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* linguist-vendored
*.py linguist-vendored=false
text eol=lf
+openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/Terminal_icon.png filter=lfs diff=lfs merge=lfs -text
diff --git a/openbb_platform/obbject_extensions/charting/README.md b/openbb_platform/obbject_extensions/charting/README.md
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+# OpenBB Charting extension
+
+This extension provides a charting library for OpenBB Platform.
+
+The library includes:
+
+- a charting infrastructure based on Plotly
+- a set of charting components
+- prebuilt charts for a set of commands that are built-in OpenBB extensions
+
+>[!NOTE]
+> The charting library is an `OBBject` extension which means you'll have the functionality it exposes on every command result.
+
+## Installation
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install openbb-charting
+```
+
+## PyWry dependency on Linux
+
+The PyWry dependency handles the display of interactive charts and tables in a separate window. It is installed automatically with the OpenBB Charting extension.
+
+When using Linux distributions, the PyWry dependency requires certain dependencies to be installed first.
+
+- Debian-based / Ubuntu / Mint:
+`sudo apt install libwebkit2gtk-4.0-dev`
+
+- Arch Linux / Manjaro:
+`sudo pacman -S webkit2gtk`
+
+- Fedora:
+`sudo dnf install gtk3-devel webkit2gtk3-devel`
+
+## Usage
+
+To use the extension, run any of the OpenBB Platform endpoints with the `chart` argument set to `True`.
+
+Here's an example of how it would look like in a python interface:
+
+```python
+from openbb import obb
+equity_data = obb.equity.price.historical(symbol="TSLA", chart=True)
+```
+
+This results in a `OBBject` object containing a `chart` attribute, which contains Plotly JSON data.
+
+In order to display the chart, you need to call the `show()` method:
+
+```python
+equity_data.show()
+```
+
+> Note: The `show()` method currently works either in a Jupyter Notebook or in a standalone python script with a PyWry based backend properly initialized.
+
+Alternatively, you can use the fact that the `openbb-charting` is an `OBBject` extension and use its available methods.
+
+```python
+from openbb import obb
+res = obb.equity.price.historical("AAPL")
+res.charting.show()
+```
+
+The above code will produce the same effect as the previous example.
+
+### Discovering available charts
+
+Not all the endpoints are currently supported by the charting extension. To discover which endpoints are supported, you can run the following command:
+
+```python
+from openbb_charting import Charting
+Charting.functions()
+```
+
+### Using the `to_chart` method
+
+The `to_chart` function should be taken as an advanced feature, as it requires the user to have a good understanding of the charting extension and the `OpenBBFigure` class.
+
+The user can use any number of `**kwargs` that will be passed to the `PlotlyTA` class in order to build custom visualizations with custom indicators and similar.
+
+> Note that, this method will only work to some limited extent with data that is not standardized.
+> Also, it is currently designed only to handle time series (OHLCV) data.
+
+Example usage:
+
+- Plotting a time series with TA indicators
+
+ ```python
+
+ from openbb import obb
+ res = obb.equity.price.historical("AAPL")
+
+ indicators = dict(
+ sma=dict(length=[20,30,50]),
+ adx=dict(length=14),
+ rsi=dict(length=14),
+ macd=dict(fast=12, slow=26, signal=9),
+ bbands=dict(length=20, std=2),
+ stoch=dict(length=14),
+ ema=dict(length=[20,30,50]),
+ )
+ res.charting.to_chart(**{"indicators": indicators})
+
+ ```
+
+- Get all the available indicators
+
+ ```python
+
+ # if you have a command result already
+ res.charting.indicators
+
+ # or if you want to know in standalone fashion
+ from openbb_charting import Charting
+ Charting.indicators()
+
+ ```
+
+## Add a visualization to an existing Platform command
+
+To add a visualization to an existing command, you'll need to add a `poetry` plugin to your `pyproject.toml` file. The syntax should be the following:
+
+```toml
+[tool.poetry.plugins."openbb_charting_extension"]
+my_extension = "openbb_my_extension.my_extension_views:MyExtensionViews"
+```
+
+Where the `openbb_charting_extension` is **mandatory**, otherwise the charting extension won't be able to find the visualization.
+
+And the suggested structure for the `my_extension_views` module is the following:
+
+```python
+"""Views for MyExtension."""
+
+from typing import Any, Dict, Tuple
+
+from openbb_charting.charts.price_historical import price_historical
+from openbb_charting.core.openbb_figure import OpenBBFigure
+
+
+class MyExtensionViews:
+ """MyExtension Views."""
+
+ @staticmethod
+ def my_extension_price_historical(
+ **kwargs,
+ ) -> Tuple[OpenBBFigure, Dict[str, Any]]:
+ """MyExtension Price Historical Chart."""
+ return price_historical(**kwargs)
+```
+
+> Note that `my_extension_views` lives under the `openbb_my_extension` package.
+
+Afterwards, you'll need to add the visualization to your new `MyExtensionViews` class. The convention to match the endpoint with the respective charting function is the following:
+
+- `/equity/price/historical` -> `equity_price_historical`
+- `/technical/ema` -> `technical_ema`
+- `/my_extension/price_historical` -> `my_extension_price_historical`
+
+When you spot the charting function on the charting router file, you can add the visualization to it.
+
+The implementation should leverage the already existing classes and methods to do so, namely:
+
+- `OpenBBFigure`
+- `PlotlyTA`
+
+Note that the return of each charting function should respect the already defined return types: `Tuple[OpenBBFigure, Dict[str, Any]]`.
+
+The returned tuple contains a `OpenBBFigure` that is an interactive plotly figure which can be used in a Python interpreter, and a `Dict[str, Any]` that contains the raw data leveraged by the API.
+
+After you're done implementing the charting function, you can use either the Python interface or the API to get the chart. To do so, you'll only need to set the already available `chart` argument to `True`.
+Or accessing the `charting` attribute of the `OBBject` object: `my_obbject.charting.show()`.
diff --git a/openbb_platform/obbject_extensions/charting/examples.md b/openbb_platform/obbject_extensions/charting/examples.md
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index 0000000000000000000000000000000000000000..e2cb239b9780f02505b337104de32d873c138928
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+---
+title: Examples
+sidebar_position: 1
+description: This page provides examples of creating charts with the `openbb-charting` extension.
+keywords:
+- tutorial
+- OpenBB Platform
+- Python client
+- Fast API
+- getting started
+- extensions
+- charting
+- view
+- Plotly
+- toolkits
+- how-to
+- generic
+- figure
+---
+
+import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
+
+
+
+## Overview
+
+This page will walk through creating different charts using the `openbb-charting` extension.
+The perspective for this content is from the Python Interface,
+and the examples will assume that the OpenBB Platform is installed with all optional packages.
+
+```python
+from datetime import datetime, timedelta
+from openbb import obb
+```
+
+## Cumulative Returns
+
+The historical (equity) prices can be requested for multiple symbols.
+The extension will attempt to handle variations accordingly.
+By default, more than three symbols will draw the chart as cumulative returns from the beginning of the series.
+
+### Default View
+
+The tickers below are a collection of State Street Global Advisors SPDR funds, representing S&P 500 components.
+The data is looking back five years.
+
+```python
+SPDRS = [
+ "SPY",
+ "XLE",
+ "XLB",
+ "XLI",
+ "XHB",
+ "XLP",
+ "XLY",
+ "XRT",
+ "XLF",
+ "XLV",
+ "XLK",
+ "XLC",
+ "XLU",
+ "XLRE",
+]
+start_date = (datetime.now() - timedelta(weeks=52*5)).date()
+spdrs = obb.equity.price.historical(SPDRS, start_date=start_date, provider="yfinance", chart=True)
+
+spdrs.show()
+```
+
+
+
+### Redraw as YTD
+
+The `charting` attribute of the command output has methods for creating the chart again.
+The `data` parameter allows modifications to the data before creating the figure.
+In this example, the length of the data is trimmed to the beginning of the year.
+
+```python
+new_data = spdrs.to_df().loc[datetime(2024,12,29).date():]
+spdrs.charting.to_chart(data=new_data, title="YTD")
+```
+
+:::note
+This replaces the chart that was already created.
+:::
+
+
+
+## Price Performance Bar Chart
+
+The `obb.equity.price.performance` endpoint will create a bar chart over intervals.
+
+```python
+price_performance = obb.equity.price.performance(SPDRS, chart=True)
+price_performance.show()
+```
+
+
+
+### Create Bar Chart
+
+This example uses the `create_bar_chart()` method, which does not replace the existing chart, in `price_performance.chart`.
+It isolates the one-month performance and orients the layout as horizontal.
+
+```python
+new_data = price_performance.to_df().set_index("symbol").multiply(100).reset_index()
+price_performance.charting.create_bar_chart(
+ data=new_data,
+ x="symbol",
+ y="one_month",
+ orientation="h",
+ title="One Month Price Performance",
+ xtitle="Percent (%)"
+)
+```
+
+
+
+## Create Your Own
+
+This example analyzes the share volume turnover of the S&P 500 Energy Sector constituents, year-to-date.
+
+```python
+symbols = [
+ 'XOM',
+ 'CVX',
+ 'COP',
+ 'WMB',
+ 'EOG',
+ 'KMI',
+ 'OKE',
+ 'MPC',
+ 'PSX',
+ 'SLB',
+ 'VLO',
+ 'BKR',
+ 'HES',
+ 'TRGP',
+ 'EQT',
+ 'OXY',
+ 'TPL',
+ 'FANG',
+ 'EXE',
+ 'DVN',
+ 'HAL',
+ 'CTRA',
+ 'APA',
+]
+data = obb.equity.price.historical(symbols, start_date="2025-01-01", provider="yfinance")
+create_bar_chart = data.charting.create_bar_chart
+volume = data.to_df().groupby("symbol").sum()["volume"]
+shares = obb.equity.profile(
+ symbols, provider="yfinance"
+).to_df().set_index("symbol")["shares_float"]
+df = volume.to_frame().join(shares)
+df["Turnover"] = (df.volume/df.shares_float).round(4)
+df = df.sort_values(by="Turnover", ascending=False).reset_index()
+create_bar_chart(
+ data=df,
+ x="symbol",
+ y="Turnover",
+ title="S&P Energy Sector YTD Turnover Rate",
+)
+```
+
+
diff --git a/openbb_platform/obbject_extensions/charting/index.md b/openbb_platform/obbject_extensions/charting/index.md
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index 0000000000000000000000000000000000000000..3ca1703066009869ffbdca88915fc9234004c50d
--- /dev/null
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@@ -0,0 +1,359 @@
+---
+title: OpenBB Charting
+sidebar_position: 1
+description: This page introduces the optional openbb-charting extension.
+keywords:
+- explanation
+- OpenBB Platform
+- Python client
+- Fast API
+- getting started
+- extensions
+- charting
+- view
+- Plotly
+- toolkits
+- community
+- Plotly
+- OpenBBFigure
+- PyWry
+---
+
+import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
+
+
+
+## Overview
+
+The `openbb-charting` extension provides elements for building and displaying interactive charts, tables, dashboards, and more, directly from the OpenBB Platform's Python Interface and FAST API.
+
+It allows users to create a custom view, without any previous experience working with Plotly, from any response served by the OpenBB Platform.
+
+The Python Interface includes a custom [PyWry](https://github.com/OpenBB-finance/pywry) backend for displaying any content, in a WebKit HTML window served over `localhost`. In an IDE setting, they will be rendered inline.
+
+To install, follow the instructions [here](installation). The sections below provide a general explanation of the extension.
+
+## How Does It Work?
+
+It works by extending the `OBBject` class with a new attribute, `charting`. When it is installed, every response from the OpenBB Platform will be equipped with these tools.
+
+For functions that have pre-defined views, it serves as an intermediary between the user request and the response, activated when `chart=True`. When a chart is created, it will populate the existing, `chart`, attribute of the `OBBject`. This is where it is served by the FAST API from the function request. In the Python Interface, charts can be generated post-request, regardless of `chart=True`.
+
+The `chart` attribute in the OBBject contains three items, responses from the API have two:
+
+- `fig`: The OpenBBFigure object - an extended Plotly GraphObjects class. Not included in the API response.
+- `content`: The Plotly JSON representation of the chart - Returned to the API.
+- `format`: The format of the chart - 'plotly' is currently the only charting library.
+
+There is one OBBject class method, `show()`, which will display the contents of the `chart` attribute, if populated.
+
+The new `charting` attribute that binds to the OBBject also has a `show()` method. This differs in that it overwrites the existing chart, effectively a 'reset' for the view.
+
+The extension has a docstring, and it lists the class methods within `charting`.
+
+```python
+from openbb import obb
+data = obb.equity.price.historical("AAPL")
+data.charting?
+```
+
+```console
+Charting extension.
+
+Methods
+-------
+show
+ Display chart and save it to the OBBject.
+to_chart
+ Redraw the chart and save it to the OBBject, with an optional entry point for Data.
+functions
+ Return a list of Platform commands with charting functions.
+get_params
+ Return the charting parameters for the function the OBBject was created from.
+indicators
+ Return the list of the available technical indicators to use with the `to_chart` method and OHLC+V data.
+table
+ Display an interactive table.
+create_line_chart
+ Create a line chart from external data.
+create_bar_chart
+ Create a bar chart, on a single x-axis with one or more values for the y-axis, from external data.
+```
+
+:::note
+When creating a chart directly from the OpenBB Platform endpoint, chart parameters must be passed as a nested dictionary under the name, `chart_params`.
+
+```python
+chart_params = dict(
+ title="AAPL 50/200 Day EMA",
+ indicators=dict(
+ ema=dict(length=[50,200]),
+ ),
+)
+params = dict(
+ symbol="AAPL",
+ start_date="2022-01-01",
+ provider="yfinance",
+ chart=True,
+ chart_params=chart_params,
+)
+data = obb.equity.price.historical(**params)
+```
+
+`chart_params` are sent in the body of the request when using the API.
+:::
+
+Passing only `chart=True` will return a default view which can be modified and drawn again post-request, via the `OBBject`.
+
+```console
+OBBject
+
+id: 06614d74-7443-7201-8000-a65f358136a3
+results: [{'date': datetime.date(2022, 1, 3), 'open': 177.8300018310547, 'high': 18...
+provider: yfinance
+warnings: None
+chart: {'content': {'data': [{'close': [182.00999450683594, 179.6999969482422, 174....
+extra: {'metadata': {'arguments': {'provider_choices': {'provider': 'yfinance'}, 's...
+```
+
+```python
+data.show()
+```
+
+
+
+### No Render
+
+The charts can be created without opening the PyWry window, and this is the default behaviour when `chart=True`.
+With the `charting.show()` and `charting.to_chart()` methods, the default is `render=True`.
+Setting as `False` will return the chart to itself, populating the `chart` attribute of OBBject.
+
+## What Endpoints Have Charts?
+
+The OpenBB Platform router, open_api.json, function signatures, and documentation are all generated based on your specific configuration. When the `openbb-charting` extension is installed, any function found in the "[charting_router](https://github.com/OpenBB-finance/OpenBB/blob/develop/openbb_platform/obbject_extensions/charting/openbb_charting/charting_router.py)" adds `chart: bool = False` to the command on build. For example, `obb.index.price.historical?`
+
+```python
+Signature:
+obb.index.price.historical(
+ symbol: Annotated[Union[str, List[str]], OpenBBCustomParameter(description='Symbol to get data for. Multiple comma separated items allowed for provider(s): cboe, fmp, intrinio, polygon, yfinance.')],
+ ...
+ chart: typing.Annotated[bool, OpenBBCustomParameter(description='Whether to create a chart or not, by default False.')] = False,
+ **kwargs,
+) -> openbb_core.app.model.obbject.OBBject
+```
+
+### Charting Functions
+
+The `charting` attribute of every command output has methods for identifying the charting functions and parameters.
+While able to serve JSON-serializable charts, the `openbb-charting` extension is best-suited for use with the Python Interface. Much of the functionality is realized post-request.
+
+Examine the extension by returning any command at all.
+
+```python
+from openbb import obb
+
+data = obb.equity.price.historical("SPY,QQQ,XLK,BTC-USD", provider="yfinance")
+
+data.charting.functions()
+```
+
+```console
+['crypto_price_historical',
+ 'currency_price_historical',
+ 'economy_fred_series',
+ 'equity_price_historical',
+ 'equity_price_performance',
+ 'etf_historical',
+ 'etf_holdings',
+ 'etf_price_performance',
+ 'index_price_historical',
+ 'technical_adx',
+ 'technical_aroon',
+ 'technical_cones',
+ 'technical_ema',
+ 'technical_hma',
+ 'technical_macd',
+ 'technical_rsi',
+ 'technical_sma',
+ 'technical_wma',
+ 'technical_zlma']
+```
+
+:::tip
+The list above should, as shown here, should not be considered as the source of truth. It's just a sample.
+:::
+
+If the `OBBject` in question has a dedicated charting function associated with it, parameters are detailed by the `get_params()` method.
+
+```console
+EquityPriceHistoricalChartQueryParams
+
+ Parameters
+ ----------
+
+ data : Union[Data, list[Data], NoneType]
+ Filtered versions of the data contained in the original `self.results`.
+ Columns should be the same as the original data.
+ Example use is to reduce the number of columns, or the length of data, to plot.
+
+ title : Union[str, NoneType]
+ Title of the chart.
+
+ target : Union[str, NoneType]
+ The specific column to target.
+ If supplied, this will override the candles and volume parameters.
+
+ multi_symbol : bool
+ Flag to indicate whether the data contains multiple symbols.
+ This is mostly handled automatically, but if the chart fails to generate try setting this to True.
+
+ same_axis : bool
+ If True, forces all data to be plotted on the same axis.
+
+ normalize : bool
+ If True, the data will be normalized and placed on the same axis.
+
+ returns : bool
+ If True, the cumulative returns for the length of the time series will be calculated and plotted.
+
+ candles : bool
+ If True, and OHLC exists, and there is only one symbol in the data, candles will be plotted.
+
+ heikin_ashi : bool
+ If True, and `candles=True`, Heikin Ashi candles will be plotted.
+
+ volume : bool
+ If True, and volume exists, and `candles=True`, volume will be plotted.
+
+ indicators : Union[ChartIndicators, dict[str, dict[str, Any]], NoneType]
+ Indicators to be plotted, formatted as a dictionary.
+ Data containing multiple symbols will ignore indicators.
