From 5d5b0c466666e5ac238b14a2c938ffc5f8be2458 Mon Sep 17 00:00:00 2001 From: Dom Date: Fri, 23 Apr 2021 09:40:57 +0100 Subject: [PATCH] Add support for Bokeh and Plotly (#15) * Add support for Bokeh and Plotly --- .gitignore | 4 +- .travis.yml | 16 +- Makefile | 4 +- docs/01-getting-started/quickstart.md | 2 +- docs/02-user-guide/examples.md | 26 +- docs/03-api-reference/adaptors.md | 13 +- docs/03-api-reference/content.md | 4 + docs/examples/interactive-plots.ipynb | 12390 ++++++++++++++++ .../{iris.ipynb => iris-report.ipynb} | 0 docs/index.md | 2 + esparto/__init__.py | 17 +- esparto/_adaptors.py | 38 +- esparto/_content.py | 224 +- esparto/_layout.py | 27 +- esparto/_publish.py | 85 +- esparto/templates/base.html | 21 +- poetry.lock | 234 +- pyproject.toml | 13 +- tests/check_package_version.py | 19 + tests/conftest.py | 52 +- tests/test_adaptors.py | 22 +- tests/test_content.py | 19 +- tests/test_publish.py | 13 +- tox.ini | 25 +- 24 files changed, 13098 insertions(+), 172 deletions(-) create mode 100644 docs/examples/interactive-plots.ipynb rename docs/examples/{iris.ipynb => iris-report.ipynb} (100%) create mode 100644 tests/check_package_version.py diff --git a/.gitignore b/.gitignore index fe33072..c939b39 100644 --- a/.gitignore +++ b/.gitignore @@ -1,8 +1,8 @@ # Scratch files for testing scratch.ipynb scratch.py -esparto-page-*.html -notebooks/*.jpg +esparto-doc.html +docs/examples/*.html # IDE files .vscode diff --git a/.travis.yml b/.travis.yml index 0811cdc..b994d60 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,21 +1,31 @@ +sudo: false language: python os: linux dist: xenial python: + - 3.9 - 3.8 - 3.7 - 3.6 +env: + - INSTALL_DEPS="" + - INSTALL_DEPS="--no-dev" + before_install: - - pip install poetry + - curl -fsS -o get-poetry.py https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py + - python get-poetry.py -y + - export PATH="$PATH:$HOME/.poetry/bin" + - poetry config virtualenvs.in-project true install: - - poetry install + - poetry install $INSTALL_DEPS -E test script: - black --check . - flake8 - - coverage run --source esparto -m pytest + - mypy esparto tests + - coverage run --append --source esparto -m pytest after_success: - bash <(curl -s https://codecov.io/bash) diff --git a/Makefile b/Makefile index 6569769..7ead546 100644 --- a/Makefile +++ b/Makefile @@ -61,9 +61,11 @@ mypy: ## check type hints test: ## run tests quickly with the default Python pytest + python -m tests.check_package_version test-all: ## run tests on every Python version with tox - tox + tox --skip-missing-interpreters + python -m tests.check_package_version coverage: ## check code coverage quickly with the default Python coverage run --source esparto -m pytest diff --git a/docs/01-getting-started/quickstart.md b/docs/01-getting-started/quickstart.md index a282365..be8731d 100644 --- a/docs/01-getting-started/quickstart.md +++ b/docs/01-getting-started/quickstart.md @@ -57,6 +57,6 @@ Esparto determines that the string points to a valid image and loads the file:
-Please check the [examples page](../02-user-guide/examples.md) for a more in-depth guide. +Please see the [examples page](../02-user-guide/examples.md) for more.
diff --git a/docs/02-user-guide/examples.md b/docs/02-user-guide/examples.md index 7cd41b0..c07e4f6 100644 --- a/docs/02-user-guide/examples.md +++ b/docs/02-user-guide/examples.md @@ -1,13 +1,13 @@ # Examples -### Data Analysis Report +### Data Analysis -[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/domvwt/esparto/blob/main/docs/examples/iris.ipynb) -[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/domvwt/esparto/main?filepath=docs%2Fexamples%2Firis.ipynb) +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/domvwt/esparto/blob/main/docs/examples/iris-report.ipynb) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/domvwt/esparto/main?filepath=docs%2Fexamples%2Firis-report.ipynb) The iris dataset is one of the most well known datasets in statistics and data science. This example notebook shows how we can put together a simple data analysis report in esparto. -This example covers +This example covers: * Text content with markdown formatting * Including images from files @@ -15,3 +15,21 @@ This example covers * Adding plots from Matplotlib and Seaborn
+ +### Interactive Plotting + +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/domvwt/esparto/blob/main/docs/examples/interactive-plots.ipynb) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/domvwt/esparto/main?filepath=docs%2Fexamples%2Finteractive-plots.ipynb) + +The [pandas-bokeh](https://github.com/PatrikHlobil/Pandas-Bokeh) library offers convenient functions for producing interactive Bokeh plots +with few lines of code. + +With the [Plotly backend for Pandas](https://plotly.com/python/pandas-backend/) +we can access the Plotly Express API directly from the '.plot()' method of any DataFrame or Series. + +This example will show basic examples from each library: + +* Interactive plotting with Bokeh and Plotly +* Adding interactive content to the page + +
diff --git a/docs/03-api-reference/adaptors.md b/docs/03-api-reference/adaptors.md index 4bcbd30..ccb7a33 100644 --- a/docs/03-api-reference/adaptors.md +++ b/docs/03-api-reference/adaptors.md @@ -2,13 +2,20 @@ !!! info The ```content_adaptor``` is called internally when an explicit Content class is not provided. + Input objects are matched to a suitable Content class through [_single dispatch_](https://docs.python.org/3/library/functools.html#functools.singledispatch). + ``` python import esparto as es - # Create some new Markdown text - markdown = es.Markdown("Example _markdown_ text.") - + # Text automatically converted to Markdown content. + section = es.Section() + section += "Example _markdown_ text." + print(section) + ``` ``` + {'Section': [{'Row': [{'Column': ['Markdown']}]}]} + ``` + ## ::: esparto._adaptors diff --git a/docs/03-api-reference/content.md b/docs/03-api-reference/content.md index e0c9e3b..e18475b 100644 --- a/docs/03-api-reference/content.md +++ b/docs/03-api-reference/content.md @@ -22,4 +22,8 @@ ## ::: esparto._content.FigureMpl +## ::: esparto._content.FigureBokeh + +## ::: esparto._content.FigurePlotly +
diff --git a/docs/examples/interactive-plots.ipynb b/docs/examples/interactive-plots.ipynb new file mode 100644 index 0000000..6307988 --- /dev/null +++ b/docs/examples/interactive-plots.ipynb @@ -0,0 +1,12390 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Oy98EV4EJcOy" + }, + "source": [ + "# Interactive Plots with Bokeh and Plotly\n", + "This notebook demonstrates how we can incorporate interactive plots from Bokeh and Plotly into a page.\n", + "\n", + "\n", + "We will look at:\n", + "* Interactive plotting with Bokeh and Plotly\n", + "* Adding interactive content to the page" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "C30QlbKwJcPE", + "outputId": "162f1970-6e9c-42a9-f5ae-de6341e93dc8" + }, + "outputs": [], + "source": [ + "# Environment setup\n", + "import os\n", + "!pip install -Uqq esparto plotly bokeh pandas-bokeh\n", + "if os.environ.get(\"BINDER_SERVICE_HOST\"):\n", + " !pip install -Uqq pandas" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "0Pzi4t5EsUlq" + }, + "outputs": [], + "source": [ + "import esparto as es\n", + "import numpy as np\n", + "import pandas as pd\n", + "import pandas_bokeh\n", + "import bokeh as bk\n", + "import plotly" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1002\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error(url) {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (let i = 0; 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\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1002\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.1.min.js\": \"YF85VygJKMVnHE+lLv2AM93Vbstr0yo2TbIu5v8se5Rq3UQAUmcuh4aaJwNlpKwa\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.1.min.js\": \"KKuas3gevv3PvrlkyCMzffFeaMq5we/a2QsP5AUoS3mJ0jmaCL7jirFJN3GoE/lM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.1.min.js\": \"MK/uFc3YT18pkvvXRl66tTHjP0/dxoSH2e/eiNMFIguKlun2+WVqaPTWmUy/zvh4\"};\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bk.io.output_notebook()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ABCD
2000-01-01-0.153236-2.4325090.507984-0.324032
2000-01-02-1.664313-3.303931-0.3568460.284717
2000-01-03-1.102675-1.7891800.291079-1.066933
2000-01-04-2.511884-0.6584551.857765-1.304681
2000-01-05-1.953081-2.163346-0.086156-2.478704
\n", + "
