when this lttb-C building fails. In the near future, we will look into CIBuildWheels to build the wheels for the major OS & Python matrix versions.  
+A well deserved s/o to [dgoeris/lttbc](https://github.com/dgoeries/lttbc), who heavily inspired our implementation!
+
+### Figure Output serialization 📸 
+Plotly-resampler now also has the option to store the output figure as an Image in notebook output. As long the notebook is connected, the interactive plotly-resampler figure is shown; but once the figure / notebook isn't connected anymore, a static image will be rendered in the notebook output.
+
+## What's Changed (generated)
+* :bug: return self when calling add_traces by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/75
+* :fire: add streamlit integration example by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/80
+* ✨ adding `convert_traces_kwargs` by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/81
+* Fix numeric `hf_y` input as dtype object by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/90
+* :fire: add support for figure dict input + propagate _grid_str by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/92
+* :pray: fix tests for all OS by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/95
+* Add python3dot10 by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/96
+* :sunrise: FigureResampler display improvements by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/97
+* :package: serialization support +  :level_slider: update OS & python version in test-matrix by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/87
+* Lttbv2 🍒 ⛏️  branch by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/103
+* :robot: hack together output retention in notebooks by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/105
+* :package: improve docs by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/104
+
+& some other minor bug fixes :see_no_evil: 
+
+**Full Changelog**: https://github.com/predict-idlab/plotly-resampler/compare/v0.7.0...v0.8.0
+
+---
+
+# V0.7.0
+
+## What's Changed
+
+**You can register plotly_resampler**; this adds dynamic resampling functionality *under the hood* to plotly.py! 🥳
+As a result, you can stop wrapping plotly figures with a plotly-resampler decorator (as this all happens automatically) 
+> You only need to call the `register_plotly_resampler` method and all plotly figures will be wrapped (under the hood) according to that method's configuration.
+
+-> More info in the [README](https://github.com/predict-idlab/plotly-resampler#usage) and [docs](https://predict-idlab.github.io/plotly-resampler/getting_started.html#how-to-use)!
+
+Aditionally, all resampler Figures are now composable; implying that they can be decorated by themselves and all other types of plotly-(resampler) figures. This eases the switching from a FigureResampler to FigureWidgetResampler and vice-versa.
+
+
+## What's Changed (PR's)
+* 🦌 Adding reset-axes functionality by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/48
+* 🐛 Small bugfixes by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/52
+* 🔍  investigating gap-detection methodology by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/53
+* :mag: fix float index problem of #63 by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/64
+* :wrench: hotfix for rounding error by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/66
+* 🗳️ Compose figs by @jonasvdd in https://github.com/predict-idlab/plotly-resampler/pull/72
+* :sparkles: register plotly-resampler by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/70
+* :robot: update dependencies + new release by @jvdd in https://github.com/predict-idlab/plotly-resampler/pull/74
+
+
+**Full Changelog**: https://github.com/predict-idlab/plotly-resampler/compare/v0.6.0...v0.7.0

CONTRIBUTING.md

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+# How to contribute
+
+First of all, thank you for considering contributing to `plotly-resampler`.<br>
+It's people like you that will help make `plotly-resampler` a great toolkit.
+
+As usual, contributions are managed through GitHub Issues and Pull Requests.
+
+We are welcoming contributions in the following forms:
+* **Bug reports**: when filing an issue to report a bug, please use the search tool to ensure the bug hasn't been reported yet;
+* **New feature suggestions**: if you think `plotly-resampler` should include a new feature, please open an issue to ask for it (of course, you should always check that the feature has not been asked for yet :). Think about linking to a pdf version of the paper that first proposed the method when suggesting a new algorithm. 
+* **Bugfixes and new feature implementations**: if you feel you can fix a reported bug/implement a suggested feature yourself, do not hesitate to:
+  1. fork the project;
+  2. implement your bugfix;
+  3. submit a pull request referencing the ID of the issue in which the bug was reported / the feature was suggested;
+
+When submitting code, please think about code quality, adding proper docstrings, and including thorough unit tests with high code coverage.
+
+
+## How to develop locally
+
+*Note: this guide is tailored to developers using linux*
+
+The following steps assume that your console is at the root folder of this repository.
+
+### Create a new (poetry) Python environment
+
+It is best practice to use a new Python environment when starting on a new project.
+
+We describe two options; 
+
+<details>
+<summary><i>Advised option</i>: using poetry shell</summary>
+For dependency management we use poetry (read more below).<br>
+Hence, we advise to use poetry shell to create a Python environment for this project.
+
+1. Install poetry: https://python-poetry.org/docs/#installation <br>
+   (If necessary add poetry to the PATH)
+2. Create & activate a new python environment: <code>poetry shell</code>
+
+After the poetry shell command your python environment is activated.
+</details>
+
+<details>
+<summary><i>Alternative option</i>: using python-venv</summary>
+As alternative option, you can create a Python environment by using python-venv
+
+1. Create a new Python environment: <code>python -m venv venv</code>
+2. Activate this environment; <code>source venv/bin/activate</code>
+</details>
+
+Make sure that this environment is activated when developing (e.g., installing dependencies, running tests).
+
+
+### Installing & building the dependencies
+
+We use [poetry](https://python-poetry.org/) as dependency manager for this project. 
+- The dependencies for installation & development are written in the [pyproject.toml](pyproject.toml) file (which is quite similar to a requirements.txt file). 