+ Example:
+ indicators = dict(
+ sma=dict(length=[20,30,50]),
+ adx=dict(length=14),
+ rsi=dict(length=14),
+ )
+```
+
+Not all commands will have the same `chart_params`, and some less than others, but it is always possible to redraw the chart with a different combination post-request. Here's what the default chart is from the output of the command above.
+
+If `chart=True` was not specified, it will need to be created.
+
+```python
+data.charting.to_chart()
+```
+
+
+
+The extension recognized that multiple symbols were within the object, and made a determination to display cumulative returns by default.
+
+A candlestick chart will draw only when there is one symbol in the data.
+
+```python
+obb.equity.price.historical(
+ symbol="XLK",
+ start_date="2024-01-01",
+ provider="yfinance",
+ chart=True,
+ chart_params=dict(title="XLK YTD", heikin_ashi=True)
+).show()
+```
+
+
+
+## Endpoints Without Charts
+
+Most functions do not have dedicated charts. However, it's still possible to generate one automatically. Using the `data` above, we can try passing it through a quantitative analysis command.
+
+```python
+data = obb.equity.price.historical(
+ symbol="XLK",
+ start_date="2023-01-01",
+ provider="yfinance",
+)
+qa = obb.quantitative.rolling.stdev(data.results, target="close")
+
+qa.charting.show(title="XLK Rolling 21 Day Standard Deviation")
+```
+
+
+
+## Charts From Any Data
+
+There are methods for creating a generic chart from any external data.
+They will bypass any data contained in the parent object, unless specifically fed into itself.
+
+- charting.create_bar_chart()
+- charting.create_line_chart()
+
+They can also be used as standalone components by initializing an empty instance of the OBBject class.
+
+```python
+from openbb import obb
+from openbb_core.app.model.obbject import OBBject
+create_bar_chart = OBBject(results=None).charting.create_bar_chart
+
+create_bar_chart?
+````
+
+```console
+Create a bar chart on a single x-axis with one or more values for the y-axis.
+
+Parameters
+----------
+data : Union[list, dict, pd.DataFrame, List[pd.DataFrame], pd.Series, List[pd.Series], np.ndarray, Data]
+ Data to plot.
+x : str
+ The x-axis column name.
+y : Union[str, List[str]]
+ The y-axis column name(s).
+barmode : Literal["group", "stack", "relative", "overlay"], optional
+ The bar mode, by default "group".
+xtype : Literal["category", "multicategory", "date", "log", "linear"], optional
+ The x-axis type, by default "category".
+title : Optional[str], optional
+ The title of the chart, by default None.
+xtitle : Optional[str], optional
+ The x-axis title, by default None.
+ytitle : Optional[str], optional
+ The y-axis title, by default None.
+orientation : Literal["h", "v"], optional
+ The orientation of the chart, by default "v".
+colors: Optional[List[str]], optional
+ Manually set the colors to cycle through for each column in 'y', by default None.
+layout_kwargs : Optional[Dict[str, Any]], optional
+ Additional keyword arguments to apply with figure.update_layout(), by default None.
+
+Returns
+-------
+OpenBBFigure
+ The OpenBBFigure object.
+```
+
+## Tables
+
+The `openbb-charting` extension is equipped with interactive tables, utilizing the React framework. They are displayed by using the `table` method.
+
+```python
+data = obb.equity.price.quote("AAPL,MSFT,GOOGL,META,TSLA,AMZN", provider="yfinance")
+data.charting.table()
+```
+
+
+
+External data can also be supplied, providing an opportunity to filter or apply Pandas operations before display.
+
+```python
+new_df = df.to_df().T
+new_df.index.name="metric"
+new_df.columns = new_df.loc["symbol"]
+new_df.drop("symbol", inplace=True)
+data.charting.table(data=new_df)
+```
+
+
+
+:::important
+This does not alter the contents of the original object, the displayed data is a copy.
+:::
diff --git a/openbb_platform/obbject_extensions/charting/indicators.md b/openbb_platform/obbject_extensions/charting/indicators.md
new file mode 100644
index 0000000000000000000000000000000000000000..635cb71ce260b09cd9dfb6e6eb4d3ffe2e3c63d3
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/indicators.md
@@ -0,0 +1,384 @@
+---
+title: Indicators
+sidebar_position: 2
+description: A tutorial of the technical indicators included with the openbb-charting library, including how to get started using them.
+keywords:
+- tutorial
+- OpenBB Platform
+- getting started
+- extensions
+- charting
+- view
+- Plotly
+- toolkits
+- indicators
+- Plotly
+- OpenBBFigure
+- PyWry
+---
+
+import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
+
+
+
+## Introduction
+
+Select indicators (technical) can be added to a chart where the data is OHLC+V prices over time, and the data is for one symbol only.
+They are meant as quick visualizations, and a way to build more complex charts.
+As starting points, they can be refined to perfection by manipulating the figure object directly.
+
+```python
+from datetime import datetime, timedelta
+from openbb import obb
+data = obb.equity.price.historical(
+ "TSLA",
+ provider="yfinance",
+ interval="15m",
+ start_date=(datetime.now()-timedelta(days=21)).date(),
+ chart=True,
+ chart_params=dict(
+ heikin_ashi=True,
+ indicators=(dict(
+ ema=dict(length=[8,32]),
+ srlines={}, # For indicators, an empty dictionary implies the default state.
+ rsi=dict(length=32)
+ ))
+ )
+)
+data.show()
+```
+
+
+
+## Available Indicators
+
+To get all the indicators, use the `charting.indicators()` method.
+The object returned is a Pydantic model where each indicator is field.
+If you don't catch it, it will print as a docstring to the console.
+
+:::danger
+Some indicators, like RSI and MACD, create subplots. Only 4 subplots (not including the main candles + volume) can be created within the same view.
+:::
+
+```python
+data.charting.indicators()
+```
+
+```console
+SMA:
+
+ Parameters
+ ----------
+
+ length : Union[int, list[int]]
+ Window length for the moving average, by default is 50.
+ The number is relative to the interval of the time series data.
+
+ offset : int
+ Number of periods to offset for the moving average, by default is 0.
+
+EMA:
+
+ Parameters
+ ----------
+
+ length : Union[int, list[int]]
+ Window length for the moving average, by default is 50.
+ The number is relative to the interval of the time series data.
+
+ offset : int
+ Number of periods to offset for the moving average, by default is 0.
+
+HMA:
+
+ Parameters
+ ----------
+
+ length : Union[int, list[int]]
+ Window length for the moving average, by default is 50.
+ The number is relative to the interval of the time series data.
+
+ offset : int
+ Number of periods to offset for the moving average, by default is 0.
+
+WMA:
+
+ Parameters
+ ----------
+
+ length : Union[int, list[int]]
+ Window length for the moving average, by default is 50.
+ The number is relative to the interval of the time series data.
+
+ offset : int
+ Number of periods to offset for the moving average, by default is 0.
+
+ZLMA:
+
+ Parameters
+ ----------
+
+ length : Union[int, list[int]]
+ Window length for the moving average, by default is 50.
+ The number is relative to the interval of the time series data.
+
+ offset : int
+ Number of periods to offset for the moving average, by default is 0.
+
+AD:
+
+ Parameters
+ ----------
+
+ offset : int
+ Offset value for the AD, by default is 0.
+
+AD Oscillator:
+
+ Parameters
+ ----------
+
+ fast : int
+ Number of periods to use for the fast calculation, by default 3.
+
+ slow : int
+ Number of periods to use for the slow calculation, by default 10.
+
+ offset : int
+ Offset to be used for the calculation, by default is 0.
+
+ADX:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the ADX, by default is 50.
+
+ scalar : float
+ Scalar to multiply the ADX by, default is 100.
+
+ drift : int
+ Drift value for the ADX, by default is 1.
+
+Aroon:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the Aroon, by default is 50.
+
+ scalar : float
+ Scalar to multiply the Aroon by, default is 100.
+
+ATR:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the ATR, by default is 14.
+
+ mamode : Literal[rma, ema, sma, wma]
+ The mode to use for the moving average calculation.
+
+ drift : int
+ The difference period.
+
+ offset : int
+ Number of periods to offset the result, by default is 0.
+
+CCI:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the CCI, by default is 14.
+
+ scalar : float
+ Scalar to multiply the CCI by, default is 0.015.
+
+Clenow:
+
+ Parameters
+ ----------
+
+ period : int
+ The number of periods for the momentum, by default 90.
+
+Demark:
+
+ Parameters
+ ----------
+
+ show_all : bool
+ Show 1 - 13.
+ If set to False, show 6 - 9.
+
+ offset : int
+ Number of periods to offset the result, by default is 0.
+
+Donchian:
+
+ Parameters
+ ----------
+
+ lower : Union[int, NoneType]
+ Window length for the lower band, by default is 20.
+
+ upper : Union[int, NoneType]
+ Window length for the upper band, by default is 20.
+
+ offset : Union[int, NoneType]
+ Number of periods to offset the result, by default is 0.
+
+Fib:
+
+ Parameters
+ ----------
+
+ period : int
+ The period to calculate the Fibonacci Retracement, by default 120.
+
+ start_date : Union[str, NoneType]
+ The start date for the Fibonacci Retracement.
+
+ end_date : Union[str, NoneType]
+ The end date for the Fibonacci Retracement.
+
+Fisher:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the Fisher Transform, by default is 14.
+
+ signal : int
+ Fisher Signal Period
+
+Ichimoku:
+
+ Parameters
+ ----------
+
+ conversion : int
+ The conversion line period, by default 9.
+
+ base : int
+ The base line period, by default 26.
+
+ lagging : int
+ The lagging line period, by default 52.
+
+ offset : int
+ The offset period, by default 26.
+
+ lookahead : bool
+ Drops the Chikou Span Column to prevent potential data leak
+
+KC:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the Keltner Channel, by default is 20.
+
+ scalar : float
+ Scalar to multiply the ATR, by default is 2.
+
+ mamode : Literal[ema, sma, wma, hna, zlma, rma]
+ The mode to use for the moving average calculation, by default is ema.
+
+ offset : int
+ Number of periods to offset the result, by default is 0.
+
+MACD:
+
+ Parameters
+ ----------
+
+ fast : Union[int, NoneType]
+ Window length for the fast EMA, by default is 12.
+
+ slow : Union[int, NoneType]
+ Window length for the slow EMA, by default is 26.
+
+ signal : Union[int, NoneType]
+ Window length for the signal line, by default is 9.
+
+ scalar : Union[float, NoneType]
+ Scalar to multiply the MACD by, default is 100.
+
+OBV:
+
+ Parameters
+ ----------
+
+ offset : int
+ Number of periods to offset the result, by default is 0.
+
+RSI:
+
+ Parameters
+ ----------
+
+ length : int
+ Window length for the RSI, by default is 14.
+
+ scalar : float
+ Scalar to multiply the RSI by, default is 100.
+
+ drift : int
+ Drift value for the RSI, by default is 1.
+
+SRLines:
+
+ Parameters
+ ----------
+
+ show : bool
+ Show the support and resistance lines.
+
+Stoch:
+
+ Parameters
+ ----------
+
+ fast_k : int
+ The fast K period, by default 14.
+
+ slow_d : int
+ The slow D period, by default 3.
+
+ slow_k : int
+ The slow K period, by default 3.
+```
+
+The model can be converted to a dictionary and then passed through the `indicators` params.
+
+The chart below is built from the same object as the one above.
+
+```python
+indicators = data.charting.indicators().dict()
+macd=indicators.get("macd")
+kc=indicators.get("kc")
+chart_params=dict(
+ candles=False,
+ title="My New Chart",
+ indicators=(dict(
+ macd=macd,
+ kc=kc,
+ ))
+)
+data.charting.to_chart(**chart_params)
+```
+
+
+
+:::tip
+Data can be exported directly from the chart as a CSV. Use the button at the bottom-right of the mode bar.
+:::
diff --git a/openbb_platform/obbject_extensions/charting/installation.md b/openbb_platform/obbject_extensions/charting/installation.md
new file mode 100644
index 0000000000000000000000000000000000000000..2282d777aebb84003408c56b3cdc5919297155b3
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/installation.md
@@ -0,0 +1,71 @@
+---
+title: Installation
+sidebar_position: 1
+description: This page outlines the installation of the openbb-charting extension.
+keywords:
+- tutorial
+- OpenBB Platform
+- Installation
+- Python client
+- Fast API
+- getting started
+- extensions
+- charting
+- view
+- Plotly
+- toolkit
+- community
+- Plotly
+- OpenBBFigure
+- PyWry
+---
+
+import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
+
+
+
+## PyPI
+
+To install the extension, run the following command in this folder:
+
+```bash
+pip install openbb-charting
+```
+
+> Find the latest version on [PyPI](https://pypi.org/project/openbb-charting/).
+
+## Editable Mode
+
+To install from source in editable mode, navigate into the folder, `~/openbb_platform/extensions/charting`, and enter:
+
+```console
+pip install -e .
+```
+
+After installation, the Python interface will automatically rebuild on initialization. This process can also be triggered manually with:
+
+```python
+import openbb
+openbb.build()
+```
+
+The Python interpreter may need to be restarted.
+
+## PyWry Dependency In Linux
+
+When using Linux distributions, the PyWry dependency requires certain dependencies to be installed first.
+
+- Debian-based / Ubuntu / Mint:
+`sudo apt install libwebkit2gtk-4.0-dev`
+
+- Arch Linux / Manjaro:
+`sudo pacman -S webkit2gtk`
+
+- Fedora:
+`sudo dnf install gtk3-devel webkit2gtk3-devel`
+
+If Rust (Cargo) is required, install it:
+
+```console
+curl --proto '=https' --tlsv1.3 https://sh.rustup.rs -sSf | sh
+```
diff --git a/openbb_platform/obbject_extensions/charting/integration/test_charting_api.py b/openbb_platform/obbject_extensions/charting/integration/test_charting_api.py
new file mode 100644
index 0000000000000000000000000000000000000000..7076f5728f5610bbdcad78cccfe3e5e339ac4828
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/integration/test_charting_api.py
@@ -0,0 +1,908 @@
+"""Integration tests for charting API."""
+
+import base64
+import json
+
+import pytest
+import requests
+from extensions.tests.conftest import parametrize
+from openbb_core.env import Env
+from openbb_core.provider.utils.helpers import get_querystring
+
+
+@pytest.fixture(scope="session")
+def headers():
+ """Headers fixture."""
+ return get_headers()
+
+
+# pylint:disable=redefined-outer-name
+
+data: dict = {}
+
+
+def get_headers():
+ """Get headers for requests."""
+ if "headers" in data:
+ return data["headers"]
+
+ userpass = f"{Env().API_USERNAME}:{Env().API_PASSWORD}"
+ userpass_bytes = userpass.encode("ascii")
+ base64_bytes = base64.b64encode(userpass_bytes)
+
+ data["headers"] = {"Authorization": f"Basic {base64_bytes.decode('ascii')}"}
+ return data["headers"]
+
+
+def get_equity_data():
+ """Get equity data."""
+ if "stocks_data" in data:
+ return data["stocks_data"]
+
+ url = "http://0.0.0.0:8000/api/v1/equity/price/historical?symbol=AAPL&provider=fmp"
+ result = requests.get(url, headers=get_headers(), timeout=10)
+ data["stocks_data"] = result.json()["results"]
+
+ return data["stocks_data"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "AAPL",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_price_historical(params, headers):
+ """Test chart equity price historical.."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/equity/price/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=40)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "USDGBP",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_currency_price_historical(params, headers):
+ """Test chart currency price historical."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/currency/price/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=40)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "QQQ",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_historical(params, headers):
+ """Test chart etf historical."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/etf/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=40)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "NDX",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_index_price_historical(params, headers):
+ """Test chart index price historical."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/index/price/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=40)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "BTCUSD",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_crypto_price_historical(params, headers):
+ """Test chart crypto price historical."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/crypto/price/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=40)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "index": "date",
+ "length": "60",
+ "scalar": "90.0",
+ "drift": "2",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_adx(params, headers):
+ """Test chart ta adx."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/adx?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [{"data": "", "index": "date", "length": "30", "scalar": "110", "chart": True}],
+)
+@pytest.mark.integration
+def test_charting_technical_aroon(params, headers):
+ """Test chart ta aroon."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/aroon?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "",
+ "length": "60",
+ "offset": "10",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_ema(params, headers):
+ """Test chart ta ema."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/ema?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "2",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_hma(params, headers):
+ """Test chart ta hma."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/hma?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "fast": "10",
+ "slow": "30",
+ "signal": "10",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_macd(params, headers):
+ """Test chart ta macd."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/macd?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "16",
+ "scalar": "90.0",
+ "drift": "2",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_rsi(params, headers):
+ """Test chart ta rsi."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/rsi?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "2",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_sma(params, headers):
+ """Test chart ta sma."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/sma?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "60",
+ "offset": "10",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_wma(params, headers):
+ """Test chart ta wma."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/wma?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "5",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_zlma(params, headers):
+ """Test chart ta zlma."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/zlma?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "model": "yang_zhang",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_cones(params, headers):
+ """Test chart ta cones."""
+ params = {p: v for p, v in params.items() if v}
+ body = json.dumps(get_equity_data())
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/technical/cones?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "DGS10",
+ "transform": "pc1",
+ "chart": True,
+ "provider": "fred",
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_economy_fred_series(params, headers):
+ """Test chart ta cones."""
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/economy/fred_series?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "study": "price",
+ "benchmark": "SPY",
+ "long_period": 252,
+ "short_period": 21,
+ "window": 21,
+ "trading_periods": 252,
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_relative_rotation(params):
+ params = {p: v for p, v in params.items() if v}
+ data_params = dict(
+ symbol="AAPL,MSFT,GOOGL,AMZN,SPY",
+ provider="yfinance",
+ start_date="2022-01-01",
+ end_date="2024-01-01",
+ )
+ data_query_str = get_querystring(data_params, [])
+ data_url = f"http://0.0.0.0:8000/api/v1/equity/price/historical?{data_query_str}"
+ data_result = requests.get(data_url, headers=get_headers(), timeout=10).json()[
+ "results"
+ ]
+ body = json.dumps({"data": data_result})
+ query_str = get_querystring(params, ["data"])
+ url = f"http://0.0.0.0:8000/api/v1/technical/relative_rotation?{query_str}"
+ result = requests.post(url, headers=get_headers(), timeout=10, data=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT,XLB,XLI,XLH,XLC,XLY,XLU,XLK",
+ "chart": True,
+ "provider": "finviz",
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_price_performance(params, headers):
+ """Test chart equity price performance."""