" + ], + "text/plain": [ + " A B C D\n", + "2000-01-01 -0.153236 -2.432509 0.507984 -0.324032\n", + "2000-01-02 -1.664313 -3.303931 -0.356846 0.284717\n", + "2000-01-03 -1.102675 -1.789180 0.291079 -1.066933\n", + "2000-01-04 -2.511884 -0.658455 1.857765 -1.304681\n", + "2000-01-05 -1.953081 -2.163346 -0.086156 -2.478704" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# From: https://github.com/PatrikHlobil/Pandas-Bokeh#Examples\n", + "np.random.seed(1)\n", + "ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))\n", + "df_lines = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list('ABCD'))\n", + "df_lines = df_lines.cumsum()\n", + "df_lines.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"D\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"1XzoBcd1A8C4bq4nc24KwGIHt2l7oPy/WFEf4w8S5b/yxsZpiE4BwJ6mqMtPegXAtwN6HmQd9L/My3nvNoT8vxHHGJoYYwPA+YlDepoZB8AIJTEZKkgCwBacMH6Fpw7Aoq+LXrHoEsAzf74kwkMVwIb3HbKpZw3ATPSN2NDoC8BjajeHUdYJwFKJteJdVxDAZBrwVg1z+79oHX0+5A/jvxivVDFVtNu/ju5Q2p616r9BuMNsisgEwHdxpwRwNAPAirrqzAj9AcDcAZ5pZMTQv1N9jIjqW96/+GgGVz8E5T+yEzQc+NPcPzkgXDhU4eg/NkEON5u4/j+RbK+m08T6PzJ4BdTxnvg/QmZiotNe+T9TBGETsTf8P/ncS4FpIvo/ryGw+4eIAUCfxodnwqUAQE6PoRmVvw5AVccYVTeKD0AavJaRU7MJQEtqhmEFqf0/fRHYCgBwCUDCEkYmPuURQI/uahMqMQxAKYttQvRBCkCZMr6JB9QMQCBNkv+P/QRAGOqMCuqc/j9gX+4dYbfdPxCydBEUvPE/NyOn/uUIAkCdnLNsirsQQP6eNh5xrgxAHhPf2jT8B0Cu6MMq6xIPQFxSZ6571BFAj9Fqq85/HUAr5wclkNEdQHrefnoKkBtAXLqq3zWmGEAG5Q/KdLgbQFhswEqFzxhAF9W3ITZ/FkBSttbFCS4dQOv3IOfz7xxAwH0lF1rEG0CoYm3MGKUcQIxxmJS6DB1A1HqmqnbWIEC0u27L1KcgQIknLd9ALCJAANmh6LArJEA+JauXx2IkQB23m9DEAyVAoBZRSah2KECBWn1VPYgnQJ4UZyOQ9yhAX8d+3MZzKECYoK8jmxsqQF1F4To1fCdABJeWtcBOJkA/JziTTHQlQON3OruGMiRAk9VXmTQNJEA5Kk1AfBEkQNoqZBGzuCFA5i6nSlaVJED/6m0KIVolQLOnVT4MNCZABbhh2CG5JUA+TgPY7Y0nQCb4h3msNypAICzfj2cgJ0A0n6B3jf8lQD6fXLWMZSRAjeSauHIZI0CVV33AxsAjQCCuf9t+Gh1A9BYit5QEIEC2erd0PHciQOsJyWXuoSJAoocfxNdhIkAujJI73kckQH/7LPMcISlAdBbfBhMTKEAwSkJZabcoQN+k6ydUYChAzZI9ObjaKEA+6jQ4uNwpQHFZFhnkgipAlp8ct1jRLkDsTtBMFPsvQG17UXPDmi9A29QXRKyaLEC/CAZFrsYtQJUV8JSRKzBA/LQr7S0ZK0CwLTy+O70tQOlzTWW2HC9AkKR5bsJALkBtRsrHmJkrQIPyoW9jkSVAUItJaSFFJUD/XR9asNkkQPPQIn6+OSRAWsVFQ0vlJUBsHNDHyDsoQOApbg/DUyhAByvspDhuJ0D+CaTHotYlQPO+YNqYHSVAX8Sia197I0Ced/QFd7QfQDRxzQEiASBAmOVf6LliG0CogJKlzUoXQDzJbTTLhBJACDW9teOnFUCeFuzeDwsaQDYJHDs5px9ArsKvqLY9IECiHazoOQ4ZQD9NfYRpfRtAzjdfSs1YFUA76Bh9CBAHQLXKCQFgiARAeGLZDWPbCECZ2ew4Gj0QQJ4sLhWDDQpAqwGhD3RTEUAFCd0aMncUQPxfdpVYYhJAR8GzDZpdEUD+SXv3j5wLQH52HFpgCgNAtFcKm/y1EUDSdKHS6G4LQCett4iAchtAAAtUUgdcG0BpxeEfQ6sfQIWII/zm9xlAb0ZhrJ8BHUBL9EQB9ysgQK/rNw+sZiFAZlbUmUa3IEDapzVzUHQaQIp+2819LxxADEISqSWWFUC8mSec3EkVQEbBk5lxiRNA8V/9GYaKE0A5bd8/nXgRQIH1YxJKVgxAaoT6svFdFECPXMejXM4UQESSt8O5VhBApMjBsmtcGEDX5xJVAZ8OQODRXG5hwgpA2VTiMCgVB0Da5TGIxywSQJNvTY9yIhJAok4gjsmpEEAoCXfC/doQQEDT85RHqhdAZbXDfIizFEB4yaFb2AEYQHgI7UopRhlA3BRrOzA1HkAtPl7Eu3IfQHITdMnipiFA3A3OjpvRIED9UfeLYu0hQGbAjxjxZCFAeDtQZtXEIUDKIA6V/QojQCoGme54YyNAV3fgTkxBJUDPxXkwyEApQM4SOh6mMixA1wD5OYMmLkBeIoKAp5krQFCRlvWJ9ypAnRySFDJaLEBDgVwxKh4sQCWu1M4qZClAm0Bojxh1KUCZzQ//V8coQFYKW+NGSSdAbDRN4m7RJ0B9AquTz8EqQLaOlKlsrChA8TuhtoHiJkB2lbPMDRQqQFEUwGWPuylAWcp1qVEiJkDcFo59sRcmQJEv3Tm1/CJA/oz851/VJUBlQqj7FaslQKqSyA0+wiZA715LnaMcJUCmfpZQco4mQKYEnH1lQyVA8bDYAli8IUB2dZZtvp0iQJQcDt29HCBArGzOsEzlHkDaRLjFm1QhQHB8unaJTiRAIWqLwJUiI0CxILXonWQiQGpkzkc/LCJA+bG2y1MSH0C+YrTHjIUZQGcByLyNRBdA+TXGYRW/FkB9m0QLB3EYQOfggrHWlhBAKzuGtR2FBkC4KZGe2x0DQNxQhNPcbwVAAyRxj4y4B0Cel2ks+UD6P8BblJpsgQ5AJIAzZp1UB0DYw7rUm0ICQCJFrALEA+w/0JSh53Gnp7+fN1VdAKfIPytFdH0Mnuk/wMYaMJb1jD/FVkJCGW/HPwsVy+MEuv6/PlVAgo+4BcAKo8oZFsMCwMImCwiPOQjAxiiZIQ+IDsDyID5e2gwEwHzlyU8Kivm/Zx4Hf57f+r99yKnGXR/3v1Qzk7n2+QXAR3ZwqtoVBcAAtyV/E5z+v+wYin/ULwnAXWj7ieny/b/eW5nUzLX5v2ZVBI+jQfa/qInWjhJixL8eMRiMAmn2v/uImum0HQbApJ0+vCZ6DsDMmYmeACf7v0s6LTptawbAB9fenGkHBMDwQZKfkWMMwOIPYpAn9wXANnkgkP1g9L+NEv4SmNwBwHYaI4LeBwnAojo+dcchAMB+Y4OxAJwCwMhm7Pg7NAXAjpW0pjs+E8AxVyEFz8YVwAxUegsiuxTAkW25+DL2FMCEPsF3cQsbwFyABatNaRfAPWz8/Z8rGMCZxoZYY1cdwJ3bzI3CZxrAuTuetVjKGMBW1l55qVscwAwvYNE80iDAMJ1TgTIIIcAU4QkvIygcwNcIpeQWRCDAwq3PlSovIMBTj4jBqrIhwO38EgW1RiPATI+6P3KFJMDU/UveTz0kwAAsJoNu3SLA1hMtG5A5JMBuHToGckQjwOQAPYeC/SXAXkJxTqGtJMDLGLEAz+wkwIfb8XjlXCXAvoqIsh9MJMBQjNMdUOIgwE3uQIfv5SPAJ5Fn4R/aJMBiGSywtuEjwJAc196kpiPA4URlHUG9I8A+SX3/DTQlwMw0ZlFTXSXALfEVg2KaJMCv5ZSvopQlwO75mM+WRyfAzLsOXUU9JcCHlGGvnhYnwLxSd/gITifADAKVsP2VJsBd0bI42BcnwOpAzCW2+irA0F5gZV+GLcBBdBpiSZEuwCAN4QWXDy7A+e0i0wsvLcAklK1bfe0twM78DUoQZzDAX/EQAonNL8CDHztrCtsxwOWPn6RFgzHAQYHxRW7yMsB/h4ZdCWgywJlCJ9GrDjLAdVoGE2UyMcD2H8VHM8ExwObVjKeanjDAuSTn0qQJMcDzZ92ZlecxwJwA4J/oDzPApMTYyTquM8AviM6/KlE1wOf0ocCRLTTALJc/NL9YNMBQbHY5/W01wPZYAn0P9DTAicmdC8iFNMBR1tKXUNYzwDY18wURjTLA3bN5Tym+MsAnz7mFrHozwMgd/xe4RTTANh0cFUaRNMB4m+3Nxwg2wFHXZwW+fzbAmmqcUoGWNcD8Sn6Lt0w3wP90gC+KlzjAgkGzkJZjOcDyOAwDfbU5wDENbV21qTjAWYLnlQ1SOcCjat1wglM6wH/qCgHVhzrAxN/ymbkXOsBKQdWr3Fo6wGyET8zZkzrA8/jaBDSXOsC7BKqGTtg6wGhvW2LM7zrA4jiOQsvXPMDmejW5AkM8wP+egtA9NDzA88RroXQZPMAhgJLu3BI+wE6z/DhR6jzAIdEFSlKNPcAsCbV8Smc9wBrl0x6jmz7AcTLTMlF1PsB8g8HB8p4/wDmRsznTaUDAlNuMjbGYP8Ap1w1pqZQ/wEWCiWZcoD/A1jm45+xNPsAEaqf1Ebs9wN0DJ8imSjzAg2hZyINyPcCQ5Em9UQk+wOYg40Umnj/A3aaBXz9CQMCIe5AZzJ1AwCC4xz2cJEHABV4AOwpgQcCjyxwgfspAwJLc1oDbK0HADmE5+3zeQMALEfuLMj9AwDS87Uo+EUDAThyk71E3PsC5X6ldjUA9wK4lyJEtwjzAwkH5B8nkOsBTxfqpd6A5wCXXFbaLFDnAKhsrw/NpOMDUAD4iFqM3wM/jEV2dfDfA1H1WjdkbOMAWYdRxHVg4wEvX949ZYDrAsN58oaSuO8BRK+wZF5Q9wFpcKbcfUz3A7Ar8mcEePsAlP6Q1naA+wKqtXxDEcj/Av3r4qC78PsBUQhhb/zs9wO/5QaivVT7A6zRQG9FkQMBE7Ai2M7dAwDcE22DcQEHAqxSG6I9DQcDvzE0te69BwPKjMuAXvkHAQhbOj33mQcCNZzgHmWNCwB7oEJAQWkLAVnrDY7LeQsApM4sxdnlDwJaBLIeDKkPA93Rj8fiBQ8CVPbM729ZDwMxqyJz5/0LAPr84qrCHQ8BQ7BKySclDwFKHeLytokLAUVwTq8rDQsBCRcsWd9tCwFn3ps7zMkLAnMUa+vtWQsDZ8LXJUIJCwOqcQg7rzULAzUUNJnJaQ8ByF9RG7VJDwGiTqgdy4EHABcrY2NNSQsAl1XI0aVJDwJzlggNhfkPAtGHbZTvHQ8BVLvfCiJtDwBlJO7DsiEPA1r17RmvFQ8D0brM+KlxDwCe/3Rn0qULAXdKnEe0XQ8AQIaCavyBDwBtxRnHBR0PA2QlzJa6GQ8BggejaDqxCwA6Qvdab00HA5z8R56HSQcBU29pBomBCwJ7gteDDuULA1XycesKZQsCIo2JcsldCwK0i1P1dGELAHUcza3puQsCSLUk+FUNCwLMJzkqgGELArHnJR3GqQsBrtFlvO7VCwArP2dHzJ0LAqcwB0bTkQcAEBOhQMTVCwDyPCK7GL0LAnqpK1J52QcBHymGsvt5BwLMIW1iAgUHAbeM+HYXFQcAwSsb+kMtBwCgKsCbpUELA+wYCV3J9QsAIGeAkuO1BwHjxykt+60DA7EPSdpPQQMDIihx3Ip5AwAMGUL7xwkDAq0jJGxulQMBdDzvsY7hAwDjdh+fJnUDAOKXqvtvMQMBfSgehe88/wHwBVhRlGUDAq4ENBnjkP8A1curLgwc/wGSpoD2qvT7AUmMV3+ApPcDE7Lw66FI8wFjTMEk1pD3AY2s77tEOPMCTJLdrbHM8wCYZcPFXgT3AwhI09lUsPsDVT97c/nk9wIHLgIWgtjvAR9exXuIgO8BP8Bekz+s5wM+jqgLsgznAltRyYiVAOsBCABqkfik4wMfEkXJYZjjAECz9PyFEOcD/6BrrDsg4wJ/GkCBZ5jnAVIxu8sVMOcDRJV6C5Ow4wH/5oXEmHDnAIMeAUCaON8DAnfAsPRE4wHn+YAYbWjjAPpBWAfggOcBKi1Btisw5wCKwsmzmSTnAHNiUiarSOMDETn65M0s5wGqvRjkqwDjAa6RIDFeuOMD7FU1NEQw5wE0IGTzxdjjAOG1b9WggOMDwE1NWuA05wFVk1ximaDrAUdC6NyITOsAx6vNtxXU6wNriEXKxGjvAKVAQ+8mAO8DmzqjufqA7wBISngsB4DrAW95hzLUfO8AKU3fC5aQ6wBMQI3A2tTrAiEqFNFjlOsC2+NbE3OU5wIdNsZ9H/jjA9Y26GywwO8D6NcdMcbw6wD49YL+3hTrANJjUVDVSOcAPAiZJY+s5wEAfsDFx1zvAJZti/2yoOsB9Cl8GMKU7wJ8s6abIpDzALUwGDPVhPMAveBw6SVw9wC6P61IXjDzAQm3zmkP1PcCyqJ6NY1s/wODB+gacVT3AAOlYWxYBPsAwytZTcw4+wLkCzI0dET/A7r/0nAv0PsBjkj2UQD8/wNZ9w/XyiD/At24lhll4P8BYYfh6ph8/wGY/CkECJz/AuRdJ81cbPsCxPdp3cb8+wJcPmD0cHEDAOdyPtAKKP8AFVO9o/hc9wJpsgrOrbD7AyFLI/XjYPsCxy8I5RbI+wJcR4ikpwz3Aolzv9vRAPsA5UneTgnM9wEmi4ZnztjvACb/5pSqYPMBPPLhhAbY7wBZ8tD1+czvAayhPJEYeO8CMbLXRxuo8wAvIOoPAJz3AdGVM7VkEPsCalFtfPbM+wNK2NYKqyT/ACunSSc5KQMBDuggYzt9AwJT2mUZUBEDAmNnVfR31P8CqW5YV8hA+wC92hXT1ezzAQ0J8EJriOsAVG1ypwOU6wDdfFdkzOzrAYnDhUGikOsC4Gmn5TmY6wH9CzKo3+zrAq4f00chhO8AwQXWsLIc5wFX+QXLA6jnAWSjSspZ3OsBnsg8lL3o7wIvseyKVfDrALY1JO8DbO8DkjuUwfAQ8wC2aMtX18TzAQpJ4gGkQPcBe4lJF3049wMaNkpmxpz3AKlBoR2VuO8A6I/MXK0k8wBrKUTvHwTvAE5OzN6z0OsBDCHZc9Bg6wBKSJ/TOwDnA5KjB8cZ2OsAuhePMX6c5wIZ2BxrJgTjAJx+b1WmbOMCc/TCg9EE5wLIDay1IATnAL2f4Y1vlOcDtVDUWcEs6wHjRBdUsgjnAm2EYztdLOsDO+hpXm/o7wIXFGN6PXTvAVCh6uCeMO8CSJ5/LFRc7wBen+YA+mjzAstTB3C+RPcC+Ryiwzak9wAm8BJAdYT7AXfm3oD6mPsD9CZa/cmw+wNDGKjubsT7ArS890BkWP8Db4oPjr0Y/wAcuF/lUb0DA0W5TNYR+QMCuo05rL9JAwJTYW327M0HA7Hr9HN4DQcAHIrX6hwlAwK/akLO120DAx63PxPAZQMANbtCcOgFAwHDiU3vxAz/AqS91piLLQMCTFD/RWiNBwKm5yDPCFkHANn2Jw+fiQcDlcKJqg9RBwBDE2IDMVUHAD4qG8u+JQMAsOjik6Pg/wJ+tQvXpyD/AI/X3mLT/P8DqtjpfmQFAwEGgL0dJoD/Awd/GzVe1P8CnsHwsxMM/wLCJjD8GWkDAbyhHzIswQMBBhiLBLs9AwCw0qWwpBUHAJo/nvgngQMCd3AHE2ulBwH1H7C2xNELAadvlxsL8QsBT4XWWpaRCwAbnUjfojULAWJjRBXLHQcDebNKKJH5CwNKYalV2BULAGH5KSXsgQsDxXNq8RU5CwFvYJ7YGG0PAI0gIiwh9Q8C6B0CVXEZDwJ2ZYXZL5kLAcs3n271TQ8BeAScvjLhDwB+8nTouiUPAjI+R878yQ8AYXVA5T5RDwNs0w30iokPAKbslE+FrQ8ALcU6TrF5DwHxHBTzaukLARB7y3PczQsBcaBu1QpZCwME55WhklULAP/SV0aI/Q8AHgjpJy2lDwHW9QlOCzkPAWGuYiTs8RMCr4M+3hTRFwJ7Ee5W53kXAc4EhRhndRcBtNOmn54FGwG3jthfKykXAS9LZj84PRsAlYxBNAsdFwEaMoh1iGkbAMY2DK6TORcAEEv64CZVFwLRSpU2uykXAJV5NOrWhRcDpmMY0Ym1GwMuY+HBcfkbAlzp0Q6u/RsAFqwdCupNGwNZsspklOUbAJB8ZsquDRsD1TJUNa0BGwCqgmKw+4EXAzxUkchd4RsAIvNXaUcZFwOhg1gsiNUbAcbETzMeORcCYZeYQdHJGwEAtBm4GuUbAIB5vR0MgRsChH7b8ElpGwMIsArdk4EbAKW57SJ5jR8BTIuOvVm1HwKUOlOB1dkjAQBWWyvqDSMDLQ3R6gTBHwIFxJ/IW00bAMj3AmdadRsBarR5WPwZGwCM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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"littl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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"D\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"D\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"D\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"AACA9VmNa0IAAADB/o1rQgAAgIyjjmtCAAAAWEiPa0IAAIAj7Y9rQgAAAO+RkGtCAACAujaRa0IAAACG25FrQgAAgFGAkmtCAAAAHSWTa0IAAIDoyZNrQgAAALRulGtCAACAfxOVa0IAAABLuJVrQgAAgBZdlmtCAAAA4gGXa0IAAICtppdrQgAAAHlLmGtCAACARPCYa0IAAAAQlZlrQgAAgNs5mmtCAAAAp96aa0IAAIByg5trQgAAAD4onGtCAACACc2ca0IAAADVcZ1rQgAAgKAWnmtCAAAAbLuea0IAAIA3YJ9rQgAAAAMFoGtCAACAzqmga0IAAACaTqFrQgAAgGXzoWtCAAAAMZiia0IAAID8PKNrQgAAAMjho2tCAACAk4aka0IAAABfK6VrQgAAgCrQpWtCAAAA9nSma0IAAIDBGadrQgAAAI2+p2tCAACAWGOoa0IAAAAkCKlrQgAAgO+sqWtCAAAAu1Gqa0IAAICG9qprQgAAAFKbq2tCAACAHUCsa0IAAADp5KxrQgAAgLSJrWtCAAAAgC6ua0IAAIBL065rQgAAABd4r2tCAACA4hywa0IAAACuwbBrQgAAgHlmsWtCAAAARQuya0IAAIAQsLJrQgAAANxUs2tCAACAp/mza0IAAABznrRrQgAAgD5DtWtCAAAACui1a0IAAIDVjLZrQgAAAKExt2tCAACAbNa3a0IAAAA4e7hrQgAAgAMguWtCAAAAz8S5a0IAAICaabprQgAAAGYOu2tCAACAMbO7a0IAAAD9V7xrQgAAgMj8vGtCAAAAlKG9a0IAAIBfRr5rQgAAACvrvmtCAACA9o+/a0IAAADCNMBrQgAAgI3ZwGtCAAAAWX7Ba0IAAIAkI8JrQgAAAPDHwmtCAACAu2zDa0IAAACHEcRrQgAAgFK2xGtCAAAAHlvFa0IAAIDp/8VrQgAAALWkxmtCAACAgEnHa0IAAABM7sdrQgAAgBeTyGtCAAAA4zfJa0IAAICu3MlrQgAAAHqBymtCAACARSbLa0IAAAARy8trQgAAgNxvzGtCAAAAqBTNa0IAAIBzuc1rQgAAAD9ezmtCAACACgPPa0IAAADWp89rQgAAgKFM0GtCAAAAbfHQa0IAAIA4ltFrQgAAAAQ70mtCAACAz9/Sa0IAAACbhNNrQgAAgGYp1GtCAAAAMs7Ua0IAAID9ctVrQgAAAMkX1mtCAACAlLzWa0IAAABgYddrQgAAgCsG2GtCAAAA96rYa0IAAIDCT9lrQgAAAI702WtCAACAWZnaa0IAAAAlPttrQgAAgPDi22tCAAAAvIfca0IAAICHLN1rQgAAAFPR3WtCAACAHnbea0IAAADqGt9rQgAAgLW/32tCAAAAgWTga0IAAIBMCeFrQgAAABiu4WtCAACA41Lia0IAAACv9+JrQgAAgHqc42tC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EBrw7AH93eYYG4BcCcZtdrGW4DwPxsH82IuwrAnksniemHBMC1kVafr5kPwLpjA20cmg3A9fqgPGQSC8D4FezBg1kAwEsW/C6zjQLAL7jyyhIyAMAA3pgF3XDxv27RFMDaEOU/ihKlO/EH5D9wzRsG7oTgv/gpZei5gQLAgWMo2emL+b+a5usJt4AFwO8iXu23IQvAMUNupjTo/7+KivUVhr/zv5b67RTcmuy/l64rcVFcBcCZRHTSSPsKwDlYcGHT7hTAOZNX8lPkEcDk7iiW1JoawCW5lCbrmR7ALGLgr0d4IMDFWZhQUmkgwEzDnmLliSHAx1ZAreZQHsC81XwKgEAgwAjWocxC3R/AhKC+SkuHG8C8ocKXJJsewGjaCssGchrAOnfZA9s/GMB417RB5eYYwKgis0r4xR3AXtbYynRMHMBXpVVYKBQdwNZJ+P5PtyLA1Cl8MpTFIcClX3kHoeofwBrzBeBuwh3ARo14UCJYHcDme2iRxeQawGrhtUxMOx7ARJChfGa4HMCPygWrA4sdwBuQE86qThvAUd6l/NLWG8Dwp/wK2HIVwGqjp7WjhR3AWDQl4oZgGcAlWTnvtfkbwDoj0rfImxrAFgAxW5sEIsB+A9AOgoEhwItVWd99WyHAysUChKAQHsAZVmRHrOgfwH7H5FuTeyDADeyVyR0TH8AkJSfqw2kewDjuOK+qHxrADxEW2zTXGMCz8aBTGQMcwAow0iyPDBrA1kcleUt3GsCMxPdkhoAWwM+Sp70lFA/AzFNpa81hAsD0LIV8rK4OwBMOP2MedwzAC62