+- To ensure that package versions are consistent with everyone who works on this project poetry uses a [poetry.lock](poetry.lock) file (read more [here](https://python-poetry.org/docs/basic-usage/#installing-with-poetrylock)).
+
+To install the requirements
+```sh
+pip install poetry  # install poetry (if you do use the venv option)
+poetry install  # install all the dependencies
+poetry build  # build the underlying C code
+```
+
+<details>
+   <summary>
+      <b>How to resolve the following error when running build.py:</b><br>
+      <code>Unable to build the "plotly_resampler.aggregation.algorithms.lttbc" C extension; will use the slower python fallback. <br>
+      command 'x86_64-linux-gnu-gcc' failed: No such file or directory
+      </code>
+   </summary>
+
+   To resolve this error we suggest to install some additional packages as no gcc (C compiler was found on your PC):
+   ```sh
+   sudo apt-get install build-essential libssl-dev libffi-dev python-dev
+   ```
+
+</details>
+
+### Running the tests (& code coverage)
+
+You can run the test with the following code:
+
+```sh
+poetry run pytest --cov-report term-missing --cov=plotly-resampler tests
+```
+
+To get the selenium tests working you should have Google Chrome installed.
+
+If you want to visually follow the selenium tests;
+* change the `TESTING_LOCAL` variable in [tests/conftest.py](tests/conftest.py) to `True`
+
+### Generating the docs
+
+When you've added or updated a feature; it is always a good practice to alter the 
+documentation and [changelog.md](CHANGELOG.md).
+
+The current listing below gives you the provided steps to regenerate the documentation.
+
+1. Make sure that your python env is active (e.g., by running `poetry shell`)
+2. Navigate to `sphinx/docs` and run from that directory:
+```bash
+sphinx-autogen -o _autosummary && make clean html
+```
+
+## More details on Pull requests
+
+The preferred workflow for contributing to plotly-resampler is to fork the
+[main repository](https://github.com/predict-idlab/plotly-resampler) on
+GitHub, clone, and develop on a branch. Steps:
+
+1. Fork the [project repository](https://github.com/predict-idlab/plotly-resampler)
+   by clicking on the 'Fork' button near the top right of the page. This creates
+   a copy of the code under your GitHub user account. For more details on
+   how to fork a repository see [this guide](https://help.github.com/articles/fork-a-repo/).
+
+2. Clone your fork of the plotly-resampler repo from your GitHub account to your local disk:
+
+   ```bash
+   $ git clone [email protected]:YourLogin/plotly-resampler.git
+   $ cd plotly-resampler
+   ```
+
+3. Create a ``feature`` branch to hold your development changes:
+
+   ```bash
+   $ git checkout -b my-feature
+   ```
+
+   Always use a ``feature`` branch. It's good practice to never work on the ``master`` branch!
+
+4. Develop the feature on your feature branch. Add changed files using ``git add`` and then ``git commit`` files:
+
+   ```bash
+   $ git add modified_files
+   $ git commit
+   ```
+
+   to record your changes in Git, then push the changes to your GitHub account with:
+
+   ```bash
+   $ git push -u origin my-feature
+   ```
+
+5. Follow [these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork)
+to create a pull request from your fork. This will send an email to the committers.
+
+(If any of the above seems like magic to you, please look up the
+[Git documentation](https://git-scm.com/documentation) on the web, or ask a friend or another contributor for help.)
+
+### Pull Request Checklist
+
+We recommended that your contribution complies with the
+following rules before you submit a pull request:
+
+-  Follow the PEP8 Guidelines.
+
+-  If your pull request addresses an issue, please use the pull request title
+   to describe the issue and mention the issue number in the pull request description. 
+   This will make sure a link back to the original issue is created.
+
+-  All public methods should have informative *numpy* docstrings with sample
+   usage presented as doctests when appropriate. Validate whether the generated 
+   documentation is properly formatted (see below). 
+
+-  Please prefix the title of your pull request with `[MRG]` (Ready for
+   Merge), if the contribution is complete and ready for a detailed review.
+   An incomplete contribution -- where you expect to do more work before
+   receiving a full review -- should be prefixed `[WIP]` (to indicate a work
+   in progress) and changed to `[MRG]` when it matures. WIPs may be useful
+   to: indicate you are working on something to avoid duplicated work,
+   request broad review of functionality or API, or seek collaborators.
+   WIPs often benefit from the inclusion of a
+   [task list](https://github.com/blog/1375-task-lists-in-gfm-issues-pulls-comments)
+   in the PR description.
+
+-  When adding additional functionality, provide at least one
+   example notebook in the ``plotly-resampler/examples/`` folder or add the functionality in an 
+   existing notebook. Have a look at other examples for reference. 
+   Examples should demonstrate why the new functionality is useful in practice and, 
+   if possible, benchmark/integrate with other packages.
+
+-  Documentation and high-coverage tests are necessary for enhancements to be
+   accepted. Bug-fixes or new features should be provided with 
+   [non-regression tests](https://en.wikipedia.org/wiki/Non-regression_testing).
+   These tests verify the correct behavior of the fix or feature. In this
+   manner, further modifications on the code base are granted to be consistent
+   with the desired behavior.
+   For the Bug-fixes case, at the time of the PR, this tests should fail for
+   the code base in master and pass for the PR code.
+
+
+---
+
+Bonus points for contributions that include a performance analysis with a benchmark script and profiling output (please report on the GitHub issue).
+