+ params = {p: v for p, v in params.items() if v}
+ body = (
+ json.dumps(
+ {"extra_params": {"chart_params": {"limit": 4, "orientation": "h"}}}
+ ),
+ )
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/equity/price/performance?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT,XLB,XLI,XLH,XLC,XLY,XLU,XLK",
+ "chart": True,
+ "provider": "fmp",
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_price_performance(params, headers):
+ """Test chart equity price performance."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"orientation": "v"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/etf/price_performance?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT",
+ "chart": True,
+ "provider": "fmp",
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_holdings(params, headers):
+ """Test chart etf holdings."""
+ params = {p: v for p, v in params.items() if v}
+ body = (
+ json.dumps(
+ {"extra_params": {"chart_params": {"orientation": "v", "limit": 10}}}
+ ),
+ )
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/etf/holdings?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "econdb",
+ "country": "united_kingdom",
+ "date": None,
+ "chart": True,
+ }
+ ),
+ (
+ {
+ "provider": "fred",
+ "date": "2023-05-10,2024-05-10",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_fixedincome_government_yield_curve(params, headers):
+ """Test chart fixedincome government yield curve."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"title": "test chart"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/fixedincome/government/yield_curve?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "provider": "yfinance",
+ "symbol": "ES",
+ "start_date": "2022-01-01",
+ "end_date": "2022-02-01",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_derivatives_futures_historical(params, headers):
+ """Test chart derivatives futures historical."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"title": "test chart"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/derivatives/futures/historical?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "ES",
+ "date": None,
+ "chart": True,
+ }
+ ),
+ (
+ {
+ "provider": "cboe",
+ "symbol": "VX",
+ "date": "2024-06-25",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_derivatives_futures_curve(params, headers):
+ """Test chart derivatives futures curve."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"title": "test chart"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/derivatives/futures/curve?{query_str}"
+ result = requests.get(url, headers=headers, timeout=30, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "provider": "fmp",
+ "symbol": "AAPL",
+ "start_date": "2024-01-01",
+ "end_date": "2024-06-30",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_historical_market_cap(params, headers):
+ """Test chart equity historical market cap."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"title": "test chart"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/equity/historical_market_cap?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "bls",
+ "symbol": "APUS49D74714,APUS49D74715,APUS49D74716",
+ "start_date": "2014-01-01",
+ "end_date": "2024-07-01",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_economy_survey_bls_series(params, headers):
+ """Test chart economy survey bls series."""
+ params = {p: v for p, v in params.items() if v}
+ body = (json.dumps({"extra_params": {"chart_params": {"title": "test chart"}}}),)
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/economy/survey/bls_series?{query_str}"
+ result = requests.get(url, headers=headers, timeout=10, json=body)
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "method": "pearson",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_econometrics_correlation_matrix(params, headers):
+ """Test chart econometrics correlation matrix."""
+ # pylint:disable=import-outside-toplevel
+ from pandas import DataFrame
+
+ url = "http://0.0.0.0:8000/api/v1/equity/price/historical?symbol=AAPL,MSFT,GOOG&provider=yfinance"
+ result = requests.get(url, headers=headers, timeout=10)
+ df = DataFrame(result.json()["results"])
+ df = df.pivot(index="date", columns="symbol", values="close").reset_index()
+ body = df.to_dict(orient="records")
+
+ params = {p: v for p, v in params.items() if v}
+
+ query_str = get_querystring(params, [])
+ url = f"http://0.0.0.0:8000/api/v1/econometrics/correlation_matrix?{query_str}"
+ result = requests.post(url, headers=headers, timeout=10, data=json.dumps(body))
+
+ assert isinstance(result, requests.Response)
+ assert result.status_code == 200
+
+ chart = result.json()["chart"]
+ fig = chart.pop("fig", {})
+
+ assert chart
+ assert not fig
+ assert list(chart.keys()) == ["content", "format"]
diff --git a/openbb_platform/obbject_extensions/charting/integration/test_charting_python.py b/openbb_platform/obbject_extensions/charting/integration/test_charting_python.py
new file mode 100644
index 0000000000000000000000000000000000000000..4d9481278ba6fe039ad456265a35b88920af5fe5
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/integration/test_charting_python.py
@@ -0,0 +1,747 @@
+"""Test charting extension."""
+
+import pytest
+from extensions.tests.conftest import parametrize
+from openbb_charting.core.openbb_figure import OpenBBFigure
+from openbb_core.app.model.obbject import OBBject
+
+
+# pylint:disable=inconsistent-return-statements
+@pytest.fixture(scope="session")
+def obb(pytestconfig):
+ """Fixture to setup obb."""
+ if pytestconfig.getoption("markexpr") != "not integration":
+ import openbb # pylint:disable=import-outside-toplevel
+
+ return openbb.obb
+
+
+# pylint:disable=redefined-outer-name
+
+data: dict = {}
+
+
+def get_equity_data():
+ """Get equity data."""
+ import openbb # pylint:disable=import-outside-toplevel
+
+ if "stocks_data" in data:
+ return data["stocks_data"]
+
+ symbol = "AAPL"
+ provider = "fmp"
+
+ data["stocks_data"] = openbb.obb.equity.price.historical(
+ symbol=symbol, provider=provider
+ ).results
+ return data["stocks_data"]
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "AAPL",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_price_historical(params, obb):
+ """Test chart equity price historical."""
+ result = obb.equity.price.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "JPYUSD",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_currency_price_historical(params, obb):
+ """Test chart currency price historical."""
+ result = obb.currency.price.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "BTCUSD",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_crypto_price_historical(params, obb):
+ """Test chart crypto price historical."""
+ result = obb.crypto.price.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "NDX",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_index_price_historical(params, obb):
+ """Test chart index price historical."""
+ result = obb.index.price.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "QQQ",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_historical(params, obb):
+ """Test chart etf historical."""
+ result = obb.etf.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "index": "date",
+ "length": "60",
+ "scalar": "90.0",
+ "drift": "2",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_adx(params, obb):
+ """Test chart ta adx."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.adx(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "index": "date",
+ "length": "30",
+ "scalar": "110",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_aroon(params, obb):
+ """Test chart ta aroon."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.aroon(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "",
+ "length": "60",
+ "offset": "10",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_ema(params, obb):
+ """Test chart ta ema."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.ema(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "2",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_hma(params, obb):
+ """Test chart ta hma."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.hma(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "fast": "10",
+ "slow": "30",
+ "signal": "10",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_macd(params, obb):
+ """Test chart ta macd."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.macd(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "16",
+ "scalar": "90.0",
+ "drift": "2",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_rsi(params, obb):
+ """Test chart ta rsi."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.rsi(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "2",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_sma(params, obb):
+ """Test chart ta sma."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.sma(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "60",
+ "offset": "10",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_wma(params, obb):
+ """Test chart ta wma."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.wma(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "target": "high",
+ "index": "date",
+ "length": "55",
+ "offset": "5",
+ "chart": "True",
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_zlma(params, obb):
+ """Test chart ta zlma."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.zlma(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "model": "yang_zhang",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_cones(params, obb):
+ """Test chart ta cones."""
+ params = {p: v for p, v in params.items() if v}
+
+ params["data"] = get_equity_data()
+
+ result = obb.technical.cones(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "DGS10",
+ "transform": "pc1",
+ "chart": True,
+ "provider": "fred",
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_economy_fred_series(params, obb):
+ """Test chart economy fred series."""
+ result = obb.economy.fred_series(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "data": "",
+ "study": "price",
+ "benchmark": "SPY",
+ "long_period": 252,
+ "short_period": 21,
+ "window": 21,
+ "trading_periods": 252,
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_technical_relative_rotation(params, obb):
+ params["data"] = obb.equity.price.historical(
+ "AAPL,MSFT,GOOGL,AMZN,SPY",
+ provider="yfinance",
+ start_date="2022-01-01",
+ end_date="2024-01-01",
+ ).results
+ result = obb.technical.relative_rotation(
+ data=params["data"],
+ benchmark=params["benchmark"],
+ study=params["study"],
+ long_period=params["long_period"],
+ short_period=params["short_period"],
+ window=params["window"],
+ trading_periods=params["trading_periods"],
+ chart=params["chart"],
+ )
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results.rs_ratios) > 0 # type: ignore
+ assert result.chart.content # type: ignore
+ assert isinstance(result.chart.fig, OpenBBFigure) # type: ignore
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT,XLB,XLI,XLH,XLC,XLY,XLU,XLK",
+ "chart": True,
+ "provider": "finviz",
+ "chart_params": {"limit": 4, "orientation": "h"},
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_price_performance(params, obb):
+ """Test chart equity price performance."""
+ result = obb.equity.price.performance(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT,XLB,XLI,XLH,XLC,XLY,XLU,XLK",
+ "chart": True,
+ "provider": "fmp",
+ "chart_params": {"orientation": "v"},
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_price_performance(params, obb):
+ """Test chart etf price performance."""
+ result = obb.etf.price_performance(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": None,
+ "symbol": "XRT",
+ "chart": True,
+ "provider": "fmp",
+ "chart_params": {"orientation": "v", "limit": 10},
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_etf_holdings(params, obb):
+ """Test chart etf holdings."""
+ result = obb.etf.holdings(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "econdb",
+ "country": "united_kingdom",
+ "date": None,
+ "chart": True,
+ }
+ ),
+ (
+ {
+ "provider": "fred",
+ "date": "2023-05-10,2024-05-10",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_fixedincome_government_yield_curve(params, obb):
+ """Test chart fixedincome government yield curve."""
+ result = obb.fixedincome.government.yield_curve(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "provider": "yfinance",
+ "symbol": "ES",
+ "start_date": "2022-01-01",
+ "end_date": "2022-02-01",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_derivatives_futures_historical(params, obb):
+ """Test chart derivatives futures historical."""
+ result = obb.derivatives.futures.historical(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "yfinance",
+ "symbol": "ES",
+ "date": None,
+ "chart": True,
+ }
+ ),
+ (
+ {
+ "provider": "cboe",
+ "symbol": "VX",
+ "date": "2024-06-25",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_derivatives_futures_curve(params, obb):
+ """Test chart derivatives futures curve."""
+ result = obb.derivatives.futures.curve(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "fmp",
+ "symbol": "AAPL",
+ "start_date": "2024-01-01",
+ "end_date": "2024-06-30",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_equity_historical_market_cap(params, obb):
+ """Test chart equity historical market cap."""
+ result = obb.equity.historical_market_cap(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ (
+ {
+ "provider": "bls",
+ "symbol": "APUS49D74714,APUS49D74715,APUS49D74716",
+ "start_date": "2014-01-01",
+ "end_date": "2024-07-01",
+ "chart": True,
+ }
+ ),
+ ],
+)
+@pytest.mark.integration
+def test_charting_economy_survey_bls_series(params, obb):
+ """Test chart economy survey bls series."""
+ result = obb.economy.survey.bls_series(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
+
+
+@parametrize(
+ "params",
+ [
+ {
+ "data": "",
+ "method": "pearson",
+ "chart": True,
+ }
+ ],
+)
+@pytest.mark.integration
+def test_charting_econometrics_correlation_matrix(params, obb):
+ """Test chart econometrics correlation matrix."""
+
+ symbols = "XRT,XLB,XLI,XLH,XLC,XLY,XLU,XLK".split(",")
+ params["data"] = (
+ obb.equity.price.historical(symbol=symbols, provider="yfinance")
+ .to_df()
+ .pivot(columns="symbol", values="close")
+ .filter(items=symbols, axis=1)
+ )
+ result = obb.econometrics.correlation_matrix(**params)
+ assert result
+ assert isinstance(result, OBBject)
+ assert len(result.results) > 0
+ assert result.chart.content
+ assert isinstance(result.chart.fig, OpenBBFigure)
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/__init__.py b/openbb_platform/obbject_extensions/charting/openbb_charting/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f3e8cab7d8797476827b0390f860d02c2130e307
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/__init__.py
@@ -0,0 +1,25 @@
+"""OpenBB OBBject extension for charting."""
+
+import warnings
+
+from openbb_core.app.model.extension import Extension
+
+warnings.filterwarnings(
+ "ignore",
+ category=UserWarning,
+ module="openbb_core.app.model.extension",
+)
+
+
+def get_charting_module():
+ """Get the Charting module."""
+ # pylint: disable=import-outside-toplevel
+ import importlib
+
+ _Charting = importlib.import_module("openbb_charting.charting").Charting
+ return _Charting
+
+
+ext = Extension(name="charting", description="Create custom charts from OBBject data.")
+
+Charting = ext.obbject_accessor(get_charting_module())
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charting.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charting.py
new file mode 100644
index 0000000000000000000000000000000000000000..119a2b9337d37fa4678dac82bbb8451e3fcfe777
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charting.py
@@ -0,0 +1,681 @@
+"""Charting Class implementation."""
+
+# pylint: disable=too-many-arguments,unused-argument,too-many-positional-arguments
+
+from typing import (
+ TYPE_CHECKING,
+ Any,
+ Callable,
+ ClassVar,
+ Dict,
+ List,
+ Literal,
+ Optional,
+ Tuple,
+ Type,
+ Union,
+)
+from warnings import warn
+
+from importlib_metadata import entry_points
+from openbb_core.app.model.charts.chart import Chart
+from openbb_core.app.model.obbject import OBBject
+from openbb_core.provider.abstract.data import Data
+
+from openbb_charting.charts.helpers import (
+ get_charting_functions,
+ get_charting_functions_list,
+)
+
+if TYPE_CHECKING:
+ from numpy import ndarray # noqa
+ from pandas import DataFrame, Series # noqa
+ from plotly.graph_objs import Figure # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+ from openbb_charting.query_params import ChartParams # noqa
+ from openbb_charting.core.backend import Backend # noqa
+
+
+class Charting:
+ """Charting extension.
+
+ Methods
+ -------
+ show
+ Display chart and save it to the OBBject.
+ to_chart
+ Redraw the chart and save it to the OBBject, with an optional entry point for Data.
+ functions
+ Return a list of Platform commands with charting functions.
+ get_params
+ Return the charting parameters for the function the OBBject was created from.
+ indicators
+ Return the list of the available technical indicators to use with the `to_chart` method and OHLC+V data.
+ table
+ Display an interactive table.
+ create_line_chart
+ Create a line chart from external data.
+ create_bar_chart
+ Create a bar chart, on a single x-axis with one or more values for the y-axis, from external data.
+ create_correlation_matrix
+ Create a correlation matrix from external data.
+ toggle_chart_style
+ Toggle the chart style, of an existing chart, between light and dark mode.
+ """
+
+ _extension_views: ClassVar[List[Type]] = [
+ entry_point.load()
+ for entry_point in entry_points(group="openbb_charting_extension")
+ ]
+ _format = "plotly" # the charts computed by this extension will be in plotly format
+
+ def __init__(self, obbject):
+ """Initialize Charting extension."""
+ # pylint: disable=import-outside-toplevel
+ import importlib # noqa
+
+ charting_settings_module = importlib.import_module(
+ "openbb_core.app.model.charts.charting_settings", "ChartingSettings"
+ )
+ ChartingSettings = charting_settings_module.ChartingSettings
+
+ self._obbject: OBBject = obbject
+ self._charting_settings = ChartingSettings(
+ user_settings=self._obbject._user_settings, # type: ignore
+ system_settings=self._obbject._system_settings, # type: ignore
+ )
+ self._backend = self._handle_backend()
+ self._functions: Dict[str, Callable] = self._get_functions()
+
+ @classmethod
+ def indicators(cls):
+ """Return an instance of the IndicatorsParams class, containing all available indicators and their parameters.
+
+ Without assigning to a variable, it will print the the information to the console.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.query_params import IndicatorsParams
+
+ return IndicatorsParams()
+
+ @classmethod
+ def functions(cls) -> List[str]:
+ """Return a list of the available functions."""
+ functions: List[str] = []
+ for view in cls._extension_views:
+ functions.extend(get_charting_functions_list(view))
+
+ return functions
+
+ def _get_functions(self) -> Dict[str, Callable]:
+ """Return a dict with the available functions."""
+ functions: Dict[str, Callable] = {}
+ for view in self._extension_views:
+ functions.update(get_charting_functions(view))
+
+ return functions
+
+ def _handle_backend(self) -> "Backend":
+ """Create and start the backend."""
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.core.backend import create_backend, get_backend
+
+ create_backend(self._charting_settings)
+ backend = get_backend()
+ backend.start(debug=self._charting_settings.debug_mode)
+ return backend
+
+ def _get_chart_function(self, route: str) -> Callable:
+ """Given a route, it returns the chart function. The module must contain the given route."""
+ if route is None:
+ raise ValueError("OBBject was initialized with no function route.")
+ adjusted_route = route.replace("/", "_")[1:]
+ if adjusted_route not in self._functions:
+ raise ValueError(
+ f"Could not find the route `{adjusted_route}` in the charting functions."
+ )
+ return self._functions[adjusted_route]
+
+ def get_params(self) -> Union["ChartParams", None]:
+ """Return the ChartQueryParams class for the function the OBBject was created from.
+
+ Without assigning to a variable, it will print the docstring to the console.
+ If the class is not defined, the help for the function will be returned.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.query_params import ChartParams
+
+ if self._obbject._route is None: # pylint: disable=protected-access
+ raise ValueError("OBBject was initialized with no function route.")
+ charting_function = (
+ self._obbject._route # pylint: disable=protected-access
+ ).replace("/", "_")[1:]
+ if hasattr(ChartParams, charting_function):
+ return getattr(ChartParams, charting_function)()
+
+ return help( # type: ignore
+ self._get_chart_function( # pylint: disable=protected-access
+ self._obbject.extra[ # pylint: disable=protected-access
+ "metadata"
+ ].route
+ )
+ )
+
+ def _prepare_data_as_df(
+ self, data: Optional[Union["DataFrame", "Series"]]
+ ) -> Tuple["DataFrame", bool]:
+ """Convert supplied data to a DataFrame."""