QrNuxDsCLExyDEk0AwBbuaNf2oAjA6qJ1RBxWD8CAX72/ovIEwLFvr/F4JQHA3ld4XXHs+7/4rdT3WUfzv06SWnTmiPq/MemZl9zG6L9+0yeNviHTvzS+xaYI/OG/Wvxfxc5v478m2x/XwNzTPxRsrZqmOfE/BssEcsGmAkAqyhoiRqDmPxT0AccBfgtAyLwZhZtcAkCxxlc66q8BQDwQhXst4fc/RBtDT06vAEBcpCGeY/PzP4cxqK5OowBArp44BeCI8z/03/INh4f3P9JrEG/ZQwBAzRY+U1I99D+ZPVgRfAfhPxVBZebhiOK/0KICCwNR878p22fEi28IwDwrLqFivwTA/bUK8XIFBcAI62HGImgCwKoqn3JnBfq/nI3t5BES+r+EYTkADpz7v58ReZvFpgDATIZ+8D0qDMAwJFV1kdEMwEqhj2tNRBPA1EToO14rFcDhX08hly4UwJ6lheZKexfARkPeXwrTEsAMmftQ/X8VwPQY7/aZThHAtqxFIAhkE8AHzsY66METwOkbAR1MwBXAPZ5sb+VlFcBZh5ckdl4VwLey/THfUhXAY5L1PKWtF8A+Tn6sboEYwBZ1GFRphhbA4htuxcwTF8C0+tS6o+oXwA+YUDDTlhfAI+aLE5LeF8CUTqD+hzYfwHQb5X3kNxvA6Yim0xl6IMD5v5HSXosgwJ+G0Vme5x3AbSDj9ut7HMBRnmsVSiMfwEMXmj478CDA8ojgdazdIsAy/H+6AcIiwKTlHYY4NSLAT/whmKc0J8DlOIGTKtEmwHRK9902PyXAvgrb1XcvI8ByyawqRkkiwKoibzCbLh/AboZJXXUbIsDvpMQZKLQiwGdLwijaXSHA84GKIFQJIcBbuFz4IEgiwKDMgIibbyLAgUuaoiNhIcD0nzYeqvMgwBeRjTatBR7AxSydrebfG8DAkfYinBIdwLu1bXud+xnAbJRXaf9IHMDHAxiArFUWwNWN93Lu+BfAS3cxh0XzGsBTwZBkq/QbwFJOx042AQ7AAjYJ8QHQEcB5cEeBqhEKwJtE8jm8sfe/ZD6CQxGp6L+WmdsASyvxv09CjobLSPC/VrHLSaBf1L+GdrWetEj3v4pVjQ9DhxDAL38IYoLwD8COYL0uE4wUwCJhUJDdUhDANF3lXRicFcAd5VZ56XQTwFdz/fHOJg3Adgfr7i/A+7+UBtyVipP+v1MwgoDzU/W/QDeJUOy6rj8til5iNvz3v5N3Byvv8xDAYvKqzFAtEsB8YwPdvmMRwG59e+sHDgbAhyYNwbLzCcDxBMaLOYoBwM7LxaTdJAvAMP9U5/Ar+b+5efQC2yvqvxB6Rw2Uorw/fK/eU6X1xL8gs8g3QSh7v4PEPNq51eU/AGQScUkWu7+gSfUvyOHnv0x316NFney/TjgqrHnx1r+PaDLXGFvwv6dRPkFZiwTAXnHfOWPs6L+sXHHR51nLvwIrZrEMZfG/qOencq91/r++7en2od/4v3KeS3gmiAjASokU9xUjEMDgEZ5asloVwPvX9XswEBLAR6whme5HFcDm79OFzu8awBpR5ir9GR/AQ4fpMV1iHcAgz36HpGAewB8w2Zv0nSHAv8YMsPjrI8BZfk0WwaMgwDL6pzIABB7AcEP3xQdfIsAa/bhFbwkiwEEWcEZBEBvAHHvtwIlJIMAL6EiDZ1ogwCI0Z9B2JyHAMYokabNRIsCyz9H3Ae0iwFPE46JkiiPATCnND/0XI8DP872PLbMmwD/9SKy8aSfA96NxHtXTKMA0mpAxLosrwMWGI6pUeCzAen83JouBK8ARveqZlr0swHZE3mNeYivAGWxU3qUYJ8DOHAqk7eslwDJK8t4hPCbADsP11FZcJ8D92N8e8qsowEOXJxhixyjAs0V5jETLKMDWznA92GcpwNzc/Pe6/CXAhToT1Ia4KMC7OHRQByIpwFO+Wz6rtyrA5qReuLYBLsCOlFQypysuwAZSRwyJBC3A3BcPKITBLcAQruZwUx8qwFegfIlbsSnAHoLLW5QNLcCcn9fLf3guwP10FsDmyC7ABe0FFZiwL8C4HuWRKeAwwM6d+Lz3jTDADGArG32kL8Apfx3uYt8rwChcosh6yy7A9Oebt8wrLsAYPKZKlfgswLxfR8Fc6C/AahyXl+NkMcDsSACNmAIywCs2QjwUgjHAjOtWqnMCMsAP6JOK2HcwwIAYPSrQxDDAA4R0gbldMsAzcuw/riIywNPS1BzIMzPAP8JvJviyNMD2GZpUp5E2wBLCEXgP8jbAkbjfQ0XiNsCBQLvsBMo1wHn1IMVuODXA5KVNwxOnNsBEdyt1or42wFUfeGkMQzjAuR74DEtROsCrjNQ3mIc7wOks7pfSPTvASFIIPq1bOsDOEA79Ojw6wBRCNyvVTjvABc59rsglO8AssWW5G8E8wAm86CebpzzA9eL/D8g9PsCE/Wbzo+I8wJqazgWPtzvAk+nQX1MEO8Dh32vFEIQ6wIZOYfZcnTrAzvUG/ivROsCtVBDhxNc5wBqeXKeYzznAx/6mPoEpOcC+PaDnywo6wE5QtMG3VDrA/HgNU+zaOcDINy6W5P84wOo7AURlxTfAZMQxwocyOMANvMp6BN03wH/CD6FvfTjAgcu25cKZOMD3r/Qviqw4wLZIePWK/jfA5zM59cSwN8A7phIpl8w2wPu1ESqg+jfAJXcVh12bN8BUueImUoI3wMhjZcX9tTXAo8o6y36dNMCkR/KwdQo0wDfanAk0rjLAk1CqYRcRMsD2V4oReV4ywOoU4gP5nDPAe0lFkLWAMsCI2VtGFJQ0wCDzvgJq4DXAsDXvN0vyNcDR8Xe+VU41wPF1TMdCtTTAnliMsI2+M8CE1/i5DvYzwPV/+4MFhDPAKQNs2YAnNMD1YLGySv8zwPunkGJ3zzPA4z52jnOxMsDLVEcq5m0zwGrOAz3rRTPAPXjWqamuMcAQy/esOWcywFIQc3QrLTPARqoKD1UmM8BqpGSqHRYzwOj15dREezTAw30PDX9dM8Cl1QLO6RMzwJljzuVFoDHAxLWD/+EOMcBrCfGAdaQxwGacnc1FezLAWrT7Jf//MsC95B6UkW8ywCumoIsV2zDA0GdqDiarMMDeDmT9+/QwwGmi3VOwPDHAThmLYJ/YLsBZJs+NgqsswEuLvaVtqC7Ao7DSdF5XLsArw4sQ4pQtwMJprIR/dirATtgxpNdaKcBZBDAHHxAtwEYigdKVpifAl7aqdTXqJsDmqXAesDslwP/aI/llgSTAJFM1uSYaI8ApEQ655I8kwLtwv4xC9yPAnPRTkI32HMAelFhCFfMbwBx9DZePFhnA5o8GCV11FsBTax2cgZgXwFk42KFYJxPAD7eYukzfEsAZzHUK398QwA3OAteWvhTAPebkIY6OCcCAd5F1Zu7mv4Yxx4Q9K+K/9Ghjta8F6L+IDx6FyZW8vwQyrIo+beg/ikzm2QPp6L+M4mG2iybgv3c1rg7OhfC/gnhNp0wa9r8SyfZRKFP4v+aHbOUtBgHA5+z2mNJvAMCBbDD/mD3/v/iSiJeWTQfAFdKKaxFtCMAKc0Nnc8ADwEWIj0wEUgbA2BNtILgNBsAXJGPL3ncAwOgGBAQbtQvAcNQEvl8fCMB+OPjvavcGwHgS0GiDXgnAtz9+sNFT/b/mVoPKijP7v4yRHibdLfu/PnZySMHpAsDSusVWQQEEwHFwlkSNlRHAtcPGeiY+E8BnZPrG67kWwIhuK89xGRHAeTxPUPLnD8CQmIAIV/YPwCWFU5VG2hHAailV47aPB8D3HS2Dv+MMwAxJ+JYo+Q3AFxuqgwFbE8Du4gUUnecbwBariLJTsx/Az0RVnkpDIcDV7mG4n1MgwH8RxHjy7yPAc4XNcH/IIsBLbuPSd2UnwNQSv++kUyfARigMJTneI8DAnII6HHglwJo3jj4F6yHAm2q2kviHIMCvkW0tT28bwJa86HhmqhbAYNFu0xicD8C80HOzIScYwMaFcHAP8xTAP1bEge+6GcCgqx+EtgYdwNO62easyh3AzGPSOGghHMC5c6rTpsoawDhZjo8lTB3AmvrEyxDWGsAue1uXRs8awMidl3D+xRfA+m9N17CIFsBkjj8fH8kdwG1E1yxS7h7AKopi5G3pFcB2247DbUMVwEt07IFptxrAl/SHw7osHcBBCbFT7vcTwNtrt0niDBbAqe6HdaPdFMBXVTNz/SUYwEzdf/tARhrAL3G229wNG8Ax9u+xnqkawHJqVQ11HhbA1nFbYvqcF8DUXF1QOfoPwPqL2g0tyBTA5/TVxlNHGMDLhgYyiRwYwBfcB0mx1xfAead7w2xfFMDYk+Piaj4TwPlaFAtUORLAbeQa929bFsDSnec4w54fwHtUrFo23CLARUq1JUZ1H8CSBL5vCVUlwOfTxeku6CnAgcDV+7/MK8CcsZpfXvYswIVD8vvEYi7AdFWzjh0jMMA2HYljLT4uwHmejirMjizAYP65w6rXLsDVhgVti3wvwN9g6YZ4wzHAMsugXRU3McB1EVqC4xAywMwG6jpk9zPA75W72aBvNMDz7COogug0wL/2lM9VizTApk163yPzM8BrxYeBc+k0wDb1RHOCRjTA/AS3sglBNMAqGTIxwvM0wK1nFoASIjLAhUOYZRE3MMCwJ1t0HdowwOIlX07kGjTAtH5fBNKxM8AGxdKu0XUzwO3EyFuaZTPAraGM3cppMsCbMX6GaBAzwOthaK0ygDLAWZjmdvG/MMCpgakJL18xwHGMPhTsOzPAISxxLC5CM8CmnXulU3oywDR/uy3wejHArVS9VzuSL8CRYmJNMxwwwO8y3PYETC/ASTVfu8PdLsCu1adOmeYvwB+Etg9Vwi3A69qaX7wSKsC/nXlomC8owP7kzArkSSnAVsjjiL4GKsDgAspf6tApwAzDXj/BWC7Ak0Q07rU0LcAmKiY7Zb0swB1AZrvppS7AnAT6Dgp4LMA0BMmH9V4owNQPVouhiijAkuIUs82NKMBxESzkZMgnwCQ8zo1C0SXASaihexmgI8CHhDuGH/cjwDnazkOvliLAHDDnXXibJsBOcIraApwhwITpt6Gv2iHA6kRU0342I8C+6q1V11AgwNdw9wEBtB3AW6+ZjVFsI8AduH9PM+UjwK4WXa9EviDAWK1Sbh+DHcBzmhqWBv8ewDw+FzAlBB7AuxtlfGy7HMClOUIZcqEbwPGwp0U1yxzAnh5CLOr6G8DT9JI+DUMUwLdKL8m/sxXAjiIRZuqSE8CVTNzsRqYQwBKO1zHO7gLAXtFj0msE/r95V9LLrBoCwOxv4fxycgPA5KjZC5/mDcDdb9Vy9CIMwJR7PGfaUA/A4WLqzkZnC8DazlPHMV0OwJ+imdMwzxPAasj1hwI/E8AgvOgd0+kUwNTHLaK6HQnAUCi8l3faEcD5DD/cdoIJwLG8X9hOKQPAQW+IZsyC9b/XPaDgvgb0vwkXujdUnPe/azKMyOBrBMDj/0J/NVcJwGzB6XhIMBLAgZwzL9YgDMBXoGlJsEkQwD3eu6Kk8hDAx0b9rX/xDcA94cP7Q94SwIZJp9ja3xPAemT8YZBWD8DSgGSfRssAwGZFRFY6ZwXABBbku3dpBMATFhWi2pEEwAi+jq0QShDALzX3cIq4EsDmbCYlsSQbwC4mzcwEvhnAwdY50FZhHsCBiU/g0agbwKHxFLwigx7AjacWU/b4HcD/zm+PZlEdwJMmM/EGzB/Ahi9RMp9WJcDzfk1mNSgkwOE8DoejTiTAhZR1t0DlJMCzVXi/9mUjwMWs0jF+cyDAMsaFJBfhIMALr+7U5QUdwL6x0rwcpB7A1M7wWXRwHsBba/hpR3EawMS0SZFl9hfAzCxCgxRKFcBDW7sObakXwCSqPi75LxfAdS2iXWFIFsD5RoXayFkWwDFp8vcuvBPAIxN/UwREEcAJ9yW2NSsUwG0DK1hAnRbAxZljXO8SFsBi2Wey2QIXwMzv0qgNNRzAQBclF6jgG8BITLBMK5wawF2PszZqlBvAhdM/MpEwIMDAZ9EY+FMYwPRPDNgrVRvAxDOTl4geFcDB5F05UZsVwGK6J+n/ChTAe++LS5dQGsBADeyfdkMUwDwR1yEnARbAwKRrgC6uH8C/mA6kLzMewPIn5vCWjhfAnXihlKmxG8AeJ7nmobUWwJM3oKXMFB3AzXfE0Kb+FsBMIzkTOhoTwCA/DqbpDQ/Aty6CNn2FCsA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"B\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"C\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"D\":{\"__ndarray__\":\"fzX/F/K81L939QiezDjSP7BTl/MnEvG//9q65vjf9L/9Rtn5YtQDwA27a/P7wQfA9FA+gzIS7r+7HBe5Wrb0vxkzDHYDm/G/1z8d7NiM7r+q0GKyTw3rvyBVu0aBG9U/2G+JP3qgrT8BwtHFWBT7P7hBpGEsJP4/a4eRvwDj+z88tSaJktrQP6YJs9RC6ec/0KcpGMOiv7+EpbuLVJvnP0+ve/37eOk/AHznz4O16T950NOKRXnwPwPMUqJnlOU/TYUWqqdT8D8garkMXnfUvwZkaxV4OeS/VI+ODlXK2j8SMMMPvRzrPx6nbNBSKQVAgYob76ytC0DYvqAkDJgJQOjWl72BGwhAQqTbBF+aBEA2ze2oVYILQGxznJKCXwlA2rtsRWzLBUAMyLt/dv8BQHJ5ulXcLQZAgh8BetyUBkC5zqU7nXkGQNc9k71OKP4/7qKCKPNIDkB1/egeqAYLQIc0+eS0wQxAQYlQcHYLEUA7EFg6zPkQQJbxCU3ZkBhAqtKe8z3wF0Cxesav3pcTQBrlc2ZePxNA6sCZCnANEUDD5N6APpwMQFPAyoR8ngdA+4kT4emaCEAAsQfMXLkKQKYjdca8HBFA2LFti6C5FUBW3gNzi9EVQK6fK3nqJQ9AilsIjcAtCUCEwYx82J8TQO5TP5s85RVAbO4JES9WEUCwvJ86y3wTQK9T5zJVQBVAbMomC48fFEDOPbQXSe0SQDDo812DXAxAOBPA+t56FUBYiT9X9uwLQOSxJPFctAFAyMg9tFB2AUAUnhDN2S/9P2Bq4h91q8q/uUx3d8/2+r9Yfyq0Lezdv2IGa1/P1O8/OP7/jKI6+T+wANCYR5fxP67M15Acj/8/IyFvVVOlBkCS+o62pzAHQPo0tfyTiAlAnFGK7EX3CEDoDaOjysoXQIKWsZ+y8xRAz6YoyLfmFUAdtT7e/+UTQO2Hq2im/BZAJSMBfxaoGkDf0wZs87sbQOVV2UK59xtAPCnErWuqFkAVwFs6DjMWQCd+BpF40xdA5JilEYLDH0DquvBdlO0iQPbEUtRTuyBA/9dSps5EIEDwzUhOesUgQGrXf8O8rCNAvlflH9+pIUCuwIhnvW4gQO5/ELD5UCJAlu93EhivH0DJMegVgVYhQI7HhYsriyJAmwyfrEDJIkB8KhcJMp0kQH8RSGbOpCVATGWip3ooJUC59w6AE28lQJEl8ySrGihAV1gXLCuyJUAiBOqbTMceQK2pSbN+MR1A/fVAaOtEH0AlAuZQZPEeQJlSk+3PuRtAyJQNpf3YGkAJrMB9QE8fQLuMSgZCqiNA1iN4t/AOJEAN2/QDq0shQCWXjMJ6BSVAgZzm3kIoIkDIyTuwkEEjQPWdeagJhSNAM0AXoB8PJECOBmftydkkQCSQsfOK9SZAhP/95IFSIkAXYPjihaAiQNt8c/lSxyVAANqADtQLJEDzzBB9ayIlQBYwSoI7nCNA4EdzoqI7I0DqjxgNShYkQK/zTAqwPiNAkIxQ56l/JEDpgCEmc8UkQJ7cY9zHEyRA+ovaWgGBJEAe1lCfSIooQN4qzf6NAydACmzL+Q43J0DuK/nKcJcjQCQ3wL0XjiNA2STObv1lIkAMdTxUd+oiQH010gPQYCRACItolkmUIEDMKDO7IeMfQLbI4PfNnRtALgFjU6kjFkANSLPdYV4UQLJ33BufBRJAyBpXZ2KJDkAAGHUq+HEFQG4ey2BN9QhAnFzRz+Y9AECwzFgOf+wIQIvOCjRXPAhAOoGFOwEmDkCAOMPnDJkVQBa8We4PdBJAzjnRYHNYEkBH2heAscoZQNzwGSV6oB9AjZpc/0bkIEA9uFd4nxEeQOcD8w+1QR9AAZz7YzLbIEAjot7gahQgQAPZ8A4SfCBA4XiG9X6XI0ABNWKEvyMhQGD81wq+OBtAiPw+FdNzFEB3OqRtl2cXQEjcbZQGkhtA4EF6j3LJHkAKzopngngVQDcyr3XUzhVA/znS6IIZGkDybxFTP2QUQB8zziK6KhBAgiomq0ohBUAD6xF75P0JQK679UykwwJAqFJZy+K5/z/Z5NFqwOABQE3HJnwufQlAM7z2hXo+BEA2gGQKW9r/PyAK2pI2LANA1fD+XpbXCUAnTM0Ei6sTQIg0oD9xCwlAZGybC1hFFEBvy3YDAbgUQFMWpbkVtQ9ArPbtgeGvFUDuu9p6ms4ZQM7/Cbwc0BpA7BmEnf2+G0DV1tAB8t0cQAdfBnHiXSFAgepj2yVwIkDw2APTxSokQGNISgcJtSNAPLFjfgN+IkCQh30kGukjQEZ2Iv44wSVAhOdjqWRkJkAOqmFR0eImQLKSpb3wvSVAHxAJwJUWJUBSGkxjfSAiQHHsAg/bLyJANeJCTuHEIEBaB4MD8zEhQC9UpuE2ySFA5mr20u/gIEAKqEQ1iFQdQBIWY4lxRRtAseRNqanDHEAXDvX5cZMbQFiliDwXahtA5GR/sVMMGUAf40zJeKMZQEjL0kKQvRxAQ/ZOYWFEH0DmXV86bn4hQJ+7Y8rn8yJAO+JdPJsMIkCY4oW5AeQeQDQlF314lx1AI9YNTLPyGkCzuo5NI/sXQF6C88qTJBRAW5ujRd2YGkCkZcMzO9McQIfuTDNTsSFAgrOJnxF3IUBev0XpilojQKs9yNkYuyNAvbTe2iaBJkAhHnu7bEglQBM2t+SLliVAFSwLhnXQJUDcZ3FvfUQlQBdd8mVNqCRAULSN1ccJJUArAp1obl8jQNbxRsszHyNAMW6Mw16lIkBJbVQXNHciQDBrU4QFViRAGD+Lh5HAJkCOtXe5DsImQPAicF5TRiZAgkKgA+GrJ0B/FtgsVnwpQKbg3HII+ylA4BsPtBy5K0Afbc5rNNUtQJYvE2wY7S9AgqRFI4TALEAxnWVgw9wtQJtyAPOeYS5AJFadVxvrLkDUnn24PoEuQItiOpaF3jBAmPtgkgxaLkBv4xMJ9BwvQL2pAz1VIDBA44fVhIp9MEAGkWJ6OtYvQAix8PKTMTBAepr6GQ8KL0CGWVqjBq0uQPq6nlX/4y9AhDcWBzLKMEArJ6tRhaQxQFP3MTe4bDBAUxZjgw/nMEBk30ouU+gwQG0jKcFSmjFAVd9RKdHZMEAOWqD6m+sxQKQ9MkeqizJAu+VRclgSM0AE+huviyc0QM86+nWHvzVAzOslLqJjNUA3kD3EN640QPl9dHJL1DNAyt+oCfcBM0BYALJjZdkyQOBLR+6tyjNAwOFS+QsAM0C4s3LUqrsxQOSTJtbz+DBAirPaaHXlMUBOn5tAil0xQLNHfpNVyjNAA2IXg+8qNkBb3h9Os202QDtkqJRAfjZACMaprjN9NkC+Duy0njM3QDYru8hNVjhA8vp/FE/4NkBYdkcdi3E1QBqSumwBnjVAocXobq0JNkBzmx8PdOg1QHbLaQ3vCzZA/WdDiyMuN0Bvew8Ehks3QCgNUKCPeDdA1rdIzPPUNkBkIvmCVOs1QF4MDP6FujRAXnQKKXhpMkCzf9gvVtwyQESvDmUY0DNAUvvPEOh4NECr85qfJMU0QCGdIAscgzVAULvdD/d5N0D7zVKqbLM3QOV6Bc8s7DVAfYjIN62dNUAtUQA4spw1QM8PruAfhjdAeKk3obRANkBR7Ad/Ihk3QKLOZWFRnDdAQPFjnqXYNkCxGZ7xDc42QCB9gkWk2TZAMigrKcwDOEDwA/EatMw4QFJtsjx8fjpA9LxyMP07PkDIv7wYCPU+QOQtHpP39j5AIO/IVXk7QEBOydFzyeI/QE5I801l3T9AYRrKgMy4QECJ1y9EAydBQFDptUMaiUBA0npwYEYmQUB9yaa46m5BQHp8opfS7EFAAI2QC9EvQkAHCc1YDlNCQLbK3xLon0JA1aB3R8MBQ0CEk5oH1NNDQNkFN5eCTUNAOIxJ5JJoQ0AodlvusbNDQC/SikTaVkRA+O4U45LQQ0B9Xf95o/lDQJ/w8krFKERAvbIDhRN8Q0CKEBydGmJDQPqu98hiQkNAiQx0NjWiQkCPFJR1aP9BQLtqVXqQVkFAocq2sjIeQUBVGSsUmi1BQDj94daVAEFAVunt+Mz4QEDsNJasNDBBQKzNQu0cNEFAQ/o2zKSEQECHQusMJAZBQM8LLgGnhkFAHaE3/uVaQkBXyMFn3MNCQNrzAlg+0kJAEqaNmgbfQkDCgWpdUmJDQLDcRrfOb0NASCkkfWq8QkAHwKP0qVBDQI5Pp5Df0kJARxFeS5KJQ0AbEU72TPxDQI3lQuD6S0RAlvHLR2/oQ0CNOqFnWnZEQDHxhBtrqkRAocBM8NUqREB8M6LTrf5DQCTAMnFkLkRAmv5goyFyREDF27385itFQMU6Y/ccbkVAiviteE/dREB/6+YrV0NEQCLK/fSfsURAyRd5v9YlRUCJUt2/+fBEQJtb9kCEW0VAQiY8DeLYRUAIqCWTeLxFQEaAPbqyTkVAJVIxMTmhREChcZdXj1tEQL6SaaDkR0RAO/2AfrOnQ0CcMlqjrDZDQJjkbiuhIENAy0EE5FB3QkB7/Z8jutpBQKZs9d8UJkFACvBJRf/NQEA8XSjJZ+5AQBPt/hmWMUFArqGeVe8IQUDI4w24fo9AQNw8Ajg6+T9Auk1eflLgP0B71zs4/qBAQLDPp+UBQUFAr1wZXjVuQUBo+VDudMlBQPo/cEyOBkJAmxwukevdQUCMrrXCT8NBQOod0wUPOEJAB2bdSvrFQUA+cmTanFVBQMT8phgLD0FAN9z5kBVPQUBX9PZ2RXdBQGlan/iMgkFArtzfGPdSQkBA96+UhYZBQI5WtNOFhkFA17OWyf0XQUDzTQus+YNAQHrEBK5igEBAg2q+t2bGQEDdeoOHMglBQClPlbWOQUFAefdwdMD3QEA5/ryzbpJBQIghPKZdVEBAsN9AadnIP0C2VdrOZzU/QNLoczddH0BAxPGgjNU2QEDyWBtdtmA/QJOL9OTo/D9A3YNYHFEdQEAcqWimtgFAQE2/3enjhj9AjRqK37jBQECJNTy1ViJBQGLHM4zBB0JAE6ciYFUDQkAYTZXWEnZCQIFFzVs/GUJAqCcxWR/ZQUAZLlTaApJBQHxq9ZL390FAVsoav4I9QUCzDWOL3NZAQCGgjlbx1EBAzFaQ4iIgQUBxpuOyrClBQBfQGa5JOUFArAPungoKQUB/V8l1g25BQK6AwrP/YkFAOPHTeiXSQUAnqP9SSOVAQHZ6ZYhoC0FALxpVhdiBQUBPH+CNwWJBQGQz4K5NvEFAMPOyb2c8QkCCErWGCjNCQM1Dx5D7qkJAd8eClU/FQkAXxNk2v5hCQELpMgp2L0NA6sqOu6jMQkCGsT1mHyZCQHFuQ/aD3UJAQRlYvFN3QkAgV70rn1BCQHQLbGeggkFAvDll3MjpQUCuRMVTWRBDQK8cA9cFG0NAVzRmPsYtQ0DRE0BsEMxDQHfzDORbpENAv1l8naydQ0CuP4NgkXRDQKeVVXZfOENAv9e72ZCvQ0CBLuddjKVEQDXFhIkX9URAtQLM6V07RUCRNUOqz4xFQG1VAFl+fEVAewmoOlbZREDrz5vBnGZFQCRMUmUoH0VAfGQET4BzRUAb8EOssUFGQP5+rlH7wEZANS1kbiACR0D50mlmawZHQNhrW5F12UdAGlRrOp7mR0CoaPuxAzJHQD9sOTVquEdAdi4ZmPJaR0Dd6btDqutHQCTEBJMVsUdAcmTtun/hSEBydOAV1MVIQJ8wlmsCJEhAdt0FcP19SEBtXJt/3gdIQH9gxl/IM0hAyO4z6URdSEDIY/+1Th5JQHqGUA32u0lA+ugNnW/jSUABDcK//Z1JQG13P1fvwUlAjVcnfdxxSkBWSuXZbJFJQF5gqhL7U0lACitEGcnLSUC8AI/+oEhKQG66rzXstkpAMtwid2ovSkD93NPC6q9JQDkiO5WEqUhA0o4Rc6e7SEAhGKXOwq5IQBiyE1v3+UdAEILYUHC+R0AJSxHh6YNHQB6HpJecfEhATd17U4PqSEAZbfHmPDBJQDTS+rHt+ElASPLNc2fOSkBxqvDugoNLQKOSowxsektA1ruHdDNxS0Ct4OEMdIxLQPhAbQIbnktAgowFQ0OhTEBVSbo6SMdMQKV/A4PsZ0xAjagu5sioS0AHDx6pvlZLQDSIzhJ1xUpAY7y1qndZS0B3wxmxK+xKQCA+wbp9OExAI0xeJA05TUAj0gi4P/pMQI9GYgBrnU1A/yJ23BjyTUDYy5CYebNNQHklV/sQs01AKR0OixE4TUDn031ixZtNQIXnDtdViU5AZDgbNYHrTkDx/XjuZGhOQHAdmyh+wU5A3sPrXkqhTUCSvC1lADVNQFpRiBFk10xAPvuG2U03TEC+q4cQdWJMQCpbNa+G4ktAVpkCU0HWSkAOEvBLtPRKQKtf1YoCL0pAp70uzRKhSkDS7XaG0fpKQDgu66cIn0tAZ2cn5CUaS0ChAHEU8oRLQCrErueaVUxArYWKsTS1S0AqiPMNjZ9KQNfIfqLG8kpAWhn3GIE2TECND17QiyFMQB0iWYQS6EtASFgQXr3oS0AVjBaeh4JLQFo2UjLnJEtAcR7v+FoxSkDU1JX3bXtKQDE9FB7Dl0pAFeX6FtJsSkDRikunVlVKQJmWXRoMQUpAj2DqxNdeSUAVy+zY4b9IQN+4T0KJnEhAORZXKCHUSECSyrn5MnlHQMyRZ7yaXEZAmUBqVH9fRkBzlKHtP9FGQDHWCxhlJkZAY3AFSMWQRUBalO8xcodEQIummF+lZURAWuAcN6X+Q0CruU6PpXNEQMK8Av3KTERA3ltuOZKnREC96oYZHbJEQJQQRZASQERAoqCn8K0mRUCerVk5ildFQHx5+u/ly0RAWcsSJsPmREBqkVD9OSFFQKraSV7lpEVAxHuG/4JxRUBVxROAi0tFQI8Q1KUba0RAXksPIyDZQ0BGBqYU+XxEQIdXjo7cZURAPdGzSlJ3RUDWmbElT6xFQApMVKUWa0VATr8dJiG/REC1MqaObupEQLCu2JRB6URAvbac0XuXREDRFMe1EkFEQB6MKWvE40RAHGJuHKmPRED0zAF2gItEQDlAxwG76kNAWQESRJgpREC5CQMG3kxDQDVYTFqQOkNATaZBmcFoQ0BsbkuXd6VDQH5ExnPsUENAxwDU4g8qREDWWAStqWdEQJaEUQHIf0RAyn4WrfBiREDO3Ua2lwJEQHpgFdt/BkRAQLHgfOxrREDY8UQThk1EQEeoCkheQUVAfvfNKTrZRUBP6rPCLXZFQLD9GHcB8EVAfw12meGkREBqtEMoQOpEQOMNZpUxNUVAwsVM7tpfRUD+4YaUY3pFQNHXU+c8vkVA8H6TkwRmRUBfypcyCS1GQLm0JXCTPkZARzyImyt8RUDpPIX+ae1EQCJY+kPSk0RACPH/huUFRUAKOZwB2o9EQLl3nxFP8ERAXgzxNfj+RUB+8oE2Rs1FQJuOXYiTa0ZAlvN6YBX8RUDovhxC30tFQEKgwEccuURAUifgk0mrREC3CKD1qpVEQP+PjIDbYURAmy1FjgZQRECH0/8HHHFEQFkDJy8YpURA7Gem1r7zQ0DJOHojL8xDQJflA0aphENAqMVx3Nc0Q0AwU1pYw71CQOWYu6CoZEJAaCFAbv9YQkDLR7ssDE1CQFEOoeNj3UFA8PhwLpLRQUAhrw/cEP5CQDco+WZHCENASkOTv2GEQkDdgcpz69pBQBygy7lQY0JA33NysEnUQkCuMnpKRvdCQKs5G4inaURAnvP3VAl1RECM9CnrZR9EQJV1yn9Y20RA0YB0C/EcRUAVzG/dEDhFQPcP/uEo1ERADT0wqtW9REDGxp7lZVNEQE5deTV3zkNAskV2ctLUQ0CB8vOnPdVEQAfIytWd9kVARPHTfWcYRkB2zX7uamlGQBenhHjwnkZA5AA4cP8FR0BZ+yK14B9HQAtkg9Q95kZAON8ris0iR0Agdt05lkZHQBz60xV8UEdA/vOAuCSaR0BqzSkhB4pHQAD06ZLKzkdAnA4E9TsxSECuRPHF/e9IQECFOvkfUklAPrL9MDzASUDNFCXb+GlKQIYjcSkphkpA5v0bmRCaSkDh067G1JpKQAqlu9uA5UpAyNICS8HiSkAEV4pyqBxKQEacr72OVkpA4JblmzFvSUA1NSfp0k1JQOjzkhNhLklAfYu9ASagSUCBIOQFFyBKQK4rhMHtyUpA6Si7DyVUS0AaPR+Yk6lKQBGS2PkIQUpAhwjmxsdNSUBPX+DjaT1JQMlxw7gqo0lAUmSYRXdnSUDAmN34RgpJQODCg1w+f0lA4eKfmb6NSUCCFkIuBHhJQK5J4P55jkpAAURDtBdzS0AIoJqt31NLQGZBomZOSUtALIROUA9HS0A5rH27extLQKUB3WPJ90pAliNg9Bj8SkCBoP1iPLVLQLcNTLHeC0tARFrfcA1mS0CV/b5Fi4NLQGWX4m+ZkUtA4LhdgqiuS0AcHc+fm61LQPkUcqEWYkxAi7918NEZTUA4T2w6PxBMQAbvAGCOt0tASx4s6w9oS0A9GTvGv+lKQIdSTNVJYEpAJyBtiv6WSkABWwNpk5hKQNuqyyttikpAf0Np1WUpS0Cb18g+vf5LQJ8/vbczYk1AEfJnsPTgTUDjk83ri+FMQOP0rOMICE1AmBL7GHK3TEAxk1mZ1y5NQOSWkEHKck1AIitV0cR1TUBMjBalt2NNQGcTju4kak1AGA2RDwcoTkBjP3h/yDxNQH+dcINzeExAAl8BOUtXTEApygykANZLQGXxj5drbExABmmRjy7nTECTUtGaSStNQF4+66BI50xAXR55T2w+TUD+fTQ1/UpNQCRneCCJy01AU2W1PhjWTkDtHpmLR31OQM3mPRbnMk9AQj0BRv6qT0AtSLsLUf5PQJcHT5YsOU9AchmD2ywpT0BPP/7G0IZPQMvd7QjQok9AJoqQPPoSUEDOYqmAfgtQQHFXuZZcGVBAN/zKBSsgUECbgLFp+wpQQEyaoS3DSFBA3EQKKlEVUEDeZMBTgsdPQJLGevPE009AuNNqeo1PUEApZW1ChiVQQEhQJWgOiU9AxBM88oG7T0BXawLvT/lOQNNeznfy6E5AohKViQ4CTkDVoQlzUUZOQIrF4qEIhk5Ar5ijGqOsTkAqEOddgAFOQPvhyDFw4k1AiwoYlpCJTUCzitTM45ROQMHA1NCKr05AuGaU1P7FTkA+obnxk8tOQARpa7TJ1k5A5NGf9f/RTkAAoqULVRlPQEZlU/3QVE9AzrV/akIZUED2Y1zHe/VPQGydo5HYLlBAWQjWfusTUEDpp/0+dJNPQIQ/+GnLKVBAmPj1caRZUEBqkX/tR11QQNJ2nJCuVlBA+KUO6K4HUEAx7xdUgBtQQBInzitzPVBASKpZaIdmUECRzc0/8pxQQH07Abl45lBAgBM8JQFKUUCcTYKMFG1RQFRSxk0aTVFACPseDGRFUUBMvtAPytxRQE5lS4EnGVJA8y//EUMWUkC8q2SmcuhRQF/etbT5/VFAaw1hiT13UkCg+zwe0lpSQBAeEDuM3VFAglUN43WLUkAcZ96wgudSQJQDQvwx31JAIHk61IEHU0Bv+ohiCzRTQN7S0qZsWlNANWmqZqLQU0CKQkan7fxTQLOHuoATmFNAvrj8mPt/U0BLLaPNdW1TQNcTTkFZglNAwKGFFDCSU0DTCNsNeG5TQBtZXMJYX1NAlhpTCHLdU0BOUh1sAh5UQNYJJ8phglRAy3VbW9eLVECTaiADrZxUQAximiq8ElRA9z9HEkbzU0DlKZcH3QBUQCRCzm5Q8lNAObOy0NuwU0BKLlfKz2tTQOgKmFjnz1NA7u++PxTNU0AjmqshEzFUQLmu/JaBPVRAc5bC+Jh5VEDAsxVimZJUQNo84dL4cFRAkE6gEfeNVEDqWTWjop5UQL27rOAhN1VAFF2t1KtqVUBnisY3qmxVQCN2USpgT1VAAmGEABU8VUBvz+QoeVhVQOBgOcARrFVAV6p523u1VUBUvutoml9VQEGrd67ih1VAvk7WrgOZVUAcCDqFUfZVQFsV6eQP9FVA8lKdePD/VUDgi56vWO5VQKAiBr9D0lVAuSDvfCRMVUCnhJHZaWhVQD0uMNS1g1VAkiPOrpK2VUBrUYdj78NVQKRea3xzq1VAK8M9w4dCVkBMmcpSIlhWQE+Sk0LIdlZA+c/UQUpOVkDfnvmAPxVWQMwcIQOnP1ZA58kNKC1bVkCBo5bpJEpWQMLLinSQzFVADSJGOltwVUAwp2c7TmBVQF23LMmEwlVAgcD+Ma53VUDK43snJ1BVQMZqZA5PRVVANzBukXBDVUCFIL+CPWNVQB6sartEd1VA0a1LxWJuVUDkz9udHXlVQKJ6VSLtI1VAreEzEZFPVUCWXS9mVjtVQGLSDknmRlVAc8HtWEAKVUAWLqE/yU9VQHRepPlLNFVAKh9mNNanVUA6CxTHNLFVQMIynqmU2lVAUc+7AbCMVUDOANi8EStVQPEQwVHu41RA9SQ7znEAVUBIk8On6kVUQLkuR1dLCFRACe85aAEGVEB21ZxJQ0dUQDKJt/xNa1RAH8pGXhKKVECDBtW/xn1UQDsXdXX5PVRA7mo3+WSvVEA2a6NAgIpUQFiRLk0Rc1RARJ9GCJdaVECw7SetjVZUQKAh2o8+vVRAH143UbtMVUA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1000]},\"__x__values\":{\"__ndarray__\":\"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mpgcylindersdisplacementhorsepowerweightaccelerationmodel_yearoriginname
018.08307.0130.0350412.070usachevrolet chevelle malibu
115.08350.0165.0369311.570usabuick skylark 320
218.08318.0150.0343611.070usaplymouth satellite
316.08304.0150.0343312.070usaamc rebel sst
417.08302.0140.0344910.570usaford torino
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0, + "ticks": "" + } + }, + "colorscale": { + "diverging": [ + [ + 0, + "#8e0152" + ], + [ + 0.1, + "#c51b7d" + ], + [ + 0.2, + "#de77ae" + ], + [ + 0.3, + "#f1b6da" + ], + [ + 0.4, + "#fde0ef" + ], + [ + 0.5, + "#f7f7f7" + ], + [ + 0.6, + "#e6f5d0" + ], + [ + 0.7, + "#b8e186" + ], + [ + 0.8, + "#7fbc41" + ], + [ + 0.9, + "#4d9221" + ], + [ + 1, + "#276419" + ] + ], + "sequential": [ + [ + 0, + "#0d0887" + ], + [ + 0.1111111111111111, + "#46039f" + ], + [ + 0.2222222222222222, + "#7201a8" + ], + [ + 0.3333333333333333, + "#9c179e" + ], + [ + 0.4444444444444444, + "#bd3786" + ], + [ + 0.5555555555555556, + "#d8576b" + ], + [ + 0.6666666666666666, + "#ed7953" + ], + [ + 0.7777777777777778, + "#fb9f3a" + ], + [ + 0.8888888888888888, + "#fdca26" + ], + [ + 1, + "#f0f921" + ] + ], + "sequentialminus": [ + [ + 0, + "#0d0887" + ], + [ + 0.1111111111111111, + "#46039f" + ], + [ + 0.2222222222222222, + "#7201a8" + ], + [ + 0.3333333333333333, + "#9c179e" + ], + [ + 0.4444444444444444, + "#bd3786" + ], + [ + 0.5555555555555556, + "#d8576b" + ], + [ + 0.6666666666666666, + "#ed7953" + ], + [ + 0.7777777777777778, + "#fb9f3a" + ], + [ + 0.8888888888888888, + "#fdca26" + ], + [ + 1, + "#f0f921" + ] + ] + }, + "colorway": [ + "#636efa", + "#EF553B", + "#00cc96", + "#ab63fa", + "#FFA15A", + "#19d3f3", + "#FF6692", + "#B6E880", + "#FF97FF", + "#FECB52" + ], + "font": { + "color": "#2a3f5f" + }, + "geo": { + "bgcolor": "white", + "lakecolor": "white", + "landcolor": "white", + "showlakes": true, + "showland": true, + "subunitcolor": "#C8D4E3" + }, + "hoverlabel": { + "align": "left" + }, + "hovermode": "closest", + "mapbox": { + "style": "light" + }, + "paper_bgcolor": "white", + "plot_bgcolor": "white", + "polar": { + "angularaxis": { + "gridcolor": "#EBF0F8", + "linecolor": "#EBF0F8", + "ticks": "" + }, + "bgcolor": "white", + "radialaxis": { + "gridcolor": "#EBF0F8", + "linecolor": "#EBF0F8", + "ticks": "" + } + }, + "scene": { + "xaxis": { + "backgroundcolor": "white", + "gridcolor": "#DFE8F3", + "gridwidth": 2, + "linecolor": "#EBF0F8", + "showbackground": true, + "ticks": "", + "zerolinecolor": "#EBF0F8" + }, + "yaxis": { + "backgroundcolor": "white", + "gridcolor": "#DFE8F3", + "gridwidth": 2, + "linecolor": "#EBF0F8", + "showbackground": true, + "ticks": "", + "zerolinecolor": "#EBF0F8" + }, + "zaxis": { + "backgroundcolor": "white", + "gridcolor": "#DFE8F3", + "gridwidth": 