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Merge pull request #52 from GIScience/development
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.github/workflows/ci-tests.yml renamed to .github/workflows/ci-development.yml

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name: tests
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name: Continous Integration for development
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on:
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pull_request:
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branches: '**'
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push:
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branches:
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- master
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branches: [ "**" ]
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jobs:
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lint:

‎.github/workflows/ci-production.yml‎

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name: Continous Integration
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on:
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push:
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branches:
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- main
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- master
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release:
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types:
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- created
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jobs:
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linux-tests:
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strategy:
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fail-fast: true
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matrix:
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config:
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- python-version: 3.6
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tox: 36
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- python-version: 3.7
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tox: 37
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- python-version: 3.8
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tox: 38
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- python-version: 3.9
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tox: 39
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poetry-version: [ 1.1.4 ]
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os: [ ubuntu-18.04, ubuntu-20.04 ]
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runs-on: ${{ matrix.os }}
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services:
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ohsome-api:
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image: julianpsotta/ohsome-api:1.3.2
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ports:
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- 8080:8080
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steps:
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- uses: actions/checkout@v2
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- name: Set up testing Python ${{ matrix.config.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.config.python-version }}
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- name: Set up base Python 3.9
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uses: actions/setup-python@v2
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with:
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python-version: 3.9
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- name: Python Poetry Action
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uses: abatilo/actions-poetry@v2.1.0
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with:
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poetry-version: ${{ matrix.poetry-version }}
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- name: Install dependencies
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run: |
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sudo add-apt-repository -y ppa:ubuntugis/ppa && sudo apt-get update && sudo apt-get install -y build-essential gdal-bin libgdal-dev
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python -m pip install --upgrade pip tox
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- name: Run tox
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env:
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OHSOME_URL: ohsome-api
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OHSOME_PORT: 8080
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TOX_TESTENV_PASSENV: OHSOME_URL, OHSOME_PORT
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run: tox -e py${{ matrix.config.tox }}
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v1
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with:
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token: ${{ secrets.CODECOV_TOKEN }}
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flags: unittests
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env_vars: OS,PYTHON
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name: codecov-umbrella
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fail_ci_if_error: true
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verbose: true
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build-and-publish:
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name: Build and publish Python distributions 📦 to PyPI and TestPyPI
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runs-on: ubuntu-20.04
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needs:
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- linux-tests
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steps:
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- uses: actions/checkout@v2
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- name: Set up base Python 3.9
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uses: actions/setup-python@v2
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with:
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python-version: 3.9
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- name: Python Poetry Action
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uses: abatilo/actions-poetry@v2.1.0
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with:
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poetry-version: 1.1.4
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- name: Publish distribution 📦 with test.pypi.org
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if: startsWith(github.ref, 'refs/tags')
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run: |
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poetry config repositories.testpypi https://test.pypi.org/legacy/
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poetry config pypi-token.testpypi ${{ secrets.TEST_PYPI_API_TOKEN }}
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poetry build
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poetry publish -r testpypi
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- name: Publish distribution 📦 to PyPI
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if: startsWith(github.ref, 'refs/tags')
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run: |
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poetry config pypi-token.pypi ${{ secrets.PYPI_API_TOKEN }}
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poetry build
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poetry publish

‎.pre-commit-config.yaml‎

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args: [ '--no-sort-keys' ]
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- id: no-commit-to-branch
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args: [ --branch, master ]
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- id: no-commit-to-branch
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args: [ --branch, main ]

‎README.md‎

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The *ohsome-py* package helps you extract and analyse OpenStreetMap history data using the [ohsome API](https://docs.ohsome.org/ohsome-api/v1/) and Python. It handles queries to the [ohsome API](https://docs.ohsome.org/ohsome-api/v1/) and converts its responses to [Pandas](https://pandas.pydata.org/) and [GeoPandas](https://geopandas.org/) data frames to facilitate easy data handling and analysis.
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The ohsome API provides various endpoints for [data aggregation](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=Data%20Aggregation), [data extraction](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=dataExtraction) and [contributions](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=Contributions). Take a look at the [documentation of the ohsome API](https://docs.ohsome.org/ohsome-api/stable) to learn more about the endpoints and query parameters or go through the [Tutorial](https://github.com/GIScience/ohsome-py/blob/master/notebooks/Tutorial.ipynb) to get started.
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The ohsome API provides various endpoints for [data aggregation](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=Data%20Aggregation), [data extraction](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=dataExtraction) and [contributions](https://api.ohsome.org/v1/swagger-ui.html?urls.primaryName=Contributions) to analyse the history of OSM data. Take a look at the [documentation of the ohsome API](https://docs.ohsome.org/ohsome-api/stable) or go through the [Tutorial](https://github.com/GIScience/ohsome-py/blob/master/notebooks/Tutorial.ipynb) to get started on how to use *ohsome-py*.
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## Installation
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The easiest way to install *ohsome-py* is using pip:
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*ohsome-py* requires Python >= 3.6. The easiest way to install *ohsome-py* is using pip:
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```
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$ pip install ohsome
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```
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To install the latest *ohsome-py* version from GitHub:
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```
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$ pip install git+https://github.com/giscience/ohsome-py
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```
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If you want to run the Juypter Notebook [Tutorial](https://github.com/GIScience/ohsome-py/blob/master/notebooks/Tutorial.ipynb) you also need to install `jupyter` and `matplotlib`:
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```
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time="2020-01-01",
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filter="landuse=farmland and type:way",
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properties="tags")
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response_gdf = response.as_geodataframe()
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response_gdf = response.as_dataframe()
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```
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Responses from the data extraction endpoint can be converted to a `geopandas.GeoDataFrame` using the `OhsomeResponse.as_geodataframe()` method, since the data contains geometries.
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Responses from the data extraction endpoint can be converted to a `geopandas.GeoDataFrame` using the `OhsomeResponse.as_dataframe()` method, since the data contains geometries.
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### Query Parameters
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‎notebooks/Public_Green_Spaces_in_OSM.ipynb‎

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"metadata": {},
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"outputs": [],
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"source": [
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"radius = 10000\n",
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"radius = 5000\n",
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"cities = {\"Tokyo\": [139.7594549, 35.6828387, radius], # lon, lat, radius\n",
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" #\"Berlin\": [13.3888599, 52.5170365, radius],\n",
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" \"London\": [-0.1276474, 51.5073219, radius],\n",
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"##### Import modules"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.append('..')"
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]
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},
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"cell_type": "code",
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"execution_count": 4,
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1.0 How many public green spaces have been mapped in each city?"
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"### How many public green spaces have been mapped in each city?"
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]
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},
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{
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" time=client.end_timestamp, \n",
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" properties=\"tags\",\n",
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" filter=\"({}) and type:way\".format(\" or \".join(tags)))\n",
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" greenspace_city = response_geometry.as_geodataframe().droplevel(1)#.loc[:,[\"leisure\", \"landuse\", \"geometry\"]]\n",
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" greenspace_city = response_geometry.as_dataframe().droplevel(1)#.loc[:,[\"leisure\", \"landuse\", \"geometry\"]]\n",
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" greenspace_city[\"area\"] = reproject_to_utm(greenspace_city).area\n",
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" # Create tag column\n",
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" tag_series = []\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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"version": "3.9.2"
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}
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},
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"nbformat": 4,

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