+ # pylint: disable=import-outside-toplevel
+ from openbb_core.app.utils import basemodel_to_df, convert_to_basemodel
+ from pandas import DataFrame, Series
+
+ has_data = (
+ isinstance(data, (Data, DataFrame, Series)) and not data.empty # type: ignore
+ ) or (bool(data))
+ index = (
+ data.index.name
+ if has_data and isinstance(data, (DataFrame, Series))
+ else None
+ )
+ data_as_df: DataFrame = (
+ basemodel_to_df(convert_to_basemodel(data), index=index)
+ if has_data
+ else self._obbject.to_dataframe(index=index)
+ )
+ if "date" in data_as_df.columns:
+ data_as_df = data_as_df.set_index("date")
+ if "provider" in data_as_df.columns:
+ data_as_df.drop(columns="provider", inplace=True)
+ return data_as_df, has_data
+
+ # pylint: disable=too-many-locals
+ def create_line_chart(
+ self,
+ data: Union[
+ list,
+ dict,
+ "DataFrame",
+ List["DataFrame"],
+ "Series",
+ List["Series"],
+ "ndarray",
+ Data,
+ ],
+ index: Optional[str] = None,
+ target: Optional[str] = None,
+ title: Optional[str] = None,
+ x: Optional[str] = None,
+ xtitle: Optional[str] = None,
+ y: Optional[Union[str, List[str]]] = None,
+ ytitle: Optional[str] = None,
+ y2: Optional[Union[str, List[str]]] = None,
+ y2title: Optional[str] = None,
+ layout_kwargs: Optional[dict] = None,
+ scatter_kwargs: Optional[dict] = None,
+ normalize: bool = False,
+ returns: bool = False,
+ same_axis: bool = False,
+ render: bool = True,
+ **kwargs,
+ ) -> Union["OpenBBFigure", "Figure", None]:
+ """Create a line chart from external data and render a chart or return the OpenBBFigure.
+
+ Parameters
+ ----------
+ data : Union[Data, DataFrame, Series]
+ Data to be plotted (OHLCV data).
+ index : Optional[str], optional
+ Index column, by default None
+ target : Optional[str], optional
+ Target column to be plotted, by default None
+ title : Optional[str], optional
+ Chart title, by default None
+ x : Optional[str], optional
+ X-axis column, by default None
+ xtitle : Optional[str], optional
+ X-axis title, by default None
+ y : Optional[Union[str, List[str]]], optional
+ Y-axis column(s), by default None
+ If None are supplied, the layout is optimized for the contents of data.
+ Where many units/scales are present,
+ it will attempt to divide based on the range of values.
+ ytitle : Optional[str], optional
+ Y-axis title, by default None
+ y2 : Optional[Union[str, List[str]]], optional
+ Y2-axis column(s), by default None
+ y2title : Optional[str], optional
+ Y2-axis title, by default None
+ layout_kwargs : Optional[dict], optional
+ Additional Plotly Layout parameters for `fig.update_layout`, by default None
+ scatter_kwargs : Optional[dict], optional
+ Additional Plotly parameters applied on creation of each scatter plot, by default None
+ normalize : bool, optional
+ Normalize the data with Z-Score Standardization, by default False
+ returns : bool, optional
+ Convert the data to cumulative returns, by default False
+ same_axis: bool, optional
+ If True, forces all data onto the same Y-axis, by default False
+ render: bool, optional
+ If True, the chart will be rendered, by default True
+ **kwargs: Dict[str, Any]
+ Extra parameters to be passed to `figure.show()`
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.charts.generic_charts import line_chart
+
+ fig = line_chart(
+ data=data,
+ index=index,
+ target=target,
+ title=title,
+ x=x,
+ xtitle=xtitle,
+ y=y,
+ ytitle=ytitle,
+ y2=y2,
+ y2title=y2title,
+ layout_kwargs=layout_kwargs,
+ scatter_kwargs=scatter_kwargs,
+ normalize=normalize,
+ returns=returns,
+ same_axis=same_axis,
+ **kwargs,
+ )
+ fig = self._set_chart_style(fig)
+ if render:
+ return fig.show(**kwargs)
+
+ return fig
+
+ def create_bar_chart(
+ self,
+ data: Union[
+ list,
+ dict,
+ "DataFrame",
+ List["DataFrame"],
+ "Series",
+ List["Series"],
+ "ndarray",
+ Data,
+ ],
+ x: str,
+ y: Union[str, List[str]],
+ barmode: Literal["group", "stack", "relative", "overlay"] = "group",
+ xtype: Literal[
+ "category", "multicategory", "date", "log", "linear"
+ ] = "category",
+ title: Optional[str] = None,
+ xtitle: Optional[str] = None,
+ ytitle: Optional[str] = None,
+ orientation: Literal["h", "v"] = "v",
+ colors: Optional[List[str]] = None,
+ layout_kwargs: Optional[Dict[str, Any]] = None,
+ bar_kwargs: Optional[Dict[str, Any]] = None,
+ render: bool = True,
+ **kwargs,
+ ) -> Union["OpenBBFigure", "Figure", None]:
+ """Create a bar chart on a single x-axis with one or more values for the y-axis.
+
+ Parameters
+ ----------
+ data : Union[list, dict, DataFrame, List[DataFrame], Series, List[Series], ndarray, Data]
+ Data to plot.
+ x : str
+ The x-axis column name.
+ y : Union[str, List[str]]
+ The y-axis column name(s).
+ barmode : Literal["group", "stack", "relative", "overlay"], optional
+ The bar mode, by default "group".
+ xtype : Literal["category", "multicategory", "date", "log", "linear"], optional
+ The x-axis type, by default "category".
+ title : str, optional
+ The title of the chart, by default None.
+ xtitle : str, optional
+ The x-axis title, by default None.
+ ytitle : str, optional
+ The y-axis title, by default None.
+ colors: List[str], optional
+ Manually set the colors to cycle through for each column in 'y', by default None.
+ bar_kwargs : Dict[str, Any], optional
+ Additional keyword arguments to apply with figure.add_bar(), by default None.
+ layout_kwargs : Dict[str, Any], optional
+ Additional keyword arguments to apply with figure.update_layout(), by default None.
+ Returns
+ -------
+ OpenBBFigure
+ The OpenBBFigure object.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.charts.generic_charts import bar_chart
+
+ fig = bar_chart(
+ data=data,
+ x=x,
+ y=y,
+ barmode=barmode,
+ xtype=xtype,
+ title=title,
+ xtitle=xtitle,
+ ytitle=ytitle,
+ orientation=orientation,
+ colors=colors,
+ bar_kwargs=bar_kwargs,
+ layout_kwargs=layout_kwargs,
+ )
+ fig = self._set_chart_style(fig)
+ if render:
+ return fig.show(**kwargs)
+
+ return fig
+
+ def create_correlation_matrix(
+ self,
+ data: Union[
+ list[Data],
+ "DataFrame",
+ ],
+ method: Literal["pearson", "kendall", "spearman"] = "pearson",
+ colorscale: str = "RdBu",
+ title: str = "Asset Correlation Matrix",
+ layout_kwargs: Optional[Dict[str, Any]] = None,
+ ):
+ """Create a correlation matrix from external data.
+
+ Parameters
+ ----------
+ data : Union[list[Data], DataFrame]
+ Input dataset.
+ method : Literal["pearson", "kendall", "spearman"]
+ Method to use for correlation calculation. Default is "pearson".
+ pearson : standard correlation coefficient
+ kendall : Kendall Tau correlation coefficient
+ spearman : Spearman rank correlation
+ colorscale : str
+ Plotly colorscale to use for the heatmap. Default is "RdBu".
+ title : str
+ Title of the chart. Default is "Asset Correlation Matrix".
+ layout_kwargs : Dict[str, Any]
+ Additional keyword arguments to apply with figure.update_layout(), by default None.
+
+ Returns
+ -------
+ OpenBBFigure
+ The OpenBBFigure object.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.charts.correlation_matrix import correlation_matrix
+
+ kwargs = {
+ "data": data,
+ "method": method,
+ "colorscale": colorscale,
+ "title": title,
+ "layout_kwargs": layout_kwargs,
+ }
+ fig, _ = correlation_matrix(**kwargs)
+ fig = self._set_chart_style(fig)
+ return fig
+
+ # pylint: disable=inconsistent-return-statements
+ def show(self, render: bool = True, **kwargs):
+ """Display chart and save it to the OBBject."""
+ try:
+ charting_function = self._get_chart_function(
+ self._obbject._route # pylint: disable=protected-access
+ )
+ kwargs["obbject_item"] = self._obbject.results
+ kwargs["charting_settings"] = self._charting_settings
+ kwargs["standard_params"] = (
+ self._obbject._standard_params # pylint: disable=protected-access
+ )
+ kwargs["extra_params"] = (
+ self._obbject._extra_params # pylint: disable=protected-access
+ )
+ kwargs["provider"] = self._obbject.provider
+ kwargs["extra"] = self._obbject.extra
+ fig, content = charting_function(**kwargs)
+ fig = self._set_chart_style(fig)
+ content = fig.show(external=True, **kwargs).to_plotly_json()
+ self._obbject.chart = Chart(fig=fig, content=content, format=self._format)
+ if render:
+ fig.show(**kwargs)
+ except Exception: # pylint: disable=W0718
+ try:
+ fig = self.create_line_chart(data=self._obbject.results, render=False, **kwargs) # type: ignore
+ fig = self._set_chart_style(fig)
+ content = fig.show(external=True, **kwargs).to_plotly_json() # type: ignore
+ self._obbject.chart = Chart(
+ fig=fig, content=content, format=self._format
+ )
+ if render:
+ return fig.show(**kwargs) # type: ignore
+ except Exception as e:
+ raise RuntimeError(
+ "Failed to automatically create a generic chart with the data provided."
+ ) from e
+
+ # pylint: disable=too-many-locals,inconsistent-return-statements
+ def to_chart(
+ self,
+ data: Optional[
+ Union[
+ list,
+ dict,
+ "DataFrame",
+ List["DataFrame"],
+ "Series",
+ List["Series"],
+ "ndarray",
+ Data,
+ ]
+ ] = None,
+ target: Optional[str] = None,
+ index: Optional[str] = None,
+ indicators: Optional[Dict[str, Dict[str, Any]]] = None,
+ symbol: str = "",
+ candles: bool = True,
+ volume: bool = True,
+ volume_ticks_x: int = 7,
+ render: bool = True,
+ **kwargs,
+ ):
+ """Create an OpenBBFigure with user customizations (if any) and save it to the OBBject.
+
+ This function is used to populate, or re-populate, the OBBject with a chart using the data within
+ the OBBject or external data supplied via the `data` parameter.
+ This function modifies the original OBBject by overwriting the existing chart.
+
+ Parameters
+ ----------
+ data : Union[Data, DataFrame, Series]
+ Data to be plotted.
+ indicators : Dict[str, Dict[str, Any]], optional
+ Indicators to be plotted, by default None
+ symbol : str, optional
+ Symbol to be plotted. This is used for labels and titles, by default ""
+ candles : bool, optional
+ If True, candles will be plotted, by default True
+ volume : bool, optional
+ If True, volume will be plotted, by default True
+ volume_ticks_x : int, optional
+ Volume ticks, by default 7
+ render : bool, optional
+ If True, the chart will be rendered, by default True
+ kwargs: Dict[str, Any]
+ Extra parameters to be passed to the chart constructor.
+
+ Examples
+ --------
+ Plotting a time series with TA indicators
+
+ >>> from openbb import obb
+ >>> res = obb.equity.price.historical("AAPL")
+ >>> indicators = dict(
+ >>> sma=dict(length=[20,30,50]),
+ >>> adx=dict(length=14),
+ >>> rsi=dict(length=14),
+ >>> macd=dict(fast=12, slow=26, signal=9),
+ >>> bbands=dict(length=20, std=2),
+ >>> stoch=dict(length=14),
+ >>> ema=dict(length=[20,30,50]),
+ >>> )
+ >>> res.charting.to_chart(**{"indicators": indicators})
+
+ Get all the available indicators
+
+ >>> res = obb.equity.price.historical("AAPL")
+ >>> indicators = res.charting.indicators()
+ >>> indicators?
+ """
+ data_as_df, has_data = self._prepare_data_as_df(data) # type: ignore
+ if target is not None:
+ data_as_df = data_as_df[[target]]
+ kwargs["candles"] = candles
+ kwargs["volume"] = volume
+ kwargs["volume_ticks_x"] = volume_ticks_x
+ kwargs["indicators"] = indicators if indicators else {}
+ kwargs["symbol"] = symbol
+ kwargs["target"] = target
+ kwargs["index"] = index
+ kwargs["obbject_item"] = self._obbject.results
+ kwargs["charting_settings"] = self._charting_settings
+ kwargs["standard_params"] = (
+ self._obbject._standard_params # pylint: disable=protected-access
+ )
+ kwargs["extra_params"] = (
+ self._obbject._extra_params # pylint: disable=protected-access
+ )
+ kwargs["provider"] = self._obbject.provider # pylint: disable=protected-access
+ kwargs["extra"] = self._obbject.extra # pylint: disable=protected-access
+ try:
+ if has_data:
+ self.show(data=data_as_df, render=render, **kwargs)
+ else:
+ self.show(**kwargs, render=render)
+ except Exception: # pylint: disable=W0718
+ try:
+ fig = self.create_line_chart(data=data_as_df, render=False, **kwargs)
+ fig = self._set_chart_style(fig)
+ content = fig.show(external=True, **kwargs).to_plotly_json() # type: ignore
+ self._obbject.chart = Chart(
+ fig=fig, content=content, format=self._format
+ )
+ if render:
+ return fig.show(**kwargs) # type: ignore
+ except Exception as e: # pylint: disable=W0718
+ raise RuntimeError(
+ "Failed to automatically create a generic chart with the data provided."
+ ) from e
+
+ def _set_chart_style(self, figure: "Figure"):
+ """Set the user preference for light or dark mode."""
+ style = self._charting_settings.chart_style
+ font_color = "black" if style == "light" else "white"
+ paper_bgcolor = "white" if style == "light" else "black"
+ figure = figure.update_layout(
+ dict( # pylint: disable=R1735
+ font_color=font_color, paper_bgcolor=paper_bgcolor
+ )
+ )
+ return figure
+
+ def toggle_chart_style(self):
+ """Toggle the chart style between light and dark mode."""
+ if not hasattr(self._obbject.chart, "fig"):
+ raise ValueError(
+ "Error: No chart has been created. Please create a chart first."
+ )
+ current = self._charting_settings.chart_style
+ new = "light" if current == "dark" else "dark"
+ self._charting_settings.chart_style = new
+ figure = self._obbject.chart.fig # type: ignore[union-attr]
+ updated_figure = self._set_chart_style(figure)
+ self._obbject.chart.fig = updated_figure # type: ignore[union-attr]
+ self._obbject.chart.content = updated_figure.show( # type: ignore[union-attr]
+ external=True
+ ).to_plotly_json()
+
+ @staticmethod
+ def _convert_to_string(x):
+ """Sanitize the data for the table."""
+ # pylint: disable=import-outside-toplevel
+ from numpy import isnan
+
+ if isinstance(x, (float, int)) and not isnan(x):
+ return x
+ if isinstance(x, dict):
+ return ", ".join([str(v) for v in x.values()])
+ if isinstance(x, list):
+ if all(isinstance(i, dict) for i in x):
+ return ", ".join(
+ str(", ".join([str(v) for v in i.values()])) for i in x
+ )
+ return ", ".join([str(i) for i in x])
+
+ return (
+ str(x)
+ .replace("[", "")
+ .replace("]", "")
+ .replace("'{", "")
+ .replace("}'", "")
+ .replace("nan", "")
+ )
+
+ def table(
+ self,
+ data: Optional[Union["DataFrame", "Series"]] = None,
+ title: str = "",
+ ):
+ """Display an interactive table.
+
+ Parameters
+ ----------
+ data : Optional[Union[DataFrame, Series]], optional
+ Data to be plotted, by default None.
+ If no data is provided the OBBject results will be used.
+ title : str, optional
+ Title of the table, by default "".
+ """
+ # pylint: disable=import-outside-toplevel
+ from pandas import RangeIndex
+
+ data_as_df, _ = self._prepare_data_as_df(data)
+ if isinstance(data_as_df.index, RangeIndex):
+ data_as_df.reset_index(inplace=True, drop=True)
+ else:
+ data_as_df.reset_index(inplace=True)
+ for col in data_as_df.columns:
+ data_as_df[col] = data_as_df[col].apply(self._convert_to_string)
+ if self._backend.isatty:
+ try:
+ self._backend.send_table(
+ df_table=data_as_df,
+ title=title
+ or self._obbject._route, # pylint: disable=protected-access
+ theme=self._charting_settings.table_style,
+ )
+ except Exception as e: # pylint: disable=W0718
+ warn(f"Failed to show figure with backend. {e}")
+
+ else:
+ from plotly import optional_imports
+
+ ipython_display = optional_imports.get_module("IPython.display")
+ if ipython_display:
+ ipython_display.display(ipython_display.HTML(data_as_df.to_html()))
+ else:
+ warn("IPython.display is not available.")
+
+ def url(
+ self,
+ url: str,
+ title: str = "",
+ width: Optional[int] = None,
+ height: Optional[int] = None,
+ ):
+ """Return the URL of the chart."""
+ try:
+ self._backend.send_url(url=url, title=title, width=width, height=height)
+ except Exception as e: # pylint: disable=W0718
+ warn(f"Failed to show figure with backend. {e}")
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/__init__.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..cdba7aca0feaa5f29fb351f97298121cafe8ffb6
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/__init__.py
@@ -0,0 +1 @@
+"""OpenBB Charting utils."""
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/correlation_matrix.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/correlation_matrix.py
new file mode 100644
index 0000000000000000000000000000000000000000..6321f263e04cd98c92349787e1c1ab97fc7c2ddf
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/correlation_matrix.py
@@ -0,0 +1,119 @@
+"""Correlation Matrix Chart."""
+
+from typing import TYPE_CHECKING, Any, Union
+
+if TYPE_CHECKING:
+ from plotly.graph_objs import Figure # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+
+
+def correlation_matrix( # noqa: PLR0912
+ **kwargs,
+) -> tuple[Union["OpenBBFigure", "Figure"], dict[str, Any]]:
+ """Correlation Matrix Chart."""
+ # pylint: disable=import-outside-toplevel
+ from numpy import ones_like, triu # noqa
+ from openbb_core.app.utils import basemodel_to_df # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure
+ from openbb_charting.core.chart_style import ChartStyle
+ from plotly.graph_objs import Figure, Heatmap, Layout
+ from pandas import DataFrame
+
+ if "data" in kwargs and isinstance(kwargs["data"], DataFrame):
+ corr = kwargs["data"]
+ elif "data" in kwargs and isinstance(kwargs["data"], list):
+ corr = basemodel_to_df(kwargs["data"], index=kwargs.get("index", "date")) # type: ignore
+ else:
+ corr = basemodel_to_df(
+ kwargs["obbject_item"], index=kwargs.get("index", "date") # type: ignore
+ )
+ if (
+ "symbol" in corr.columns
+ and len(corr.symbol.unique()) > 1
+ and "close" in corr.columns
+ ):
+ corr = corr.pivot(
+ columns="symbol",
+ values="close",
+ )
+
+ method = kwargs.get("method") or "pearson"
+ corr = corr.corr(method=method, numeric_only=True)
+
+ X = corr.columns.to_list()
+ x_replace = X[-1]
+ Y = X.copy()
+ y_replace = Y[0]
+ X = [x if x != x_replace else "" for x in X]
+ Y = [y if y != y_replace else "" for y in Y]
+ mask = triu(ones_like(corr, dtype=bool))
+ df = corr.mask(mask)
+ title = kwargs.get("title") or "Asset Correlation Matrix"
+ text_color = "white" if ChartStyle().plt_style == "dark" else "black"
+ colorscale = kwargs.get("colorscale") or "RdBu"
+
+ heatmap = Heatmap(
+ z=df,
+ x=X,
+ y=Y,
+ xgap=1,
+ ygap=1,
+ colorscale=colorscale,
+ colorbar=dict(
+ orientation="v",
+ x=0.8,
+ y=0.5,
+ xanchor="left",
+ yanchor="middle",
+ xref="container",
+ yref="paper",
+ len=0.66,
+ bgcolor="rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)",
+ ),
+ text=df.fillna(""),
+ texttemplate="%{text:.4f}",
+ hoverongaps=False,
+ hovertemplate="%{x} - %{y} : %{z:.4f}",
+ )
+ layout = Layout(
+ title=title,
+ title_x=0.5,
+ xaxis=dict(
+ showgrid=False,
+ showline=False,
+ ticklen=0,
+ domain=[0.03, 1],
+ tickangle=90,
+ automargin=False,
+ ),
+ yaxis=dict(
+ showgrid=False,
+ side="left",
+ autorange="reversed",
+ showline=False,
+ ticklen=0,
+ automargin="height+width+left",
+ tickmode="auto",
+ ),
+ margin=dict(l=10, r=0, t=0, b=10),
+ dragmode="pan",
+ )
+ fig = Figure(data=[heatmap], layout=layout)
+ figure = OpenBBFigure(fig=fig)
+ figure.update_layout(
+ font=dict(color=text_color),
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ )
+ layout_kwargs = kwargs.get("layout_kwargs", {})
+
+ if layout_kwargs:
+ figure.update_layout(**layout_kwargs)
+
+ content = figure.show(external=True).to_plotly_json() # type: ignore
+
+ return figure, content
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/generic_charts.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/generic_charts.py
new file mode 100644
index 0000000000000000000000000000000000000000..003a557f33102318ad39499db04589274872d3c0
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/generic_charts.py
@@ -0,0 +1,654 @@
+"""Generic Charts Module."""
+
+# pylint: disable=too-many-arguments,unused-argument,too-many-locals, too-many-branches, too-many-lines, too-many-statements, use-dict-literal, broad-exception-caught, too-many-nested-blocks, too-many-positional-arguments
+
+from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union
+
+from openbb_core.app.utils import basemodel_to_df, convert_to_basemodel
+from openbb_core.provider.abstract.data import Data
+
+from openbb_charting.charts.helpers import (
+ calculate_returns,
+ should_share_axis,
+ z_score_standardization,
+)
+from openbb_charting.core.chart_style import ChartStyle
+from openbb_charting.styles.colors import LARGE_CYCLER
+
+if TYPE_CHECKING:
+ from numpy import ndarray # noqa
+ from pandas import DataFrame, Series # noqa
+ from plotly.graph_objs import Figure # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+
+
+def line_chart( # noqa: PLR0912
+ data: Union[
+ list,
+ dict,
+ "DataFrame",
+ List["DataFrame"],
+ "Series",
+ List["Series"],
+ "ndarray",
+ Data,
+ ],
+ index: Optional[str] = None,
+ target: Optional[str] = None,
+ title: Optional[str] = None,
+ x: Optional[str] = None,
+ xtitle: Optional[str] = None,
+ y: Optional[Union[str, List[str]]] = None,
+ ytitle: Optional[str] = None,
+ y2: Optional[Union[str, List[str]]] = None,
+ y2title: Optional[str] = None,
+ layout_kwargs: Optional[dict] = None,
+ scatter_kwargs: Optional[dict] = None,
+ normalize: bool = False,
+ returns: bool = False,
+ same_axis: bool = False,
+ **kwargs,
+) -> Union["OpenBBFigure", "Figure"]:
+ """Create a line chart."""
+ # pylint: disable=import-outside-toplevel
+ from pandas import DataFrame, Series, to_datetime # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure
+
+ if data is None:
+ raise ValueError("Error: Data is a required field.")
+
+ auto_layout = False
+ index = (
+ data.index.name
+ if isinstance(data, (DataFrame, Series))
+ else index if index is not None else x if x is not None else "date"
+ )
+ df: DataFrame = (basemodel_to_df(convert_to_basemodel(data), index=index)).dropna(
+ how="all", axis=1
+ )
+
+ if df.index.name is None:
+ if "date" in df.columns:
+ df.date = df.date.apply(to_datetime)
+ df.set_index("date", inplace=True)
+ else:
+ found_index = False
+ for col in df.columns:
+ if df[col].dtype == "object":
+ try:
+ df[col] = df[col].apply(to_datetime)
+ index = df[col].name # type: ignore
+ df.set_index(col, inplace=True)
+ df.index.name = "date"
+ found_index = True
+ except Exception as _: # noqa: S112
+ continue
+ if found_index is True:
+ break
+ if found_index is False:
+ df.set_index(df.iloc[:, 0], inplace=True)
+
+ if "symbol" in df.columns and len(df.symbol.unique()) > 1:
+ df = df.pivot(columns="symbol", values=target if target else "close")
+
+ if "symbol" not in df.columns and target in df.columns:
+ df = df[[target]]
+
+ y = y.split(",") if isinstance(y, str) else y
+
+ if y is None or same_axis is True:
+ y = df.columns.to_list()
+ auto_layout = True
+
+ if same_axis is True:
+ auto_layout = False
+
+ if returns is True:
+ df = df.apply(calculate_returns)
+ auto_layout = False
+
+ if normalize is True:
+ df = df.apply(z_score_standardization)
+ auto_layout = False
+
+ if layout_kwargs is None:
+ layout_kwargs = {}
+
+ if scatter_kwargs is None:
+ scatter_kwargs = {}
+
+ try:
+ fig = OpenBBFigure()
+ except Exception as _:
+ fig = OpenBBFigure(create_backend=True)
+
+ fig.update_layout(ChartStyle().plotly_template.get("layout", {}))
+ text_color = "white" if ChartStyle().plt_style == "dark" else "black"
+ title = f"{title}" if title else ""
+ xtitle = xtitle if xtitle else ""
+ y1title = ytitle if ytitle else ""
+ y2title = y2title if y2title else ""
+ y2 = y2 if y2 else []
+ yaxis_num = 1
+ yaxis = f"y{yaxis_num}"
+ first_y = y[0] # type: ignore[index]
+ second_y = None
+ third_y = None
+ add_scatter = False
+
+ # Attempt to layout the chart automatically with multiple y-axis.
+ mode = scatter_kwargs.pop("mode", "lines")
+ hovertemplate = scatter_kwargs.pop("hovertemplate", None)
+
+ if auto_layout is True:
+ # Sort columns by the difference between the max and min values.
+ # This is to help determine which columns should share the same y-axis.
+ diff = df.max(numeric_only=True) - df.min(numeric_only=True)
+ sorted_columns = diff.sort_values(ascending=False).index
+ if sorted_columns is None or len(sorted_columns) == 0:
+ raise ValueError("Error: expected data with numeric values.")
+ df = df[sorted_columns]
+
+ for i, col in enumerate(df.columns):
+
+ if col in y: # type: ignore[operator]
+ hovertemplate = (
+ hovertemplate
+ if hovertemplate
+ else f"{df[col].name}: %{{y}}"
+ )
+ share_yaxis = should_share_axis(df, first_y, col, threshold=2.5)
+ if share_yaxis is True:
+ add_scatter = True
+ if share_yaxis is False:
+ yaxis_num = 2
+ yaxis = f"y{yaxis_num}"
+ if second_y is None:
+ second_y = col
+ add_scatter = True
+ if second_y is not None:
+ add_scatter = False
+ share_yaxis = should_share_axis(df, col, second_y, threshold=3)
+ if share_yaxis is True:
+ add_scatter = True
+ if share_yaxis is False:
+ yaxis_num = 3
+ yaxis = f"y{yaxis_num}"
+ third_y = col
+ add_scatter = True
+
+ if add_scatter is True:
+ fig = fig.add_scatter(
+ x=df.index,
+ y=df[col],
+ name=col,
+ mode=mode,
+ line=dict(width=1, color=LARGE_CYCLER[i % len(LARGE_CYCLER)]),
+ hovertemplate=hovertemplate,
+ hoverlabel=dict(font_size=10),
+ yaxis=yaxis,
+ **scatter_kwargs,
+ )
+
+ if auto_layout is False:
+ color = 0
+ for i, col in enumerate(y): # type: ignore[arg-type]
+ hovertemplate = (
+ hovertemplate
+ if hovertemplate
+ else f"{df[col].name}: %{{y}}"
+ )
+ fig = fig.add_scatter(
+ x=df.index,
+ y=df[col],
+ name=col,
+ mode=mode,
+ line=dict(width=1, color=LARGE_CYCLER[color]),
+ hovertemplate=hovertemplate,
+ hoverlabel=dict(font_size=10),
+ yaxis="y1",
+ **scatter_kwargs,
+ )
+ color += 1
+ if y2:
+ second_y = y2[0]
+ for i, col in enumerate(y2):
+ hovertemplate = (
+ hovertemplate
+ if hovertemplate
+ else f"{df[col].name}: %{{y}}"
+ )
+ fig = fig.add_scatter(
+ x=df.index,
+ y=df[col],
+ name=col,
+ mode=mode,
+ line=dict(width=1, color=LARGE_CYCLER[color]),
+ hovertemplate=hovertemplate,
+ hoverlabel=dict(font_size=10),
+ yaxis="y2",
+ **scatter_kwargs,
+ )
+ color += 1
+
+ if returns is True:
+ y1title = "Percent"
+ title = f"{title} - Cumulative Returns" if title else "Cumulative Returns"
+
+ if normalize is True:
+ y1title = "Z-Score"
+ title = f"{title} - Z-Score" if title else "Z-Score"
+
+ if not title and target is not None:
+ title = f"{target.replace('_', ' ').title()}"
+
+ fig.update_layout(
+ title=dict(text=title if title else None, x=0.5, font=dict(size=16)),
+ font=dict(color=text_color),
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ legend=dict(
+ orientation="v",
+ yanchor="top",
+ xanchor="right",
+ y=0.95,
+ x=-0.01,
+ xref="paper",
+ font=dict(size=12),
+ bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ ),
+ yaxis=(
+ dict(
+ ticklen=0,
+ side="right",
+ title=dict(
+ text=y1title if ytitle else None, standoff=30, font=dict(size=16)
+ ),
+ tickfont=dict(size=14),
+ anchor="x",
+ showgrid=True,
+ mirror=True,
+ showline=True,
+ zeroline=False,
+ gridcolor="rgba(128,128,128,0.25)",
+ )
+ ),
+ yaxis2=(
+ dict(
+ overlaying="y",
+ side="left",
+ ticklen=0,
+ showgrid=False,
+ showline=True,
+ zeroline=False,
+ mirror=True,
+ title=dict(
+ text=y2title if y2title else None, standoff=10, font=dict(size=16)
+ ),
+ tickfont=dict(size=14),
+ anchor="x",
+ )
+ ),
+ yaxis3=(
+ dict(
+ overlaying="y",
+ side="left",
+ ticklen=0,
+ position=0,
+ showgrid=False,
+ showline=False,
+ zeroline=False,
+ showticklabels=True,
+ mirror=False,
+ tickfont=dict(size=12, color="rgba(128,128,128,0.75)"),
+ anchor="free",
+ )
+ ),
+ xaxis=dict(
+ ticklen=0,
+ showgrid=True,
+ title=(
+ dict(text=xtitle, standoff=30, font=dict(size=16)) if xtitle else None
+ ),
+ zeroline=False,
+ showline=True,
+ mirror=True,
+ gridcolor="rgba(128,128,128,0.25)",
+ domain=[0.095, 0.95] if third_y else None,
+ ),
+ margin=dict(r=25, l=25) if normalize is False else None,
+ autosize=True,
+ dragmode="pan",
+ hovermode="x",
+ )
+
+ if df.index.name not in ("date", "timestamp"):
+ fig.update_xaxes(type="category")
+
+ if layout_kwargs:
+ fig.update_layout(
+ **layout_kwargs,
+ )
+
+ return fig
+
+
+def bar_chart( # noqa: PLR0912
+ data: Union[
+ list,
+ dict,
+ "DataFrame",
+ List["DataFrame"],
+ "Series",
+ List["Series"],
+ "ndarray",
+ Data,
+ ],
+ x: str,
+ y: Union[str, List[str]],
+ barmode: Literal["group", "stack", "relative", "overlay"] = "group",
+ xtype: Literal["category", "multicategory", "date", "log", "linear"] = "category",
+ title: Optional[str] = None,
+ xtitle: Optional[str] = None,
+ ytitle: Optional[str] = None,
+ orientation: Literal["h", "v"] = "v",
+ colors: Optional[List[str]] = None,
+ bar_kwargs: Optional[Dict[str, Any]] = None,
+ layout_kwargs: Optional[Dict[str, Any]] = None,
+ **kwargs,
+) -> Union["OpenBBFigure", "Figure"]:
+ """Create a vertical bar chart on a single x-axis with one or more values for the y-axis.
+
+ Parameters
+ ----------
+ data : Union[
+ list, dict, "DataFrame", List["DataFrame"], "Series", List["Series"], "ndarray", Data
+ ]
+ Data to plot.
+ x : str
+ The x-axis column name.
+ y : Union[str, List[str]]
+ The y-axis column name(s).
+ barmode : Literal["group", "stack", "relative", "overlay"], optional
+ The bar mode, by default "group".
+ xtype : Literal["category", "multicategory", "date", "log", "linear"], optional
+ The x-axis type, by default "category".
+ title : str, optional
+ The title of the chart, by default None.
+ xtitle : str, optional
+ The x-axis title, by default None.
+ ytitle : str, optional
+ The y-axis title, by default None.
+ colors: List[str], optional
+ Manually set the colors to cycle through for each column in 'y', by default None.
+ bar_kwargs : Dict[str, Any], optional
+ Additional keyword arguments to apply with figure.add_bar(), by default None.
+ layout_kwargs : Dict[str, Any], optional
+ Additional keyword arguments to apply with figure.update_layout(), by default None.
+
+ Returns
+ -------
+ OpenBBFigure
+ The OpenBBFigure object.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.core.openbb_figure import OpenBBFigure
+
+ try:
+ figure = OpenBBFigure()
+ except Exception as _:
+ figure = OpenBBFigure(create_backend=True)
+
+ figure = figure.create_subplots(
+ 1,
+ 1,
+ shared_xaxes=True,
+ vertical_spacing=0.06,
+ horizontal_spacing=0.01,
+ row_width=[1],
+ specs=[[{"secondary_y": True}]],
+ )
+
+ figure.update_layout(ChartStyle().plotly_template.get("layout", {}))
+ text_color = "white" if ChartStyle().plt_style == "dark" else "black"
+ if colors is not None:
+ figure.update_layout(colorway=colors)
+ if bar_kwargs is None:
+ bar_kwargs = {}
+ if isinstance(data, (Data, list, dict)):
+ data = basemodel_to_df(convert_to_basemodel(data), index=None)
+
+ bar_df = data.copy().set_index(x) # type: ignore
+ y = y.split(",") if isinstance(y, str) else y
+ hovertemplate = bar_kwargs.pop("hovertemplate", None)
+ width = bar_kwargs.pop("width", None)
+ for item in y:
+ figure.add_bar(
+ x=bar_df.index if orientation == "v" else bar_df[item],
+ y=bar_df[item] if orientation == "v" else bar_df.index,
+ name=bar_df[item].name,
+ showlegend=len(y) > 1,
+ legendgroup=bar_df[item].name,
+ orientation=orientation,
+ hovertemplate=(
+ hovertemplate
+ if hovertemplate
+ else (
+ "%{fullData.name}:%{y}"
+ if orientation == "v"
+ else "%{fullData.name}:%{x}"
+ )
+ ),
+ width=(
+ width
+ if width
+ else 0.95 / len(y) * 0.75 if barmode == "group" and len(y) > 1 else 0.95
+ ),
+ **bar_kwargs,
+ )
+
+ figure.update_layout(
+ title=dict(text=title if title else None, x=0.5, font=dict(size=16)),
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rbga(255,255,255,0)"
+ ),
+ legend=dict(
+ orientation="v",
+ yanchor="top",
+ xanchor="right",
+ y=0.95,
+ x=-0.01 if orientation == "v" else 1.01,
+ xref="paper",
+ font=dict(size=12),
+ bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ ),
+ xaxis=dict(
+ type=xtype,
+ title=dict(
+ text=xtitle if xtitle else None, standoff=30, font=dict(size=16)
+ ),
+ ticklen=0,
+ showgrid=orientation == "h",
+ tickfont=dict(size=12, family="sans-serif"),
+ categoryorder="array" if orientation == "v" else None,
+ categoryarray=bar_df.index if orientation == "v" else None,
+ ),
+ yaxis=dict(
+ title=dict(
+ text=ytitle if ytitle else None, standoff=30, font=dict(size=16)
+ ),
+ ticklen=0,
+ showgrid=orientation == "v",
+ tickfont=dict(size=12),
+ side="left" if orientation == "h" else "right",
+ categoryorder="array" if orientation == "h" else None,
+ categoryarray=bar_df.index if orientation == "h" else None,
+ ),
+ margin=dict(pad=5),
+ barmode=barmode,
+ font=dict(color=text_color),
+ )
+ if orientation == "h":
+ figure.update_layout(
+ xaxis=dict(
+ type="linear",
+ showspikes=False,
+ ),
+ yaxis=dict(
+ type="category",
+ showspikes=False,
+ ),
+ hoverlabel=dict(
+ font=dict(size=12),
+ ),
+ hovermode="y unified",
+ )
+ if layout_kwargs:
+ figure.update_layout(
+ **layout_kwargs,
+ )
+ return figure
+
+
+def bar_increasing_decreasing( # pylint: disable=W0102
+ keys: List[str],
+ values: List[Union[int, float]],
+ title: Optional[str] = None,
+ xtitle: Optional[str] = None,
+ ytitle: Optional[str] = None,
+ colors: List[str] = ["blue", "red"],
+ orientation: Literal["h", "v"] = "h",
+ barmode: Literal["group", "stack", "relative", "overlay"] = "relative",
+ layout_kwargs: Optional[Dict[str, Any]] = None,
+) -> Union["OpenBBFigure", "Figure"]:
+ """Create a bar chart with increasing and decreasing values represented by two colors.