2, + "linecolor": "#EBF0F8", + "showbackground": true, + "ticks": "", + "zerolinecolor": "#EBF0F8" + } + }, + "shapedefaults": { + "line": { + "color": "#2a3f5f" + } + }, + "ternary": { + "aaxis": { + "gridcolor": "#DFE8F3", + "linecolor": "#A2B1C6", + "ticks": "" + }, + "baxis": { + "gridcolor": "#DFE8F3", + "linecolor": "#A2B1C6", + "ticks": "" + }, + "bgcolor": "white", + "caxis": { + "gridcolor": "#DFE8F3", + "linecolor": "#A2B1C6", + "ticks": "" + } + }, + "title": { + "x": 0.05 + }, + "xaxis": { + "automargin": true, + "gridcolor": "#EBF0F8", + "linecolor": "#EBF0F8", + "ticks": "", + "title": { + "standoff": 15 + }, + "zerolinecolor": "#EBF0F8", + "zerolinewidth": 2 + }, + "yaxis": { + "automargin": true, + "gridcolor": "#EBF0F8", + "linecolor": "#EBF0F8", + "ticks": "", + "title": { + "standoff": 15 + }, + "zerolinecolor": "#EBF0F8", + "zerolinewidth": 2 + } + } + }, + "title": { + "text": "Cars" + }, + "xaxis": { + "anchor": "y", + "domain": [ + 0, + 0.31999999999999995 + ], + "title": { + "text": "mpg" + } + }, + "xaxis2": { + "anchor": "y2", + "domain": [ + 0.33999999999999997, + 0.6599999999999999 + ], + "matches": "x", + "title": { + "text": "mpg" + } + }, + "xaxis3": { + "anchor": "y3", + "domain": [ + 0.6799999999999999, + 0.9999999999999999 + ], + "matches": "x", + "title": { + "text": "mpg" + } + }, + "yaxis": { + "anchor": "x", + "domain": [ + 0, + 1 + ], + "title": { + "text": "acceleration" + } + }, + "yaxis2": { + "anchor": "x2", + "domain": [ + 0, + 1 + ], + "matches": "y", + "showticklabels": false + }, + "yaxis3": { + "anchor": "x3", + "domain": [ + 0, + 1 + ], + "matches": "y", + "showticklabels": false + } + } + }, + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotly_scatter = df_mpg.plot.scatter(\n", + " title=\"Cars\",\n", + " x=\"mpg\", y=\"acceleration\", \n", + " color=\"model_year\",\n", + " color_continuous_scale=\"burg_r\",\n", + " facet_col=\"origin\",\n", + " backend=\"plotly\", \n", + " template=\"plotly_white\",\n", + ")\n", + "plotly_scatter.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "-_DFIxBq6wa5" + }, + "outputs": [], + "source": [ + "my_page = es.Page(title=\"Interactive Plots\")\n", + "\n", + "bokeh_section = es.Section(title=\"Bokeh\")\n", + "bokeh_section += \"\"\"\n", + "\n", + "The [pandas-bokeh](https://github.com/PatrikHlobil/Pandas-Bokeh) library offers \n", + "convenient functions for producing interactive Bokeh plots with few lines of code.\n", + "\n", + "Bokeh figures will preserve their default aspect ratio by default - though this behaviour\n", + "can be configured through the Bokeh figure object in some cases. Composite objects, such\n", + "as the line chart with range slider, may need to be created using the Bokeh core API in\n", + "order to configure them correctly.\n", + "\n", + "\"\"\"\n", + "\n", + "bokeh_lines.sizing_mode = \"stretch_width\" # Has no effect as this is a composite object\n", + "bokeh_scatter.sizing_mode = \"stretch_width\" # This plot will be responsive to screen width\n", + "\n", + "bokeh_section += (\n", + " es.Row(es.Column(bokeh_lines, title=\"Line Plot with Range Slider\")), \n", + " es.Row(es.Column(bokeh_scatter, title=\"Scatter Plot\"))\n", + ")\n", + "\n", + "\n", + "plotly_section = es.Section(title=\"Plotly\")\n", + "plotly_section += \"\"\"\n", + "\n", + "With the [Plotly backend for Pandas](https://plotly.com/python/pandas-backend/) \n", + "we can access the Plotly Express API directly from the '.plot()' method of any DataFrame or Series.\n", + "\n", + "Plotly figures will expand to fill their container space by default. \n", + "All [esparto](https://domvwt.github.io/esparto/) figure classes can be manually adjusted \n", + "through their width and height attributes.\n", + "\n", + "\"\"\"\n", + "\n", + "plotly_section += (\n", + " es.Row(es.Column(plotly_lines, title=\"Line Plot\")),\n", + " es.Row(es.Column(plotly_scatter, title=\"Scatter Plot with Facet Columns\"))\n", + ")\n", + "\n", + "my_page += bokeh_section, plotly_section" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Please note that in-notebook page rendering can be temperamental when using certain components due to \n", + "timing issues while waiting for CDN content. If the page does not render, try rerunning the cell a few \n", + "times and it will eventually appear. You should have no issues when opening the HTML document." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + " \n", + " \n", + "\n", + "
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Interactive Plots

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The pandas-bokeh library offers \n", + "convenient functions for producing interactive Bokeh plots with few lines of code.

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With the Plotly backend for Pandas \n", + "we can access the Plotly Express API directly from the '.plot()' method of any DataFrame or Series.

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diff --git a/esparto/__init__.py b/esparto/__init__.py index b81eff7..4d58287 100644 --- a/esparto/__init__.py +++ b/esparto/__init__.py @@ -6,19 +6,28 @@ __author__ = """Dominic Thorn""" __email__ = "dominic.thorn@gmail.com" -__version__ = "0.1.0" +__version__ = "0.2.0" -_OPTIONAL_DEPENDENCIES: list = [ +_OPTIONAL_DEPENDENCIES: set = { "bs4", "IPython", "matplotlib", "pandas", -] + "bokeh", + "plotly", +} _INSTALLED_MODULES: Set[str] = { x.name for x in [_find_spec(dep) for dep in _OPTIONAL_DEPENDENCIES] if x } -from esparto._content import DataFramePd, FigureMpl, Image, Markdown +from esparto._content import ( + DataFramePd, + FigureBokeh, + FigureMpl, + FigurePlotly, + Image, + Markdown, +) from esparto._layout import Column, Page, Row, Section diff --git a/esparto/_adaptors.py b/esparto/_adaptors.py index d8ffee3..c75168f 100644 --- a/esparto/_adaptors.py +++ b/esparto/_adaptors.py @@ -2,7 +2,15 @@ from mimetypes import guess_type from esparto import _INSTALLED_MODULES -from esparto._content import Content, DataFramePd, FigureMpl, Image, Markdown +from esparto._content import ( + Content, + DataFramePd, + FigureBokeh, + FigureMpl, + FigurePlotly, + Image, + Markdown, +) @singledispatch @@ -18,14 +26,14 @@ def content_adaptor(content: Content) -> Content: """ if not issubclass(type(content), Content): - raise TypeError("Unsupported content type.") + raise TypeError(f"Unsupported content type: {type(content)}") return content @content_adaptor.register(str) def content_adaptor_core(content: str) -> Content: - """Called through dynamic dispatch.""" + """Convert markdown or image to Markdown or Image content.""" guess = guess_type(content) if guess and "image" in str(guess[0]): return Image(content) @@ -39,7 +47,7 @@ def content_adaptor_core(content: str) -> Content: @content_adaptor.register(DataFrame) def content_adaptor_df(content: DataFrame) -> DataFramePd: - """Called through dynamic dispatch.""" + """Convert Pandas DataFrame to DataFramePD content.""" return DataFramePd(content) @@ -49,5 +57,25 @@ def content_adaptor_df(content: DataFrame) -> DataFramePd: @content_adaptor.register(Figure) def content_adaptor_fig(content: Figure) -> FigureMpl: - """Called through dynamic dispatch.""" + """Convert Matplotlib Figure to FigureMpl content.""" return FigureMpl(content) + + +# Function only available if Bokeh is installed. +if "bokeh" in _INSTALLED_MODULES: + from bokeh.layouts import LayoutDOM as BokehObject # type: ignore + + @content_adaptor.register(BokehObject) + def content_adaptor_bokeh_layout(content: BokehObject) -> FigureBokeh: + """Convert Bokeh Layout to FigureBokeh content.""" + return FigureBokeh(content) + + +# Function only available if Plotly is installed. +if "plotly" in _INSTALLED_MODULES: + from plotly.graph_objs._figure import Figure as PlotlyFigure # type: ignore + + @content_adaptor.register(PlotlyFigure) + def content_adaptor_plotly(content: PlotlyFigure) -> FigurePlotly: + """Convert Plotly Figure to FigurePlotly content.""" + return FigurePlotly(content) diff --git a/esparto/_content.py b/esparto/_content.py index b6f10c2..ad259d1 100644 --- a/esparto/_content.py +++ b/esparto/_content.py @@ -3,7 +3,7 @@ import base64 from abc import ABC, abstractmethod from io import BytesIO -from typing import Any, Union +from typing import Any, Set, Union import markdown as md import PIL.Image as Img # type: ignore @@ -12,11 +12,19 @@ from esparto import _INSTALLED_MODULES from esparto._publish import nb_display -if "pandas" in _INSTALLED_MODULES: # pragma: no cover +if "pandas" in _INSTALLED_MODULES: from pandas import DataFrame # type: ignore -if "matplotlib" in _INSTALLED_MODULES: # pragma: no cover - from matplotlib.figure import Figure # type: ignore +if "matplotlib" in _INSTALLED_MODULES: + from matplotlib.figure import Figure as MplFigure # type: ignore + +if "bokeh" in _INSTALLED_MODULES: + from bokeh.embed import components # type: ignore + from bokeh.models.layouts import LayoutDOM as BokehObject # type: ignore + +if "plotly" in _INSTALLED_MODULES: + from plotly.graph_objs._figure import Figure as PlotlyFigure # type: ignore + from plotly.io import to_html as plotly_to_html # type: ignore def _image_to_base64(image: PILImage) -> str: @@ -62,6 +70,20 @@ def display(self) -> None: """Display rendered content in a Jupyter Notebook cell.""" nb_display(self) + @property + def _dependencies(self) -> Set[str]: + raise NotImplementedError + + @_dependencies.getter + def _dependencies(self) -> Set[str]: + if hasattr(self, "_deps"): + return self._deps + return set() + + @_dependencies.setter + def _dependencies(self, deps) -> None: + self._deps = deps + def __add__(self, other): from esparto._layout import Row # Deferred for evade circular import @@ -82,7 +104,10 @@ def __str__(self): def __eq__(self, other): if isinstance(other, self.__class__): - return all(x == y for x, y in zip(self.content, other.content)) + if hasattr(self.content, "__iter__") and hasattr(other.content, "__iter__"): + return all(x == y for x, y in zip(self.content, other.content)) + else: + return self.content == other.content return False @@ -119,9 +144,9 @@ def __init__(self, text): raise TypeError(r"text must be str") self.content = str(text) + self._dependencies = set() def to_html(self) -> str: - """ """ html = md.markdown(self.content) html = f"{html}\n" html = f"