+
+ Parameters
+ ----------
+ keys : List[str]
+ The x-axis keys.
+ values : List[Any]
+ The y-axis values.
+ title : Optional[str], optional
+ The title of the chart, by default None.
+ xtitle : Optional[str], optional
+ The x-axis title, by default None.
+ ytitle : Optional[str], optional
+ The y-axis title, by default None.
+ colors : List[str], optional
+ The colors to use for increasing and decreasing values, by default ["blue", "red"].
+ orientation : Literal["h", "v"], optional
+ The orientation of the bars, by default "h".
+ barmode : Literal["group", "stack", "relative", "overlay"], optional
+ The bar mode, by default "relative".
+ layout_kwargs : Optional[Dict[str, Any]], optional
+ Additional keyword arguments to apply with figure.update_layout(), by default None.
+
+ Returns
+ -------
+ OpenBBFigure
+ The OpenBBFigure object.
+ """
+ # pylint: disable=import-outside-toplevel
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+ from pandas import Series
+
+ try:
+ figure = OpenBBFigure()
+ except Exception as _:
+ figure = OpenBBFigure(create_backend=True)
+
+ figure = figure.create_subplots(
+ 1,
+ 1,
+ shared_xaxes=False,
+ vertical_spacing=0.06,
+ horizontal_spacing=0.01,
+ row_width=[1],
+ specs=[[{"secondary_y": True}]],
+ )
+ figure.update_layout(ChartStyle().plotly_template.get("layout", {}))
+ text_color = "white" if ChartStyle().plt_style == "dark" else "black"
+
+ try:
+ data = Series(data=values, index=keys)
+ increasing_data = data[data > 0] # type: ignore
+ decreasing_data = data[data < 0] # type: ignore
+ except Exception as e:
+ raise ValueError(f"Error: {e}") from e
+
+ if not increasing_data.empty:
+ figure.add_bar(
+ x=increasing_data.index if orientation == "v" else increasing_data,
+ y=increasing_data if orientation == "v" else increasing_data.index,
+ marker=dict(color=colors[0]),
+ orientation=orientation,
+ showlegend=False,
+ width=0.95 / len(keys) * 0.75 if barmode == "group" else 0.95,
+ hoverinfo="y" if orientation == "v" else "x",
+ )
+ if not decreasing_data.empty:
+ figure.add_bar(
+ x=decreasing_data.index if orientation == "v" else decreasing_data,
+ y=decreasing_data if orientation == "v" else decreasing_data.index,
+ marker=dict(color=colors[1]),
+ orientation=orientation,
+ showlegend=False,
+ width=0.95 / len(keys) * 0.75 if barmode == "group" else 0.95,
+ hoverinfo="y" if orientation == "v" else "x",
+ )
+
+ figure.update_layout(
+ title=dict(text=title if title else None, x=0.5, font=dict(size=20)),
+ hovermode="x" if orientation == "v" else "y",
+ hoverlabel=dict(align="left" if orientation == "h" else "auto"),
+ yaxis=dict(
+ title=dict(
+ text=ytitle if ytitle else None, standoff=30, font=dict(size=16)
+ ),
+ side="left" if orientation == "h" else "right",
+ showgrid=orientation == "v",
+ gridcolor="rgba(128,128,128,0.25)",
+ tickfont=dict(size=12),
+ ticklen=0,
+ categoryorder="array" if orientation == "h" else None,
+ categoryarray=keys if orientation == "h" else None,
+ ),
+ xaxis=dict(
+ title=dict(
+ text=xtitle if xtitle else None, standoff=30, font=dict(size=16)
+ ),
+ showgrid=orientation == "h",
+ gridcolor="rgba(128,128,128,0.25)",
+ tickfont=dict(size=12),
+ ticklen=0,
+ categoryorder="array" if orientation == "v" else None,
+ categoryarray=keys if orientation == "v" else None,
+ ),
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ font=dict(color="white" if text_color == "white" else "black"),
+ margin=dict(pad=5),
+ )
+
+ if layout_kwargs:
+ figure.update_layout(
+ **layout_kwargs,
+ )
+
+ return figure
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/helpers.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/helpers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff2737e9cf30ba21c6999625bd22d5619a20829c
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/helpers.py
@@ -0,0 +1,123 @@
+"""Helper functions for charting."""
+
+# pylint: disable=R0917
+
+from typing import TYPE_CHECKING, Callable, Dict, List, Type
+
+if TYPE_CHECKING:
+ from pandas import DataFrame, Series
+
+
+def get_charting_functions(view: Type) -> Dict[str, Callable]:
+ """Discover charting functions."""
+ # pylint: disable=import-outside-toplevel
+ from inspect import getmembers, getsource, isfunction
+
+ implemented_functions: Dict[str, Callable] = {}
+
+ for name, obj in getmembers(view, isfunction):
+ if (
+ obj.__module__ == view.__module__
+ and not name.startswith("_")
+ and "NotImplementedError" not in getsource(obj)
+ ):
+ implemented_functions[name] = obj
+
+ return implemented_functions
+
+
+def get_charting_functions_list(view: Type) -> List[str]:
+ """Get a list of all the charting functions."""
+ return list(get_charting_functions(view).keys())
+
+
+def z_score_standardization(data: "Series") -> "Series":
+ """Z-Score Standardization Method."""
+ return (data - data.mean()) / data.std()
+
+
+def calculate_returns(data: "Series") -> "Series":
+ """Calculate the returns of a column."""
+ return ((1 + data.pct_change(fill_method=None).fillna(0)).cumprod() - 1) * 100
+
+
+def should_share_axis(
+ df: "DataFrame", col1: str, col2: str, threshold: float = 0.15
+) -> bool:
+ """Determine whether two columns should share an axis."""
+ # pylint: disable=import-outside-toplevel
+ from pandas import Series
+
+ try:
+ if isinstance(df, Series):
+ df = df.to_frame()
+ range1 = df[col1].max() - df[col1].min()
+ range2 = df[col2].max() - df[col2].min()
+ # Calculate the ratio of the two ranges
+ ratio = max(range1, range2) / min(range1, range2)
+ # If the ratio is less than the threshold, the two columns can share an axis
+ if ratio == 1:
+ return True
+ return ratio < threshold
+ except Exception:
+ return False
+
+
+def heikin_ashi(data: "DataFrame") -> "DataFrame":
+ """Return OHLC data as Heikin Ashi Candles.
+
+ Parameters
+ ----------
+ data: DataFrame
+ DataFrame containing OHLC data.
+
+ Returns
+ -------
+ DataFrame
+ DataFrame copy with Heikin Ashi candle calculations.
+ """
+ # pylint: disable=import-outside-toplevel
+ from pandas_ta import candles
+
+ df = data.copy()
+
+ check_columns = ["open", "high", "low", "close"]
+
+ for item in check_columns:
+ if item not in df.columns:
+ raise ValueError(
+ "The expected column labels, "
+ f"{check_columns}"
+ ", were not found in DataFrame."
+ )
+
+ ha = candles.ha(
+ df["open"],
+ df["high"],
+ df["low"],
+ df["close"],
+ )
+
+ for item in check_columns:
+ df[item] = ha[f"HA_{item}"]
+
+ return df
+
+
+def duration_sorter(durations: list) -> list:
+ """Sort durations labeled as month_5, year_5, etc."""
+
+ def duration_to_months(duration):
+ """Convert duration to months."""
+ if duration == "long_term":
+ return 360
+ parts = duration.split("_")
+ months = 0
+ for i in range(0, len(parts), 2):
+ number = int(parts[i + 1])
+ if parts[i] == "year":
+ number *= 12 # Convert years to months
+ months += number
+ return months
+
+ return sorted(durations, key=duration_to_months)
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_historical.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_historical.py
new file mode 100644
index 0000000000000000000000000000000000000000..b7151845bab504b5297c6f8fc2dd3911a82b4ef9
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_historical.py
@@ -0,0 +1,335 @@
+"""Price historical charting utility."""
+
+# pylint: disable=too-many-branches, too-many-locals, unused-argument
+
+
+from typing import TYPE_CHECKING, Any, Dict, Tuple
+
+from openbb_charting.styles.colors import LARGE_CYCLER
+
+if TYPE_CHECKING:
+ from openbb_charting.core.openbb_figure import OpenBBFigure
+
+
+def price_historical( # noqa: PLR0912
+ **kwargs,
+) -> Tuple["OpenBBFigure", Dict[str, Any]]:
+ """Equity Price Historical Chart."""
+ # pylint: disable=import-outside-toplevel
+ from pandas import DataFrame # noqa
+ from openbb_core.app.utils import basemodel_to_df # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+ from openbb_charting.core.plotly_ta.ta_class import PlotlyTA # noqa
+ from openbb_charting.core.chart_style import ChartStyle # noqa
+ from openbb_charting.charts.helpers import ( # noqa
+ calculate_returns,
+ heikin_ashi,
+ should_share_axis,
+ z_score_standardization,
+ )
+
+ if "data" in kwargs and isinstance(kwargs["data"], DataFrame):
+ data = kwargs["data"]
+ elif "data" in kwargs and isinstance(kwargs["data"], list):
+ data = basemodel_to_df(kwargs["data"], index=kwargs.get("index", "date")) # type: ignore
+ else:
+ data = basemodel_to_df(
+ kwargs["obbject_item"], index=kwargs.get("index", "date") # type: ignore
+ )
+
+ if "date" in data.columns:
+ data = data.set_index("date")
+
+ target = str(kwargs.get("target"))
+ normalize = kwargs.get("normalize") is True
+ returns = kwargs.get("returns") is True
+ same_axis = kwargs.get("same_axis") is True
+ text_color = "black" if ChartStyle().plt_style == "light" else "white"
+ title = f"{kwargs.get('title')}" if "title" in kwargs else "Historical Prices"
+ y1title = ""
+ y2title = ""
+ candles = True
+ multi_symbol = (
+ bool(kwargs.get("multi_symbol") is True)
+ or (
+ "symbol" in data.columns
+ and target in data.columns
+ and len(data.symbol.unique()) > 1
+ )
+ or ("target" in kwargs and kwargs.get("target") is not None)
+ or "symbol" in data.columns
+ or (
+ "symbol" not in data.columns
+ and bool(data.columns.isin(["open", "high", "low", "close"]).all())
+ )
+ )
+ target = "close" if target is None or target == "None" or target == "" else target
+
+ if multi_symbol is True:
+ if "symbol" not in data.columns and target in data.columns:
+ data = data[[target]]
+ y1title = target.title()
+ if "symbol" in data.columns and target in data.columns:
+ data = data.pivot(columns="symbol", values=target)
+ y1title = target
+ title = f"Historical {target.title()}"
+
+ indicators = kwargs.get("indicators", {})
+ candles = bool(~data.columns.isin(["open", "high", "low", "close"]).all())
+ candles = candles if kwargs.get("candles", True) else False
+ volume = kwargs.get("volume", True) if "volume" in data.columns else False
+
+ if normalize is True:
+ if "symbol" not in data.columns and target in data.columns:
+ data = data[[target]]
+ multi_symbol = True
+ candles = False
+ volume = False
+
+ if returns is True:
+ if "symbol" not in data.columns and target in data.columns:
+ data = data[[target]]
+ multi_symbol = True
+ candles = False
+ volume = False
+ if ( # pylint: disable = R0916
+ multi_symbol is False
+ and normalize is False
+ and returns is False
+ and candles is True
+ ) or (indicators and multi_symbol is False):
+ if (
+ "heikin_ashi" in kwargs
+ and kwargs["heikin_ashi"] is True
+ and candles is True
+ ):
+ data = heikin_ashi(data)
+ title = f"{title} - Heikin Ashi"
+ _volume = False
+ if "atr" in indicators: # type: ignore
+ _volume = volume
+ volume = False
+ ta = PlotlyTA()
+ fig = ta.plot( # type: ignore
+ data,
+ indicators=indicators if indicators else {}, # type: ignore
+ symbol=target if candles is False else "",
+ candles=candles,
+ volume=volume, # type: ignore
+ )
+ if _volume is True and "atr" in indicators: # type: ignore
+ fig.add_inchart_volume(data)
+ fig.update_layout(
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ font=dict(color=text_color),
+ showlegend=True,
+ legend=dict(
+ orientation="v",
+ yanchor="top",
+ xanchor="right",
+ y=0.95,
+ x=-0.01,
+ xref="paper",
+ font=dict(size=12),
+ bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ ),
+ xaxis=dict(
+ ticklen=0,
+ showgrid=True,
+ gridcolor="rgba(128,128,128,0.3)",
+ zeroline=True,
+ mirror=True,
+ showline=True,
+ ),
+ xaxis2=dict(
+ ticklen=0,
+ showgrid=True,
+ gridcolor="rgba(128,128,128,0.3)",
+ zeroline=True,
+ mirror=True,
+ showline=True,
+ ),
+ yaxis=dict(
+ ticklen=0,
+ showgrid=True,
+ gridcolor="rgba(128,128,128,0.3)",
+ zeroline=True,
+ mirror=True,
+ showline=True,
+ tickfont=dict(size=14),
+ ),
+ yaxis2=dict(
+ ticklen=0,
+ gridcolor="rgba(128,128,128,0.3)",
+ ),
+ yaxis3=dict(
+ ticklen=0,
+ gridcolor="rgba(128,128,128,0.3)",
+ ),
+ dragmode="pan",
+ hovermode="x",
+ )
+
+ if kwargs.get("title"):
+ title = kwargs["title"]
+ fig.update_layout(title=dict(text=title, x=0.5))
+
+ content = fig.to_plotly_json()
+
+ return fig, content
+
+ if multi_symbol is True or candles is False:
+
+ if "symbol" not in data.columns and target in data.columns:
+ data = data[[target]]
+
+ if "symbol" in data.columns:
+ data = data.pivot(columns="symbol", values=target)
+
+ title: str = kwargs.get("title", "Historical Prices") # type: ignore
+
+ y1title = data.iloc[:, 0].name
+ y2title = ""
+
+ if len(data.columns) > 2 or normalize is True or returns is True:
+ if returns is True or (len(data.columns) > 2 and normalize is False):
+ data = data.apply(calculate_returns)
+ title = f"{title} - Cumulative Returns"
+ y1title = "Percent"
+ if normalize is True:
+ if returns is True:
+ title = f"{title.replace(' - Cumulative Returns', '')} - Normalized Cumulative Returns"
+ else:
+ title = title + " - Normalized"
+ data = data.apply(z_score_standardization)
+ y1title = None # type: ignore
+ y2title = None # type: ignore
+
+ fig = OpenBBFigure()
+ fig.update_layout(ChartStyle().plotly_template.get("layout", {}))
+ text_color = "white" if ChartStyle().plt_style == "dark" else "black"
+
+ for i, col in enumerate(data.columns):
+
+ hovertemplate = f"{data[col].name}: %{{y}}"
+ yaxis = "y1"
+ if y1title and y1title != "Percent":
+ yaxis = (
+ (
+ "y1"
+ if should_share_axis(data, col, y1title) # type: ignore
+ or col == y1title
+ or normalize is True
+ or returns is True
+ else "y2"
+ )
+ if same_axis is False
+ else "y1"
+ )
+
+ if yaxis == "y2":
+ y2title = data[col].name
+
+ fig.add_scatter(
+ x=data.index,
+ y=data[col],
+ name=data[col].name,
+ mode="lines",
+ hovertemplate=hovertemplate,
+ line=dict(width=2, color=LARGE_CYCLER[i % len(LARGE_CYCLER)]),
+ yaxis=yaxis,
+ )
+
+ if normalize is True or returns is True:
+ y1title = "Percent" if returns is True else None # type: ignore
+ y2title = None # type: ignore
+
+ if same_axis is True:
+ y1title = None # type: ignore
+ y2title = None # type: ignore
+
+ fig.update_layout(
+ paper_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ plot_bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ legend=(
+ dict(
+ orientation="v",
+ yanchor="top",
+ xanchor="right",
+ y=0.95,
+ x=-0.01,
+ bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ )
+ if len(data.columns) > 2
+ else dict(
+ orientation="h",
+ yanchor="bottom",
+ xanchor="right",
+ y=1.02,
+ x=0.98,
+ bgcolor=(
+ "rgba(0,0,0,0)" if text_color == "white" else "rgba(255,255,255,0)"
+ ),
+ )
+ ),
+ yaxis1=(
+ dict(
+ side="right",
+ ticklen=0,
+ showgrid=True,
+ showline=True,
+ mirror=True,
+ gridcolor="rgba(128,128,128,0.3)",
+ title=dict(
+ text=y1title if y1title else None, standoff=20, font=dict(size=20)
+ ),
+ tickfont=dict(size=14),
+ anchor="x",
+ )
+ ),
+ yaxis2=(
+ dict(
+ overlaying="y",
+ side="left",
+ ticklen=0,
+ showgrid=False,
+ title=dict(
+ text=y2title if y2title else None, standoff=10, font=dict(size=20)
+ ),
+ tickfont=dict(size=14),
+ anchor="x",
+ )
+ if y2title
+ else None
+ ),
+ xaxis=dict(
+ ticklen=0,
+ showgrid=True,
+ gridcolor="rgba(128,128,128,0.3)",
+ showline=True,
+ mirror=True,
+ ),
+ margin=dict(l=20, r=20, b=20, t=20),
+ dragmode="pan",
+ hovermode="x",
+ )
+ if kwargs.get("title"):
+ title = kwargs["title"]
+ fig.update_layout(title=dict(text=title, x=0.5))
+
+ content = fig.show(external=True).to_plotly_json()
+
+ return fig, content
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_performance.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_performance.py
new file mode 100644
index 0000000000000000000000000000000000000000..50b53136254066535d9049c4b3965645c63686d1
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/price_performance.py
@@ -0,0 +1,108 @@
+"""Price performance charting implementation."""
+
+from typing import TYPE_CHECKING, Any, Dict, Tuple, Union
+
+if TYPE_CHECKING:
+ from plotly.graph_objs import Figure # noqa
+ from openbb_charting.core.openbb_figure import OpenBBFigure # noqa
+
+
+def price_performance(
+ **kwargs,
+) -> Tuple[Union["OpenBBFigure", "Figure"], Dict[str, Any]]: # noqa: PLR0912
+ """Equity Price Performance Chart."""
+ # pylint: disable=import-outside-toplevel
+ from pandas import DataFrame # noqa
+ from openbb_core.app.utils import basemodel_to_df # noqa
+ from openbb_charting.charts.generic_charts import bar_chart # noqa
+
+ if "data" in kwargs and isinstance(kwargs["data"], DataFrame):
+ data = kwargs["data"]
+ elif "data" in kwargs and isinstance(kwargs["data"], list):
+ data = basemodel_to_df(kwargs["data"], index=kwargs.get("index", "symbol")) # type: ignore
+ else:
+ data = basemodel_to_df(
+ kwargs["obbject_item"], index=kwargs.get("index", "symbol") # type: ignore
+ )
+
+ cols = [
+ "one_day",
+ "one_week",
+ "one_month",
+ "three_month",
+ "six_month",
+ "ytd",
+ "one_year",
+ "two_year",
+ "three_year",
+ "four_year",
+ "five_year",
+ ]
+
+ df = DataFrame()
+ chart_df = DataFrame()
+
+ if "symbol" in data.columns:
+ data = data.set_index("symbol")
+ chart_cols = []
+
+ if len(data) == 0:
+ raise ValueError("No data was found in the DataFrame.")
+
+ data = data.drop_duplicates(keep="first")
+
+ for col in cols:
+ if col in data.columns and data[col].notnull().any():
+ df[col.replace("_", " ").title() if col != "ytd" else col.upper()] = data[
+ col
+ ].apply(lambda x: round(x * 100, 4) if x is not None else None)
+
+ if df.empty:
+ raise ValueError(f"No columns matching, {cols}, were found in the data.")
+
+ chart_df = df.T
+ chart_cols = chart_df.columns.to_list()
+
+ if "limit" in kwargs and isinstance(kwargs.get("limit"), int):
+ limit = kwargs.pop("limit", 10)
+ chart_df = chart_df.head(limit) # type: ignore
+
+ layout_kwargs: Dict[str, Any] = kwargs.get("layout_kwargs", {})
+
+ title = (
+ f"{kwargs.pop('title')}" if "title" in kwargs else "Equity Price Performance"
+ )
+ orientation = (
+ kwargs.pop("orientation")
+ if "orientation" in kwargs and kwargs.get("orientation") is not None
+ else "v"
+ )
+
+ ytitle = "Performance (%)"
+ xtitle = None
+
+ if orientation == "h":
+ xtitle = ytitle # type: ignore
+ ytitle = None # type: ignore
+
+ fig = bar_chart(
+ chart_df.reset_index(),
+ x="index",
+ y=chart_cols,
+ title=title,
+ xtitle=xtitle,
+ ytitle=ytitle,
+ orientation=orientation, # type: ignore
+ )
+ fig.update_traces(
+ hovertemplate=(
+ "%{fullData.name}:%{y:.2f}%"
+ if orientation == "v"
+ else "%{fullData.name}:%{x:.2f}%"
+ )
+ )
+
+ fig.update_layout(**layout_kwargs)
+ content = fig.show(external=True).to_plotly_json() # type: ignore
+
+ return fig, content
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/charts/relative_rotation.py b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/relative_rotation.py
new file mode 100644
index 0000000000000000000000000000000000000000..26df948957164bf56d74062315f82043b9faf004
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/charts/relative_rotation.py
@@ -0,0 +1,674 @@
+"""Relative Rotation Chart Helpers."""
+
+# pylint: disable=R0917
+
+from datetime import date as dateType
+from typing import TYPE_CHECKING, Literal, Optional
+from warnings import warn
+
+if TYPE_CHECKING:
+ from pandas import DataFrame
+ from plotly.graph_objects import Figure
+
+color_sequence = [
+ "burlywood",
+ "orange",
+ "grey",
+ "magenta",
+ "cyan",
+ "yellowgreen",
+ "#1f77b4",
+ "#aec7e8",
+ "#ff7f0e",
+ "#ffbb78",
+ "#d62728",
+ "#ff9896",
+ "#9467bd",
+ "#c5b0d5",
+ "#8c564b",
+ "#c49c94",
+ "#e377c2",
+ "#f7b6d2",
+ "#7f7f7f",
+ "#c7c7c7",
+ "#bcbd22",
+ "#dbdb8d",
+ "#17becf",
+ "#9edae5",
+ "#7e7e7e",
+ "#1b9e77",
+ "#d95f02",
+ "#7570b3",
+ "#e7298a",
+ "#66a61e",
+ "#e6ab02",
+ "#a6761d",
+ "#666666",
+ "#f0027f",
+ "#bf5b17",
+ "#d9f202",
+ "#8dd3c7",
+ "#ffffb3",
+ "#bebada",
+ "#fb8072",
+ "#80b1d3",
+ "#fdb462",
+ "#b3de69",
+ "#fccde5",
+ "#d9d9d9",
+ "#bc80bd",
+ "#ccebc5",
+ "#ffed6f",
+ "#6a3d9a",
+ "#b15928",
+ "#b2df8a",
+ "#33a02c",
+ "#fb9a99",
+ "#e31a1c",
+ "#fdbf6f",
+ "#ff7f00",
+ "#cab2d6",
+ "#6a3d9a",
+ "#ffff99",
+ "#b15928",
+]
+
+
+def create_rrg_with_tails(
+ ratios_data: "DataFrame",
+ momentum_data: "DataFrame",
+ study: str,
+ benchmark_symbol: str,
+ tail_periods: int,
+ tail_interval: Literal["day", "week", "month"],
+) -> "Figure":
+ """Create The Relative Rotation Graph With Tails.
+
+ Parameters
+ ----------
+ ratios_data : DataFrame
+ The DataFrame containing the RS-Ratio values.
+ momentum_data : DataFrame
+ The DataFrame containing the RS-Momentum values.
+ study : str
+ The study that was selected when loading the raw data.
+ If custom data is supplied, this will override the study for the chart titles.
+ benchmark_symbol : str
+ The symbol of the benchmark.
+ tail_periods : int
+ The number of periods to display in the tails.
+ tail_interval : Literal["day", "week", "month"]
+
+ Returns
+ -------
+ Figure
+ Plotly GraphObjects Figure.
+ """
+ # pylint: disable=import-outside-toplevel
+ from pandas import to_datetime
+ from plotly import graph_objects as go
+
+ symbols = ratios_data.columns.to_list()
+
+ tail_dict = {"week": "W", "month": "ME"}
+ ratios_data.index = to_datetime(ratios_data.index)
+ momentum_data.index = to_datetime(momentum_data.index)
+
+ if tail_interval != "day":
+ ratios_data = ratios_data.resample(tail_dict[tail_interval]).last()
+ momentum_data = momentum_data.resample(tail_dict[tail_interval]).last()
+ ratios_data = ratios_data.iloc[-tail_periods:]
+ momentum_data = momentum_data.iloc[-tail_periods:]
+ _tail_periods = len(ratios_data)
+ tail_title = (
+ f"The Previous {_tail_periods} {tail_interval.capitalize()}s "
+ f"Ending {ratios_data.index[-1].strftime('%Y-%m-%d')}"
+ )
+ x_min = ratios_data.min().min()
+ x_max = ratios_data.max().max()
+ y_min = momentum_data.min().min()
+ y_max = momentum_data.max().max()
+ # Create an empty list to store the scatter traces
+ frames: list = []
+ x_data = ratios_data
+ y_data = momentum_data
+ for i, date in enumerate(ratios_data.index): # pylint: disable=unused-variable
+
+ frame_data: list = []
+
+ for j, symbol in enumerate(symbols):
+ x_frame_data = x_data[symbol].iloc[: i + 1]
+ y_frame_data = y_data[symbol].iloc[: i + 1]
+ name = symbol.upper().replace("^", "").replace(":US", "")
+ special_name = "-" in name or len(name) > 7
+ marker_size = 34 if special_name else 30
+ line_frame_trace = go.Scatter(
+ x=x_frame_data,
+ y=y_frame_data,
+ mode="markers+lines",
+ line=dict(color=color_sequence[j], width=2, dash="dash"),
+ marker=dict(
+ size=5, color=color_sequence[j], line=dict(color="black", width=1)
+ ),
+ showlegend=False,
+ opacity=0.3,
+ name=name,
+ text=name,
+ hovertemplate="%{fullData.name}: "
+ + "RS-Ratio: %{x:.4f}, "
+ + "RS-Momentum: %{y:.4f}"
+ + "",
+ hoverlabel=dict(font_size=10),
+ )
+
+ marker_frame_trace = go.Scatter(
+ x=[x_frame_data.iloc[-1]],
+ y=[y_frame_data.iloc[-1]],
+ mode="markers+text",
+ name=name,
+ text=name,
+ textposition="middle center",
+ textfont=(
+ dict(size=10, color="black")
+ if len(symbol) < 4
+ else dict(size=7, color="black")
+ ),
+ line=dict(color=color_sequence[j], width=2, dash="dash"),
+ marker=dict(
+ size=marker_size,
+ color=color_sequence[j],
+ line=dict(color="black", width=1),
+ ),
+ opacity=0.9,
+ showlegend=False,
+ hovertemplate="%{fullData.name}: RS-Ratio: %{x:.4f}, RS-Momentum: %{y:.4f}",
+ )
+
+ frame_data.extend([line_frame_trace, marker_frame_trace])
+
+ frames.append(go.Frame(data=frame_data, name=f"Frame {i}"))
+
+ # Define the initial trace for the figure
+ initial_trace = frames[0]["data"]
+
+ padding = 0.1
+ y_range = [y_min - padding * abs(y_min) - 0.3, y_max + padding * abs(y_max) + 0.3]
+ x_range = [x_min - padding * abs(x_min) - 0.3, x_max + padding * abs(x_max) + 0.3]
+
+ # Create the layout for the figure
+ layout = go.Layout(
+ title={
+ "text": (
+ f"Relative Rotation Against {benchmark_symbol.replace('^', '')} {study.capitalize()} For {tail_title}"
+ ),
+ "x": 0.5,
+ "xanchor": "center",
+ "font": dict(size=18),
+ },
+ xaxis=dict(
+ title=dict(text="RS-Ratio", font=dict(size=16)),
+ showgrid=True,
+ zeroline=True,
+ showline=True,
+ mirror=True,
+ ticklen=0,
+ zerolinecolor="black",
+ range=x_range,
+ gridcolor="lightgrey",
+ showspikes=False,
+ ),
+ yaxis=dict(
+ title=dict(text="RS-Momentum", font=dict(size=16)),
+ showgrid=True,
+ zeroline=True,
+ showline=True,
+ mirror=True,
+ ticklen=0,
+ zerolinecolor="black",
+ range=y_range,
+ gridcolor="lightgrey",
+ side="left",
+ title_standoff=5,
+ ),
+ plot_bgcolor="rgba(255,255,255,1)",
+ shapes=[
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=0,
+ y0=0,
+ x1=x_range[1],
+ y1=y_range[1],
+ fillcolor="lightgreen",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=0,
+ x1=0,
+ y1=y_range[1],
+ fillcolor="lightblue",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=y_range[0],
+ x1=0,
+ y1=0,
+ fillcolor="lightpink",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=0,
+ y0=y_range[0],
+ x1=x_range[1],
+ y1=0,
+ fillcolor="lightyellow",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=y_range[0],
+ x1=x_range[1],
+ y1=y_range[1],
+ line=dict(
+ color="Black",
+ width=1,
+ ),
+ fillcolor="rgba(0,0,0,0)",
+ layer="above",
+ ),
+ ],
+ annotations=[
+ go.layout.Annotation(
+ x=1,
+ xref="paper",
+ y=1,
+ yref="paper",
+ text="Leading",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="darkgreen",
+ ),
+ ),
+ go.layout.Annotation(
+ x=1,
+ xref="paper",
+ y=0,
+ yref="paper",
+ text="Weakening",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="goldenrod",
+ ),
+ ),
+ go.layout.Annotation(
+ x=0,
+ xref="paper",
+ y=0,
+ yref="paper",
+ text="Lagging",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="red",
+ ),
+ ),
+ go.layout.Annotation(
+ x=0,
+ xref="paper",
+ yref="paper",
+ y=1,
+ text="Improving",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="blue",
+ ),
+ ),
+ ],
+ autosize=True,
+ margin=dict(
+ l=30,
+ r=50,
+ b=50,
+ t=50,
+ pad=0,
+ ),
+ dragmode="pan",
+ hovermode="closest",
+ updatemenus=[
+ {
+ "buttons": [
+ {
+ "args": [
+ None,
+ {
+ "frame": {"duration": 500, "redraw": False},
+ "fromcurrent": True,
+ "transition": {"duration": 500, "easing": "linear"},
+ },
+ ],
+ "label": "Play",
+ "method": "animate",
+ }
+ ],
+ "direction": "left",
+ "pad": {"r": 0, "t": 75},
+ "showactive": False,
+ "type": "buttons",
+ "x": -0.025,
+ "xanchor": "left",
+ "y": 0,
+ "yanchor": "top",
+ "bgcolor": "rgba(150, 150, 150, 0.8)",
+ "bordercolor": "rgba(100, 100, 100, 0.5)",
+ "borderwidth": 1,
+ "font": {"color": "black"},
+ }
+ ],
+ sliders=[
+ {
+ "active": 0,
+ "yanchor": "top",
+ "xanchor": "center",
+ "currentvalue": {
+ "font": {"size": 16},
+ "prefix": "Date: ",
+ "visible": True,
+ "xanchor": "right",
+ },
+ "transition": {"duration": 300, "easing": "cubic-in-out"},
+ "pad": {"b": 10, "t": 50},
+ "len": 0.9,
+ "x": 0.5,
+ "y": 0,
+ "steps": [
+ {
+ "label": f"{x_data.index[i].strftime('%Y-%m-%d')}",
+ "method": "animate",
+ "args": [
+ [f"Frame {i}"],
+ {
+ "mode": "immediate",
+ "transition": {"duration": 300},
+ "frame": {"duration": 300, "redraw": False},
+ },
+ ],
+ }
+ for i in range(len(x_data.index))
+ ],
+ }
+ ],
+ )
+
+ # Create the figure and add the initial trace
+ fig = go.Figure(data=initial_trace, layout=layout, frames=frames)
+
+ return fig
+
+
+def create_rrg_without_tails(
+ ratios_data: "DataFrame",
+ momentum_data: "DataFrame",
+ benchmark_symbol: str,
+ study: str,
+ date: Optional[dateType] = None,
+) -> "Figure":
+ """Create the Plotly Figure Object without Tails.
+
+ Parameters
+ ----------
+ ratios_data : DataFrame
+ The DataFrame containing the RS-Ratio values.
+ momentum_data : DataFrame
+ The DataFrame containing the RS-Momentum values.
+ benchmark_symbol : str
+ The symbol of the benchmark.
+ study: str
+ The study that was selected when loading the raw data.
+ If custom data is supplied, this will override the study for the chart titles.
+ date : Optional[dateType], optional
+ A specific date within the data to target for display, by default None.
+
+ Returns
+ -------
+ Figure
+ Plotly GraphObjects Figure.
+ """
+ # pylint: disable=import-outside-toplevel
+ from plotly import graph_objects as go # noqa
+ from pandas import to_datetime # noqa
+
+ if date is not None and date not in ratios_data.index.astype(str):
+ warn(f"Date {str(date)} not found in data, using the last available date.")
+ date = ratios_data.index[-1]
+ if date is None:
+ date = ratios_data.index[-1]
+
+ # Select a single row from each dataframe
+ row_x = ratios_data.loc[to_datetime(date).date()] # type: ignore
+ row_y = momentum_data.loc[to_datetime(date).date()] # type: ignore
+
+ x_max = row_x.max() + 0.5
+ x_min = row_x.min() - 0.5
+ y_max = row_y.max() + 0.5
+ y_min = row_y.min() - 0.5
+
+ # Create an empty list to store the scatter traces
+ traces = []
+
+ # Loop through each column in the row_x dataframe
+ for i, (column_name, value_x) in enumerate(row_x.items()):
+ # Retrieve the corresponding value from the row_y dataframe
+ value_y = row_y[column_name] # type: ignore
+ marker_name = column_name.upper().replace("^", "").replace(":US", "") # type: ignore
+ special_name = "-" in marker_name or len(marker_name) > 5
+ marker_size = 38 if special_name else 30
+ # Create a scatter trace for each column
+ trace = go.Scatter(
+ x=[value_x],
+ y=[value_y],
+ mode="markers+text",
+ text=[marker_name],
+ textposition="middle center",
+ textfont=dict(size=10 if len(marker_name) < 4 else 8, color="black"),
+ marker=dict(
+ size=marker_size,
+ color=color_sequence[i % len(color_sequence)],
+ line=dict(color="black", width=1),
+ ),
+ name=column_name,
+ showlegend=False,
+ hovertemplate="%{fullData.name}"
+ + "
RS-Ratio: %{x:.4f}"
+ + "RS-Momentum: %{y:.4f}"
+ + "",
+ )
+ # Add the trace to the list
+ traces.append(trace)
+
+ padding = 0.1
+ y_range = [y_min - padding * abs(y_min) - 0.3, y_max + padding * abs(y_max)]
+ x_range = [x_min - padding * abs(x_min), x_max + padding * abs(x_max)]
+
+ layout = go.Layout(
+ title={
+ "text": (
+ f"RS-Ratio vs RS-Momentum of {study.capitalize()} "
+ f"Against {benchmark_symbol.replace('^', '')} - {to_datetime(row_x.name).strftime('%Y-%m-%d')}" # type: ignore
+ ),
+ "x": 0.5,
+ "xanchor": "center",
+ "font": dict(size=20),
+ },
+ xaxis=dict(
+ title="RS-Ratio",
+ zerolinecolor="black",
+ range=x_range,
+ showspikes=False,
+ ),
+ yaxis=dict(
+ title="
RS-Momentum",
+ zerolinecolor="black",
+ range=y_range,
+ side="left",
+ title_standoff=5,
+ showspikes=False,
+ ),
+ shapes=[
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=0,
+ y0=0,
+ x1=x_range[1],
+ y1=y_range[1],
+ fillcolor="lightgreen",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=0,
+ x1=0,
+ y1=y_range[1],
+ fillcolor="lightblue",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=y_range[0],
+ x1=0,
+ y1=0,
+ fillcolor="lightpink",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=0,
+ y0=y_range[0],
+ x1=x_range[1],
+ y1=0,
+ fillcolor="lightyellow",
+ opacity=0.3,
+ layer="below",
+ line_width=0,
+ ),
+ go.layout.Shape(
+ type="rect",
+ xref="x",
+ yref="y",
+ x0=x_range[0],
+ y0=y_range[0],
+ x1=x_range[1],
+ y1=y_range[1],
+ line=dict(
+ color="Black",
+ width=1,
+ ),
+ fillcolor="rgba(0,0,0,0)",
+ layer="above",
+ ),
+ ],
+ annotations=[
+ go.layout.Annotation(
+ x=1,
+ xref="paper",
+ y=1,
+ yref="paper",
+ text="Leading",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="darkgreen",
+ ),
+ ),
+ go.layout.Annotation(
+ x=1,
+ xref="paper",
+ y=0,
+ yref="paper",
+ text="Weakening",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="goldenrod",
+ ),
+ ),
+ go.layout.Annotation(
+ x=0,
+ xref="paper",
+ y=0,
+ yref="paper",
+ text="Lagging",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="red",
+ ),
+ ),
+ go.layout.Annotation(
+ x=0,
+ xref="paper",
+ yref="paper",
+ y=1,
+ text="Improving",
+ showarrow=False,
+ font=dict(
+ size=18,
+ color="blue",
+ ),
+ ),
+ ],
+ autosize=True,
+ margin=dict(
+ l=30,
+ r=50,
+ b=50,
+ t=50,
+ pad=0,
+ ),
+ dragmode="pan",
+ )
+
+ fig = go.Figure(data=traces, layout=layout)
+
+ return fig
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/core/__init__.py b/openbb_platform/obbject_extensions/charting/openbb_charting/core/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..91c890e79c2e7c1c9a033636efda98eaa925b3f7
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/core/__init__.py
@@ -0,0 +1 @@
+"""OpenBB Charting core."""