\n{html}\n
" @@ -202,7 +227,6 @@ def rescale(self, scale) -> "Image": return self def to_html(self) -> str: - """ """ if isinstance(self.content, PILImage): image = self.content else: @@ -271,7 +295,6 @@ def __init__( self.col_space = col_space def to_html(self) -> str: - """ """ classes = "table table-sm table-striped table-hover table-bordered" html = self.content.to_html( index=self.index, border=0, col_space=self.col_space, classes=classes @@ -286,20 +309,199 @@ class FigureMpl(Image): figure (plt.Figure): A Matplotlib figure. caption (str): Image caption (default = None) alt_text (str): Alternative text. (default = None) - scale (float): Value by which to scale image, must be > 0 and <= 1. (default = 1) """ def __init__( self, - figure: "Figure", + figure: "MplFigure", caption: str = "", alt_text: str = "Image", ): - if not isinstance(figure, Figure): + if not isinstance(figure, MplFigure): raise TypeError(r"figure must be a Matplotlib Figure") buffer = BytesIO() figure.savefig(buffer, format="png") super().__init__(buffer, scale=1, caption=caption, alt_text=alt_text) + + +class FigureBokeh(Content): + """Bokeh object to be rendered as an interactive plot. + + Args: + figure (bokeh.layouts.LayoutDOM): A Bokeh object. + width (int): Width in pixels. (default = 'auto') + height (int): Height in pixels. (default = 'auto') + + """ + + @property + def content(self) -> "BokehObject": + """ """ + raise NotImplementedError + + @content.getter + def content(self) -> "BokehObject": + """ """ + return self._content + + @content.setter + def content(self, content) -> None: + """ """ + self._content = content + + @property + def width(self) -> Union[int, str, None]: + """ """ + raise NotImplementedError + + @width.getter + def width(self) -> str: + """ """ + if isinstance(self._width, str) and self._width == "auto": + return self._width + + return f"{self._width}px" + + @width.setter + def width(self, width) -> None: + """ """ + self._width = width + + @property + def height(self) -> Union[int, str, None]: + """ """ + raise NotImplementedError + + @height.getter + def height(self) -> str: + """ """ + if isinstance(self._height, str) and self._height == "auto": + return self._height + + return f"{self._height}px" + + @height.setter + def height(self, height) -> None: + """ """ + self._height = height + + def __init__( + self, + figure: "BokehObject", + width: int = None, + height: int = None, + ): + + self._dependencies = {"bokeh"} + self.content = figure + + if not issubclass(type(figure), BokehObject): + raise TypeError(r"figure must be a Bokeh object") + + self.width = width or "auto" + self.height = height or "auto" + + # Required as deep copy is not defined for Bokeh figures + # Also need to catch some erroneous args that get passed to the function + def __deepcopy__(self, *args, **kwargs): + cls = self.__class__ + return cls(self.content) + + def to_html(self) -> str: + html, js = components(self.content) + + # Remove outer
tag so we can give our own attributes + html = _remove_outer_div(html) + + return f"
{html}\n{js}\n
" + + +class FigurePlotly(Content): + """Plotly figure to be rendered as an interactive plot. + + Args: + figure (plotly.graph_objs._figure.Figure): A Plotly figure. + width (int): Width in pixels. (default = 'auto') + height (int): Height in pixels. (default = 500') + + """ + + @property + def content(self) -> "PlotlyFigure": + """ """ + raise NotImplementedError + + @content.getter + def content(self) -> "PlotlyFigure": + """ """ + return self._content + + @content.setter + def content(self, content) -> None: + """ """ + self._content = content + + @property + def width(self) -> Union[int, str, None]: + """ """ + raise NotImplementedError + + @width.getter + def width(self) -> str: + """ """ + if self._width == "auto": + return self._width + + return f"{self._width}px" + + @width.setter + def width(self, width) -> None: + """ """ + self._width = width + + @property + def height(self) -> Union[int, str, None]: + """ """ + raise NotImplementedError + + @height.getter + def height(self) -> str: + """ """ + if self._height == "auto": + return self._height + + return f"{self._height}px" + + @height.setter + def height(self, height) -> None: + """ """ + self._height = height + + def __init__(self, figure: "PlotlyFigure", width: int = None, height: int = None): + + if not isinstance(figure, PlotlyFigure): + raise TypeError(r"figure must be a Plotly Figure") + + self.width = width or figure.layout["width"] or "auto" + self.height = height or figure.layout["height"] or 500 + + self._dependencies = {"plotly"} + self.content = figure + + def to_html(self) -> str: + html = plotly_to_html(self.content, include_plotlyjs=False, full_html=False) + + # Remove outer
tag so we can give our own attributes. + html = _remove_outer_div(html) + + return f"
{html}\n
" + + +def _remove_outer_div(html: str) -> str: + """Remove outer
tags.""" + html = html.replace("
", "", 1) + html = "".join(html.rsplit("
", 1)) + return html diff --git a/esparto/_layout.py b/esparto/_layout.py index 272747d..1bdb133 100644 --- a/esparto/_layout.py +++ b/esparto/_layout.py @@ -4,7 +4,7 @@ from abc import ABC, abstractmethod from inspect import getmembers from pprint import pformat -from typing import TYPE_CHECKING, Any, Iterable, Optional, Type, Union +from typing import TYPE_CHECKING, Any, Iterable, Optional, Set, Type, Union from esparto._publish import nb_display, publish @@ -236,6 +236,7 @@ def __init__( ): self.children = list(children) self.title = title + self._dependencies = {"bootstrap"} def __call__(self, *children: Union["Layout", "Content", None]): new = copy.deepcopy(self) @@ -271,12 +272,12 @@ def _repr_html_(self): nb_display(self) def __repr__(self): - title = self._title if self._title else "Untitled" + title = self._title or "Untitled" return f"{type(self)}: {title}" def _recurse_children(self) -> dict: """ """ - key = self._title if self._title else type(self).__name__ + key = self._title or type(self).__name__ tree = { f"{key}": [ x._recurse_children() @@ -287,6 +288,22 @@ def _recurse_children(self) -> dict: } return tree + def _required_dependencies(self) -> Set[str]: + """ """ + deps: Set[str] = self._dependencies + + def dep_finder(item): + nonlocal deps + for child in item.children: + if hasattr(child, "_dependencies"): + deps = deps | set(child._dependencies) + if hasattr(child, "children"): + dep_finder(child) + + dep_finder(self) + + return deps + def __str__(self): return pformat(self._recurse_children()) @@ -340,10 +357,10 @@ def __init__( self, *children: Union["Layout", "Content", Any], title: Optional[str] = None, - org_name: Optional[str] = None, + org_name: Optional[str] = "esparto", ): super().__init__(*children, title=title) - self.org_name = org_name if org_name else "esparto" + self.org_name = org_name class Section(Layout): diff --git a/esparto/_publish.py b/esparto/_publish.py index 3fce76e..5649f81 100644 --- a/esparto/_publish.py +++ b/esparto/_publish.py @@ -1,4 +1,5 @@ -from typing import TYPE_CHECKING, Optional, Union +import time +from typing import TYPE_CHECKING, List, Optional, Set, Union from jinja2 import Environment, PackageLoader, select_autoescape # type: ignore @@ -19,6 +20,46 @@ + 'integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" crossorigin="anonymous">' ) +if "bokeh" in _INSTALLED_MODULES: + import bokeh # type: ignore + + bokeh_version = bokeh.__version__ + _BOKEH_CDN = f"""\ + + + + """ + +if "plotly" in _INSTALLED_MODULES: + plotly_version = "latest" + _PLOTLY_CDN = f"""\ + + """ + + +def _get_head_deps(required_deps: Set[str]) -> List[str]: + include_deps: List[str] = [] + + if "bootstrap" in required_deps: + include_deps.append(_BOOTSTRAP_CDN) + + if "plotly" in required_deps: + include_deps.append(_PLOTLY_CDN) + + return include_deps + + +def _get_tail_deps(required_deps: Set[str]) -> List[str]: + include_deps: List[str] = [] + + if "bokeh" in required_deps: + include_deps.append(_BOKEH_CDN) + + return include_deps + def publish( document: "Layout", @@ -40,9 +81,15 @@ def publish( if not filepath: filepath = "./esparto-doc.html" + required_deps = document._required_dependencies() + head_deps = _get_head_deps(required_deps) + tail_deps = _get_tail_deps(required_deps) + # Jinja requires dict for accessing properties doc_dict = document.to_dict() - html_rendered: str = _BASE_TEMPLATE.render(content=doc_dict) + html_rendered: str = _BASE_TEMPLATE.render( + content=doc_dict, head_deps=head_deps, tail_deps=tail_deps + ) html_prettified = _prettify_html(html_rendered) with open(filepath, "w") as f: @@ -68,22 +115,40 @@ def nb_display( """ if "IPython" in _INSTALLED_MODULES: - from IPython.core.display import HTML, display # type: ignore + from IPython.display import HTML, Javascript, display # type: ignore + + from esparto._layout import Layout + + required_deps: set = set() + + if isinstance(item, Layout): + required_deps = item._required_dependencies() + elif hasattr(item, "_dependencies"): + required_deps = item._dependencies + + head_deps = "\n".join(_get_head_deps(required_deps)) + tail_deps = "\n".join(_get_tail_deps(required_deps)) + content_html = f"
\n{item.to_html()}\n
" - html = f"
\n{item.to_html()}\n
\n" - bootstrap_css = _BOOTSTRAP_CDN - html = bootstrap_css + html + render_html = ( + f"\n\n{head_deps}\n" + f"\n{content_html}\n{tail_deps}\n\n\n" + ) print() - display(HTML(html), metadata=dict(isolated=True)) + display(HTML(render_html), metadata=dict(isolated=True)) + # This allows time to download plotly.js from the CDN - otherwise cell renders empty + # TODO: Make this asynchronous + if "plotly" in required_deps: + time.sleep(1) print() # Prevent output scrolling - js = "" - display(HTML(js)) + js = "$('.output_scroll').removeClass('output_scroll')" + display(Javascript(js)) if return_html: - return html + js + return render_html else: return None else: diff --git a/esparto/templates/base.html b/esparto/templates/base.html index 649540b..652d513 100644 --- a/esparto/templates/base.html +++ b/esparto/templates/base.html @@ -9,9 +9,13 @@ - - + + {% if head_deps is defined and head_deps|length %} + {% for dep in head_deps %} + {{ dep }} + {% endfor %} + {% endif %} + @@ -23,12 +27,19 @@ {% if "_rendered" in content %} - {{ content["_rendered"] }} + {{ content["_rendered"] }} {% else %} -

There's nothing here...

+

There's nothing here...

{% endif %} + + {% if tail_deps is defined and tail_deps|length %} + {% for dep in tail_deps %} + {{ dep }} + {% endfor %} + {% endif %} + diff --git a/poetry.lock b/poetry.lock index 89c6ee2..d0bd145 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,5 @@ [[package]] -category = "dev" +category = "main" description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." name = "appdirs" optional = false @@ -16,7 +16,7 @@ python-versions = "*" version = "0.1.2" [[package]] -category = "dev" +category = "main" description = "Atomic file writes." marker = "sys_platform == \"win32\"" name = "atomicwrites" @@ -25,7 +25,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "1.4.0" [[package]] -category = "dev" +category = "main" description = "Classes Without Boilerplate" name = "attrs" optional = false @@ -64,7 +64,7 @@ html5lib = ["html5lib"] lxml = ["lxml"] [[package]] -category = "dev" +category = "main" description = "The uncompromising code formatter." name = "black" optional = false @@ -89,6 +89,24 @@ version = ">=0.6" colorama = ["colorama (>=0.4.3)"] d = ["aiohttp (>=3.3.2)", "aiohttp-cors"] +[[package]] +category = "dev" +description = "Interactive plots and applications in the browser from Python" +name = "bokeh" +optional = false +python-versions = ">=3.6" +version = "2.3.1" + +[package.dependencies] +Jinja2 = ">=2.7" +PyYAML = ">=3.10" +numpy = ">=1.11.3" +packaging = ">=16.8" +pillow = ">=7.1.0" +python-dateutil = ">=2.1" +tornado = ">=5.1" +typing_extensions = ">=3.7.4" + [[package]] category = "dev" description = "Python package for providing Mozilla's CA Bundle." @@ -114,7 +132,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" version = "4.0.0" [[package]] -category = "dev" +category = "main" description = "Composable command line interface toolkit" name = "click" optional = false @@ -122,7 +140,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" version = "7.1.2" [[package]] -category = "dev" +category = "main" description = "Cross-platform colored terminal text." marker = "sys_platform == \"win32\" or platform_system == \"Windows\"" name = "colorama" @@ -131,7 +149,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" version = "0.4.4" [[package]] -category = "dev" +category = "main" description = "Code coverage measurement for Python" name = "coverage" optional = false @@ -153,7 +171,7 @@ version = "0.10.0" six = "*" [[package]] -category = "dev" +category = "main" description = "A backport of the dataclasses module for Python 3.6" marker = "python_version < \"3.7\"" name = "dataclasses" @@ -167,7 +185,7 @@ description = "Decorators for Humans" name = "decorator" optional = false python-versions = ">=3.5" -version = "5.0.6" +version = "5.0.7" [[package]] category = "dev" @@ -200,12 +218,12 @@ python-versions = "*" version = "3.0.12" [[package]] -category = "dev" +category = "main" description = "the modular source code checker: pep8 pyflakes and co" name = "flake8" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" -version = "3.9.0" +version = "3.9.1" [package.dependencies] mccabe = ">=0.6.0,<0.7.0" @@ -225,7 +243,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" version = "0.18.2" [[package]] -category = "dev" +category = "main" description = "HTML parser based on the WHATWG HTML specification" name = "html5lib" optional = false @@ -248,7 +266,7 @@ description = "File identification library for Python" name = "identify" optional = false python-versions = ">=3.6.1" -version = "2.2.2" +version = "2.2.4" [package.extras] license = ["editdistance-s"] @@ -268,7 +286,7 @@ marker = "python_version < \"3.8\"" name = "importlib-metadata" optional = false python-versions = ">=3.6" -version = "3.10.0" +version = "4.0.1" [package.dependencies] zipp = ">=0.5" @@ -300,7 +318,7 @@ docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] testing = ["pytest (>=4.6)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pytest-cov", "pytest-enabler", "pytest-black (>=0.3.7)", "pytest-mypy"] [[package]] -category = "dev" +category = "main" description = "iniconfig: brain-dead simple config-ini parsing" name = "iniconfig" optional = false @@ -482,7 +500,7 @@ pyparsing = ">=2.0.3,<2.0.4 || >2.0.4,<2.1.2 || >2.1.2,<2.1.6 || >2.1.6" python-dateutil = ">=2.1" [[package]] -category = "dev" +category = "main" description = "McCabe checker, plugin for flake8" name = "mccabe" optional = false @@ -551,7 +569,7 @@ description = "A Material Design theme for MkDocs" name = "mkdocs-material" optional = false python-versions = "*" -version = "7.1.0" +version = "7.1.2" [package.dependencies] Pygments = ">=2.4" @@ -589,7 +607,7 @@ pymdown-extensions = ">=6.3,<9.0" pytkdocs = ">=0.2.0,<0.12.0" [[package]] -category = "dev" +category = "main" description = "Optional static typing for Python" name = "mypy" optional = false @@ -605,7 +623,7 @@ typing-extensions = ">=3.7.4" dmypy = ["psutil (>=4.0)"] [[package]] -category = "dev" +category = "main" description = "Experimental type system extensions for programs checked with the mypy typechecker." name = "mypy-extensions" optional = false @@ -619,7 +637,7 @@ marker = "python_version > \"2.7\"" name = "nltk" optional = false python-versions = ">=3.5.*" -version = "3.6.1" +version = "3.6.2" [package.dependencies] click = "*" @@ -628,7 +646,7 @@ regex = "*" tqdm = "*" [package.extras] -all = ["requests", "pyparsing", "numpy", "twython", "gensim (<4.0.0)", "scikit-learn", "scipy", "python-crfsuite", "matplotlib"] +all = ["matplotlib", "twython", "scipy", "numpy", "gensim (<4.0.0)", "python-crfsuite", "pyparsing", "scikit-learn", "requests"] corenlp = ["requests"] machine_learning = ["gensim (<4.0.0)", "numpy", "python-crfsuite", "scikit-learn", "scipy"] plot = ["matplotlib"] @@ -652,7 +670,7 @@ python-versions = ">=3.6" version = "1.19.5" [[package]] -category = "dev" +category = "main" description = "Core utilities for Python packages" name = "packaging" optional = false @@ -678,6 +696,18 @@ pytz = ">=2017.2" [package.extras] test = ["pytest (>=4.0.2)", "pytest-xdist", "hypothesis (>=3.58)"] +[[package]] +category = "dev" +description = "Bokeh plotting backend for Pandas, GeoPandas & Pyspark" +name = "pandas-bokeh" +optional = false +python-versions = ">=3.6" +version = "0.5.5" + +[package.dependencies] +bokeh = ">=2.0" +pandas = ">=0.22.0" + [[package]] category = "dev" description = "A Python Parser" @@ -690,7 +720,7 @@ version = "0.7.1" testing = ["docopt", "pytest (>=3.0.7)"] [[package]] -category = "dev" +category = "main" description = "Utility library for gitignore style pattern matching of file paths." name = "pathspec" optional = false @@ -727,6 +757,18 @@ version = "8.2.0" [[package]] category = "dev" +description = "An open-source, interactive data visualization library for Python" +name = "plotly" +optional = false +python-versions = "*" +version = "4.14.3" + +[package.dependencies] +retrying = ">=1.3.3" +six = "*" + +[[package]] +category = "main" description = "plugin and hook calling mechanisms for python" name = "pluggy" optional = false @@ -747,7 +789,7 @@ description = "A framework for managing and maintaining multi-language pre-commi name = "pre-commit" optional = false python-versions = ">=3.6.1" -version = "2.12.0" +version = "2.12.1" [package.dependencies] cfgv = ">=2.0.0" @@ -786,7 +828,7 @@ python-versions = "*" version = "0.7.0" [[package]] -category = "dev" +category = "main" description = "library with cross-python path, ini-parsing, io, code, log facilities" name = "py" optional = false @@ -794,7 +836,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "1.10.0" [[package]] -category = "dev" +category = "main" description = "Python style guide checker" name = "pycodestyle" optional = false @@ -802,7 +844,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" version = "2.7.0" [[package]] -category = "dev" +category = "main" description = "passive checker of Python programs" name = "pyflakes" optional = false @@ -866,7 +908,7 @@ python-versions = "*" version = "0.3.3" [[package]] -category = "dev" +category = "main" description = "Python parsing module" name = "pyparsing" optional = false @@ -874,7 +916,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" version = "2.4.7" [[package]] -category = "dev" +category = "main" description = "pytest: simple powerful testing with Python" name = "pytest" optional = false @@ -937,7 +979,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" version = "5.4.1" [[package]] -category = "dev" +category = "main" description = "Alternative regular expression module, to replace re." name = "regex" optional = false @@ -962,6 +1004,17 @@ urllib3 = ">=1.21.1,<1.27" security = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)"] socks = ["PySocks (>=1.5.6,<1.5.7 || >1.5.7)", "win-inet-pton"] +[[package]] +category = "dev" +description = "Retrying" +name = "retrying" +optional = false +python-versions = "*" +version = "1.3.3" + +[package.dependencies] +six = ">=1.7.0" + [[package]] category = "dev" description = "a python refactoring library..." @@ -974,7 +1027,7 @@ version = "0.18.0" dev = ["pytest"] [[package]] -category = "dev" +category = "main" description = "Python 2 and 3 compatibility utilities" name = "six" optional = false @@ -991,7 +1044,7 @@ python-versions = ">=3.6" version = "2.2.1" [[package]] -category = "dev" +category = "main" description = "Python Library for Tom's Obvious, Minimal Language" name = "toml" optional = false @@ -1063,12 +1116,12 @@ six = "*" test = ["pytest", "mock"] [[package]] -category = "dev" +category = "main" description = "a fork of Python 2 and 3 ast modules with type comment support" name = "typed-ast" optional = false python-versions = "*" -version = "1.4.2" +version = "1.4.3" [[package]] category = "main" @@ -1097,7 +1150,7 @@ description = "Virtual Python Environment builder" name = "virtualenv" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" -version = "20.4.3" +version = "20.4.4" [package.dependencies] appdirs = ">=1.4.3,<2" @@ -1126,7 +1179,7 @@ python-versions = "*" version = "0.2.5" [[package]] -category = "dev" +category = "main" description = "Character encoding aliases for legacy web content" name = "webencodings" optional = false @@ -1156,9 +1209,10 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pyt [extras] extras = ["beautifulsoup4"] +test = ["black", "flake8", "mypy", "pytest", "coverage", "html5lib"] [metadata] -content-hash = "1a30e7ecabd7c107aa68e2ff5a64802afcfe6ec7c2e9e0f89c055660c2b23d22" +content-hash = "b35f26f12e97d89f71848c3e0a0f7c743bb4704470e5ffe40f5c4f03a814b358" lock-version = "1.0" python-versions = "^3.6.1" @@ -1191,6 +1245,9 @@ beautifulsoup4 = [ black = [ {file = "black-20.8b1.tar.gz", hash = "sha256:1c02557aa099101b9d21496f8a914e9ed2222ef70336404eeeac8edba836fbea"}, ] +bokeh = [ + {file = "bokeh-2.3.1.tar.gz", hash = "sha256:2f2fb8bab8ca8fa039f48b1f0bed56d3a847c75694ece1d206ffab645ff5beec"}, +] certifi = [ {file = "certifi-2020.12.5-py2.py3-none-any.whl", hash = "sha256:719a74fb9e33b9bd44cc7f3a8d94bc35e4049deebe19ba7d8e108280cfd59830"}, {file = "certifi-2020.12.5.tar.gz", hash = "sha256:1a4995114262bffbc2413b159f2a1a480c969de6e6eb13ee966d470af86af59c"}, @@ -1274,8 +1331,8 @@ dataclasses = [ {file = "dataclasses-0.6.tar.gz", hash = "sha256:6988bd2b895eef432d562370bb707d540f32f7360ab13da45340101bc2307d84"}, ] decorator = [ - {file = "decorator-5.0.6-py3-none-any.whl", hash = "sha256:d9f2d2863183a3c0df05f4b786f2e6b8752c093b3547a558f287bf3022fd2bf4"}, - {file = "decorator-5.0.6.tar.gz", hash = "sha256:f2e71efb39412bfd23d878e896a51b07744f2e2250b2e87d158e76828c5ae202"}, + {file = "decorator-5.0.7-py3-none-any.whl", hash = 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{version = "^5.5", optional = true} +html5lib = {version = "^1.1", optional = true} + [tool.poetry.dev-dependencies] black = "^20.8b1" @@ -36,9 +43,13 @@ tox = "^3.23.0" mypy = "^0.812" isort = "^5.8.0" flake8 = "^3.9.0" +bokeh = "^2.3.1" +plotly = "^4.14.3" +pandas-bokeh = "^0.5.5" [tool.poetry.extras] extras = ["beautifulsoup4"] +test = ["black", "flake8", "mypy", "pytest", "coverage", "html5lib"] [build-system] requires = ["poetry>=0.12"] diff --git a/tests/check_package_version.py b/tests/check_package_version.py new file mode 100644 index 0000000..7f8caa5 --- /dev/null +++ b/tests/check_package_version.py @@ -0,0 +1,19 @@ +import sys + +import esparto + + +def check_package_version(): + if sys.version >= "3.8.0": + from importlib.metadata import version + + if esparto.__version__ == version("esparto"): + print("Version number up to date!") + else: + print("Please bump version number!") + else: + assert True + + +if __name__ == "__main__": + check_package_version() diff --git a/tests/conftest.py b/tests/conftest.py index c7ff01e..83ac62f 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -2,19 +2,13 @@ from io import BytesIO from pathlib import Path -import pandas as pd # type: ignore import pytest import esparto._content as co import esparto._layout as la +from esparto import _INSTALLED_MODULES, _OPTIONAL_DEPENDENCIES - -if sys.version.startswith("3.6."): - import matplotlib as mpl # type: ignore - - mpl.use("Agg") - -import matplotlib.pyplot as plt # type: ignore +_EXTRAS = _OPTIONAL_DEPENDENCIES <= _INSTALLED_MODULES pytestmark = pytest.mark.filterwarnings("ignore:Row titles are not rendered") @@ -23,12 +17,11 @@ with Path(_irises_path).open("rb") as f: _irises_binary = BytesIO(f.read()) + # Add new content classes here content_list = [ (co.Markdown("this _is_ some **markdown**")), (co.Image(_irises_path)), - (co.DataFramePd(pd.DataFrame({"a": range(1, 11), "b": range(11, 21)}))), - (co.FigureMpl(plt.figure())), ] # Add new layout classes here @@ -43,10 +36,40 @@ adaptor_list = [ ("this is markdown", co.Markdown), (_irises_path, co.Image), - (pd.DataFrame({"a": range(1, 11), "b": range(11, 21)}), co.DataFramePd), - (plt.figure(), co.FigureMpl), ] +if _EXTRAS: + import bokeh.layouts as bkl # type: ignore + import bokeh.plotting as bkp # type: ignore + import matplotlib.pyplot as plt # type: ignore + import pandas as pd # type: ignore + import plotly.express as px # type: ignore + + if sys.version.startswith("3.6."): + import matplotlib as mpl # type: ignore + + mpl.use("Agg") + + content_extra = [ + (co.DataFramePd(pd.DataFrame({"a": range(1, 11), "b": range(11, 21)}))), + (co.FigureMpl(plt.Figure())), + (co.FigureBokeh(bkp.figure())), + (co.FigureBokeh(bkl.column(bkp.figure()))), + (co.FigurePlotly(px.line(x=range(10), y=range(10)))), # type: ignore + ] + + content_list += content_extra + + adaptors_extra = [ + (pd.DataFrame({"a": range(1, 11), "b": range(11, 21)}), co.DataFramePd), + (plt.figure(), co.FigureMpl), + (bkp.Figure(), co.FigureBokeh), + (bkl.column(bkp.figure()), co.FigureBokeh), + (px.line(x=range(10), y=range(10)), co.FigurePlotly), + ] + + adaptor_list += adaptors_extra + @pytest.fixture def content_list_fn(): @@ -58,6 +81,11 @@ def layout_list_fn(): return layout_list +@pytest.fixture +def adaptor_list_fn(): + return adaptor_list + + @pytest.fixture def page_layout(content_list_fn) -> la.Page: return la.Page( diff --git a/tests/test_adaptors.py b/tests/test_adaptors.py index 292f5f9..0492ed9 100644 --- a/tests/test_adaptors.py +++ b/tests/test_adaptors.py @@ -1,7 +1,27 @@ +from inspect import getmembers, isfunction, signature + import pytest import esparto._adaptors as ad -from tests.conftest import adaptor_list +from esparto._content import Content +from tests.conftest import _EXTRAS, adaptor_list + + +def get_dispatch_type(fn): + sig = signature(fn) + if "content" in sig.parameters: + return sig.parameters["content"].annotation + + +def test_all_adaptors_covered(adaptor_list_fn): + test_classes = {type(item[0]) for item in adaptor_list_fn} + module_functions = [x[1] for x in getmembers(ad, isfunction)] + adaptor_types = {get_dispatch_type(fn) for fn in module_functions} + adaptor_types.remove(Content) # Can't use abstract base class in a test + if _EXTRAS: + adaptor_types.remove(ad.BokehObject) # Can't use abstract base class in a test + adaptor_types.remove(None) + assert adaptor_types <= test_classes @pytest.mark.parametrize("input_,expected", adaptor_list) diff --git a/tests/test_content.py b/tests/test_content.py index cd6b9d4..b5113b5 100644 --- a/tests/test_content.py +++ b/tests/test_content.py @@ -4,15 +4,16 @@ import esparto._content as co import esparto._layout as la -from tests.conftest import content_list +from tests.conftest import _EXTRAS, content_list +if _EXTRAS: -def test_all_content_classes_covered(content_list_fn): - test_classes = [type(c) for c in content_list_fn] - module_classes = [c for c in co.Content.__subclasses__()] - module_subclasses = [d.__subclasses__() for d in module_classes] - module_all = list(chain.from_iterable(module_subclasses)) + module_classes - assert all([c in test_classes for c in module_all]) + def test_all_content_classes_covered(content_list_fn): + test_classes = {type(c) for c in content_list_fn} + module_classes = {c for c in co.Content.__subclasses__()} + module_subclasses = [d.__subclasses__() for d in module_classes] + module_all = set(chain.from_iterable(module_subclasses)) | module_classes + assert module_all <= test_classes @pytest.mark.parametrize("a", content_list) @@ -54,8 +55,8 @@ def test_incorrect_content_rejected(a): b = type(a) class FakeClass: - def __call__(self): - return "I'm not supported" + def __init__(self): + self.supported = False fake = FakeClass() diff --git a/tests/test_publish.py b/tests/test_publish.py index 030dbdf..b4bfaf7 100644 --- a/tests/test_publish.py +++ b/tests/test_publish.py @@ -1,11 +1,10 @@ -import pytest from typing import Optional +import pytest from html5lib import HTMLParser # type: ignore -from tests.conftest import content_list, layout_list - import esparto._publish as pu +from tests.conftest import _EXTRAS, content_list, layout_list htmlparser = HTMLParser(strict=True) @@ -43,6 +42,8 @@ def test_saved_html_valid(page_layout, tmp_path): assert html_is_valid(html) -def test_notebook_html_valid(page_layout): - html = pu.nb_display(page_layout, return_html=True) - assert html_is_valid(html, fragment=True) +if _EXTRAS: + + def test_notebook_html_valid(page_layout): + html = pu.nb_display(page_layout, return_html=True) + assert html_is_valid(html) diff --git a/tox.ini b/tox.ini index 10af33e..0fbabfa 100644 --- a/tox.ini +++ b/tox.ini @@ -1,6 +1,20 @@ [tox] skipsdist = true -envlist = py38, codequal +envlist = setup,codequal,py{36,37,38,39}-{alldeps,mindeps},coverage + +[testenv] +allowlist_externals = + poetry +commands = + alldeps: poetry install -v --no-root -E test + mindeps: poetry install -v --no-root --no-dev -E test + poetry run coverage run -am pytest + +[testenv:setup] +deps = + coverage +commands = + coverage erase [testenv:codequal] basepython = python @@ -14,9 +28,8 @@ commands = flake8 esparto tests mypy esparto tests -[testenv] -whitelist_externals = poetry +[testenv:coverage] +deps = + coverage commands = - poetry install -v - poetry run coverage run -m pytest - poetry run coverage report + coverage html