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/Terminal_icon.png b/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/Terminal_icon.png
new file mode 100644
index 0000000000000000000000000000000000000000..5e984431867f3194d41292dc118162b68b691d77
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/Terminal_icon.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c35949a0354ad27527099161f9cb97503d6bfdc42769e31eca5e589062bddae3
+size 418780
diff --git a/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/plotly-3.0.0.min.js b/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/plotly-3.0.0.min.js
new file mode 100644
index 0000000000000000000000000000000000000000..dc83321e9427572056ad55cedeb85619f8d76e94
--- /dev/null
+++ b/openbb_platform/obbject_extensions/charting/openbb_charting/core/assets/plotly-3.0.0.min.js
@@ -0,0 +1,3879 @@
+/**
+* plotly.js v3.0.0
+* Copyright 2012-2025, Plotly, Inc.
+* All rights reserved.
+* Licensed under the MIT license
+*/
+(
+ function(root, factory) {
+ if (typeof module === "object" && module.exports) {
+ module.exports = factory();
+ } else {
+ root.moduleName = factory();
+ }
+} (typeof self !== "undefined" ? self : this, () => {
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Xnt=uo();$ae.exports=function(t,r){r||(r=2);var n=t.marker,i=n.sizeref||1,a=n.sizemin||0,o=n.sizemode==="area"?function(s){return Math.sqrt(s/i)}:function(s){return s/i};return function(s){var l=o(s/r);return Xnt(l)&&l>0?Math.max(l,a):0}}});var rp=ye(pv=>{"use strict";var Qae=Mr();pv.getSubplot=function(e){return e.subplot||e.xaxis+e.yaxis||e.geo};pv.isTraceInSubplots=function(e,t){if(e.type==="splom"){for(var r=e.xaxes||[],n=e.yaxes||[],i=0;i=0&&r.index{roe.exports=Qnt;var kO={a:7,c:6,h:1,l:2,m:2,q:4,s:4,t:2,v:1,z:0},$nt=/([astvzqmhlc])([^astvzqmhlc]*)/ig;function Qnt(e){var t=[];return e.replace($nt,function(r,n,i){var a=n.toLowerCase();for(i=tat(i),a=="m"&&i.length>2&&(t.push([n].concat(i.splice(0,2))),a="l",n=n=="m"?"l":"L");;){if(i.length==kO[a])return i.unshift(n),t.push(i);if(i.length{"use strict";var rat=XS(),Yn=function(e,t){return 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n=t.type,i=t.calendar,a=t.ticklabelstep,o=t.ticklabelmode==="period",s=t.range[0]>t.range[1],l=!t.ticklabelindex||Vo.isArrayOrTypedArray(t.ticklabelindex)?t.ticklabelindex:[t.ticklabelindex],u=Vo.simpleMap(t.range,t.r2l,void 0,void 0,r),c=u[1]=(k?0:1);A--){var L=!A;A?(t._dtickInit=t.dtick,t._tick0Init=t.tick0):(t.minor._dtickInit=t.minor.dtick,t.minor._tick0Init=t.minor.tick0);var _=A?t:Vo.extendFlat({},t,t.minor);if(L?kn.prepMinorTicks(_,t,r):kn.prepTicks(_,r),_.tickmode==="array"){A?(b=[],v=ise(t,!L)):(g=[],x=ise(t,!L));continue}if(_.tickmode==="sync"){b=[],v=vot(t);continue}var C=sB(u),M=C[0],p=C[1],P=ph(_.dtick),T=n==="log"&&!(P||_.dtick.charAt(0)==="L"),F=kn.tickFirst(_,r);if(A){if(t._tmin=F,F=p:V<=p;V=kn.tickIncrement(V,G,c,i)){if(A&&H++,_.rangebreaks&&!c){if(V=h)break}if(b.length>d||V===q)break;q=V;var N={value:V};A?(T&&V!==(V|0)&&(N.simpleLabel=!0),a>1&&H%a&&(N.skipLabel=!0),b.push(N)):(N.minor=!0,g.push(N))}}if(!g||g.length<2)l=!1;else{var W=(g[1].value-g[0].value)*(s?-1:1);Oot(W,t.tickformat)||(l=!1)}if(!l)E=b;else{var re=b.concat(g);o&&b.length&&(re=re.slice(1)),re=re.sort(function(Rt,kt){return Rt.value-kt.value}).filter(function(Rt,kt,Ct){return kt===0||Rt.value!==Ct[kt-1].value});var ae=re.map(function(Rt,kt){return Rt.minor===void 0&&!Rt.skipLabel?kt:null}).filter(function(Rt){return Rt!==null});ae.forEach(function(Rt){l.map(function(kt){var Ct=Rt+kt;Ct>=0&&Ct-1;ze--){if(b[ze].drop){b.splice(ze,1);continue}b[ze].value=QO(b[ze].value,t);var ce=t.c2p(b[ze].value);(Ce?Re>ce-me:Reh||Yth&&(Ct.periodX=h),Yti&&hgL)t/=gL,n=i(10),e.dtick="M"+12*_m(t,n,vL);else if(a>R3)t/=R3,e.dtick="M"+_m(t,1,nse);else if(a>Fv){if(e.dtick=_m(t,Fv,e._hasDayOfWeekBreaks?[1,2,7,14]:pot),!r){var o=kn.getTickFormat(e),s=e.ticklabelmode==="period";s&&(e._rawTick0=e.tick0),/%[uVW]/.test(o)?e.tick0=Vo.dateTick0(e.calendar,2):e.tick0=Vo.dateTick0(e.calendar,1),s&&(e._dowTick0=e.tick0)}}else a>xm?e.dtick=_m(t,xm,nse):a>tM?e.dtick=_m(t,tM,ase):a>xL?e.dtick=_m(t,xL,ase):(n=i(10),e.dtick=_m(t,n,vL))}else if(e.type==="log"){e.tick0=0;var l=Vo.simpleMap(e.range,e.r2l);if(e._isMinor&&(t*=1.5),t>.7)e.dtick=Math.ceil(t);else if(Math.abs(l[1]-l[0])<1){var u=1.5*Math.abs((l[1]-l[0])/t);t=Math.abs(Math.pow(10,l[1])-Math.pow(10,l[0]))/u,n=i(10),e.dtick="L"+_m(t,n,vL)}else e.dtick=t>.3?"D2":"D1"}else e.type==="category"||e.type==="multicategory"?(e.tick0=0,e.dtick=Math.ceil(Math.max(t,1))):cB(e)?(e.tick0=0,n=1,e.dtick=_m(t,n,got)):(e.tick0=0,n=i(10),e.dtick=_m(t,n,vL));if(e.dtick===0&&(e.dtick=1),!ph(e.dtick)&&typeof e.dtick!="string"){var c=e.dtick;throw e.dtick=1,"ax.dtick error: "+String(c)}};function dse(e){var t=e.dtick;if(e._tickexponent=0,!ph(t)&&typeof t!="string"&&(t=1),(e.type==="category"||e.type==="multicategory")&&(e._tickround=null),e.type==="date"){var r=e.r2l(e.tick0),n=e.l2r(r).replace(/(^-|i)/g,""),i=n.length;if(String(t).charAt(0)==="M")i>10||n.substr(5)!=="01-01"?e._tickround="d":e._tickround=+t.substr(1)%12===0?"y":"m";else if(t>=Fv&&i<=10||t>=Fv*15)e._tickround="d";else if(t>=tM&&i<=16||t>=xm)e._tickround="M";else if(t>=xL&&i<=19||t>=tM)e._tickround="S";else{var a=e.l2r(r+t).replace(/^-/,"").length;e._tickround=Math.max(i,a)-20,e._tickround<0&&(e._tickround=4)}}else if(ph(t)||t.charAt(0)==="L"){var o=e.range.map(e.r2d||Number);ph(t)||(t=Number(t.substr(1))),e._tickround=2-Math.floor(Math.log(t)/Math.LN10+.01);var s=Math.max(Math.abs(o[0]),Math.abs(o[1])),l=Math.floor(Math.log(s)/Math.LN10+.01),u=e.minexponent===void 0?3:e.minexponent;Math.abs(l)>u&&(wL(e.exponentformat)&&!lB(l)?e._tickexponent=3*Math.round((l-1)/3):e._tickexponent=l)}else e._tickround=null}kn.tickIncrement=function(e,t,r,n){var i=r?-1:1;if(ph(t))return Vo.increment(e,i*t);var a=t.charAt(0),o=i*Number(t.substr(1));if(a==="M")return Vo.incrementMonth(e,o,n);if(a==="L")return Math.log(Math.pow(10,e)+o)/Math.LN10;if(a==="D"){var s=t==="D2"?hse:fse,l=e+i*.01,u=Vo.roundUp(Vo.mod(l,1),s,r);return Math.floor(l)+Math.log(w0.round(Math.pow(10,u),1))/Math.LN10}throw"unrecognized dtick "+String(t)};kn.tickFirst=function(e,t){var r=e.r2l||Number,n=Vo.simpleMap(e.range,r,void 0,void 0,t),i=n[1]=0&&g<=e._length?b:null};if(a&&Vo.isArrayOrTypedArray(e.ticktext)){var f=Vo.simpleMap(e.range,e.r2l),h=(Math.abs(f[1]-f[0])-(e._lBreaks||0))/1e4;for(u=0;u"+s;else{var u=nM(e),c=e._trueSide||e.side;(!u&&c==="top"||u&&c==="bottom")&&(o+="
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n=Math.round(t.x),i=e._categories[n]||[],a=i[1]===void 0?"":String(i[1]),o=i[0]===void 0?"":String(i[0]);r?t.text=o+" - "+a:(t.text=a,t.text2=o)}function bot(e,t,r,n,i){i==="never"?i="":e.showexponent==="all"&&Math.abs(t.x/e.dtick)<1e-6&&(i="hide"),t.text=iM(t.x,e,i,n)}function wot(e,t,r,n,i){if(e.thetaunit==="radians"&&!r){var a=t.x/180;if(a===0)t.text="0";else{var o=Tot(a);if(o[1]>=100)t.text=iM(Vo.deg2rad(t.x),e,i,n);else{var s=t.x<0;o[1]===1?o[0]===1?t.text="\u03C0":t.text=o[0]+"\u03C0":t.text=["",o[0],"","\u2044","",o[1],"","\u03C0"].join(""),s&&(t.text=kb+t.text)}}}else t.text=iM(t.x,e,i,n)}function Tot(e){function t(s,l){return Math.abs(s-l)<=1e-6}function r(s,l){return t(l,0)?s:r(l,s%l)}function n(s){for(var l=1;!t(Math.round(s*l)/l,s);)l*=10;return l}var i=n(e),a=e*i,o=Math.abs(r(a,i));return[Math.round(a/o),Math.round(i/o)]}var Aot=["f","p","n","\u03BC","m","","k","M","G","T"];function wL(e){return e==="SI"||e==="B"}function lB(e){return e>14||e<-15}function iM(e,t,r,n){var 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t=e.title.font.size,r=(e.title.text.match(Eb.BR_TAG_ALL)||[]).length;return e.title.hasOwnProperty("standoff")?t*(Cb+r*rM):r?t*(r+1)*rM:t}function Pot(e,t){var r=e._fullLayout,n=t._id,i=n.charAt(0),a=t.title.font.size,o,s=(t.title.text.match(Eb.BR_TAG_ALL)||[]).length;if(t.title.hasOwnProperty("standoff"))t.side==="bottom"||t.side==="right"?o=t._depth+t.title.standoff+a*Cb:(t.side==="top"||t.side==="left")&&(o=t._depth+t.title.standoff+a*($S+s*rM));else{var l=nM(t);if(t.type==="multicategory")o=t._depth;else{var u=1.5*a;l&&(u=.5*a,t.ticks==="outside"&&(u+=t.ticklen)),o=10+u+(t.linewidth?t.linewidth-1:0)}l||(i==="x"?o+=t.side==="top"?a*(t.showticklabels?1:0):a*(t.showticklabels?1.5:.5):o+=t.side==="right"?a*(t.showticklabels?1:.5):a*(t.showticklabels?.5:0))}var c=kn.getPxPosition(e,t),f,h,d;i==="x"?(h=t._offset+t._length/2,d=t.side==="top"?c-o:c+o):(d=t._offset+t._length/2,h=t.side==="right"?c+o:c-o,f={rotate:"-90",offset:0});var v;if(t.type!=="multicategory"){var 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qB=ye(FB=>{"use strict";var Db=xa(),Sy=uo(),vle=id(),Rf=Mr(),Tst=Rf.pushUnique,DB=Rf.strTranslate,Ast=Rf.strRotate,Sst=g3(),A0=Ll(),Mst=qse(),bm=ao(),sd=va(),OL=gv(),wm=Qa(),Est=ad().zindexSeparator,U3=ba(),Ag=rp(),zb=IS(),kst=bB(),Cst=RB(),wle=zb.YANGLE,zB=Math.PI*wle/180,Lst=1/Math.sin(zB),Pst=Math.cos(zB),Ist=Math.sin(zB),Bc=zb.HOVERARROWSIZE,Us=zb.HOVERTEXTPAD,ple={box:!0,ohlc:!0,violin:!0,candlestick:!0},Rst={scatter:!0,scattergl:!0,splom:!0};function gle(e,t){return e.distance-t.distance}FB.hover=function(t,r,n,i){t=Rf.getGraphDiv(t);var a=r.target;Rf.throttle(t._fullLayout._uid+zb.HOVERID,zb.HOVERMINTIME,function(){Dst(t,r,n,i,a)})};FB.loneHover=function(t,r){var n=!0;Array.isArray(t)||(n=!1,t=[t]);var i=r.gd,a=Ele(i),o=kle(i),s=t.map(function(b){var g=b._x0||b.x0||b.x||0,E=b._x1||b.x1||b.x||0,k=b._y0||b.y0||b.y||0,A=b._y1||b.y1||b.y||0,L=b.eventData;if(L){var _=Math.min(g,E),C=Math.max(g,E),M=Math.min(k,A),p=Math.max(k,A),P=b.trace;if(U3.traceIs(P,"gl3d")){var T=i._fullLayout[P.scene]._scene.container,F=T.offsetLeft,q=T.offsetTop;_+=F,C+=F,M+=q,p+=q}L.bbox={x0:_+o,x1:C+o,y0:M+a,y1:p+a},r.inOut_bbox&&r.inOut_bbox.push(L.bbox)}else L=!1;return{color:b.color||sd.defaultLine,x0:b.x0||b.x||0,x1:b.x1||b.x||0,y0:b.y0||b.y||0,y1:b.y1||b.y||0,xLabel:b.xLabel,yLabel:b.yLabel,zLabel:b.zLabel,text:b.text,name:b.name,idealAlign:b.idealAlign,borderColor:b.borderColor,fontFamily:b.fontFamily,fontSize:b.fontSize,fontColor:b.fontColor,fontWeight:b.fontWeight,fontStyle:b.fontStyle,fontVariant:b.fontVariant,nameLength:b.nameLength,textAlign:b.textAlign,trace:b.trace||{index:0,hoverinfo:""},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:b.hovertemplate||!1,hovertemplateLabels:b.hovertemplateLabels||!1,eventData:L}}),l=!1,u=Ale(s,{gd:i,hovermode:"closest",rotateLabels:l,bgColor:r.bgColor||sd.background,container:Db.select(r.container),outerContainer:r.outerContainer||r.container}),c=u.hoverLabels,f=5,h=0,d=0;c.sort(function(b,g){return b.y0-g.y0}).each(function(b,g){var E=b.y0-b.by/2;E-fC[0]._length||ce<0||ce>M[0]._length)return OL.unhoverRaw(e,t)}if(t.pointerX=Re+C[0]._offset,t.pointerY=ce+M[0]._offset,"xval"in t?X=Ag.flat(a,t.xval):X=Ag.p2c(C,Re),"yval"in t?G=Ag.flat(a,t.yval):G=Ag.p2c(M,ce),!Sy(X[0])||!Sy(G[0]))return Rf.warn("Fx.hover failed",t,e),OL.unhoverRaw(e,t)}var ct=1/0;function qt(Ni,_n){for(W=0;W