-
-OR
-
-```python
-from openbb_terminal.sdk import TerminalStyle
-theme = TerminalStyle("dark", "dark", "dark")
-```
-
-
-
-### 3. Access Documentation
-
-Each and every command of OpenBB SDK has detailed documentation about input parameters and returned outputs. You can access them in multiple ways:
-
-**Approach 1: Press `shift + tab`.**
-This will work out of the box if you're using Jupyter Notebook. In case your IDE is VSCode, you will need to install the [Jupyter PowerToys
-extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-jupyter-powertoys).
-
-
-
-**Approach 2: Type `help(command)`.**
-
-You can also type `help(command)`, see example below, to see the command' docstring.
-
-
-
-**Approach 3: Use OpenBB SDK Documentation page.**
-
-Finally, if you prefer to check documentation on a web browser, [OpenBB SDK Documentation](https://openbb-finance.github.io/OpenBBTerminal/sdk/) will be your best friend. You can browse available commands and search for any specific one that you need.
-
-
-
-### 4. Set API Keys
-
-You can set your external API keys through OpenBB SDK.
-
-- Single API setup
-
-```python
-openbb.keys.fmp(key="example")
-
-openbb.keys.reddit(
- client_id="example",
- client_secret="example",
- password="example",
- username="example",
- useragent="example")
-```
-
-
-
-- API key setup with persistence: `persist=True` means that your key will be saved and can be reused after, otherwise it will be lost when you restart the kernel.
-
-```python
-openbb.keys.fmp(key="example", persist=True)
-```
-
-
-
-- Set multiple keys from dictionary
-
-```python
-d = {
- "fed": {
- "key":"XXXXX"
- },
- "binance": {
- "key":"YYYYY",
- "secret":"example"
- },
-}
-
-openbb.keys.set_keys(d)
-```
-
-
-
-- Get info about API setup arguments
-
-```python
-openbb.keys.get_keys_info()
-```
-
-
-
-- Get your defined keys
-
-```python
-openbb.keys.mykeys()
-openbb.keys.mykeys(show=True)
-```
-
-
-
-## Usage
-
-Now, let's explore what OpenBB SDK can do. At a high level, you can break down OpenBB SDK's functionalities into two main buckets: (1) Data layer and (2) Toolbox layer.
-
-### 1. Data Layer
-
-### **Getting financial data from multiple data sources using one single SDK**
-
-OpenBB SDK provides you access to normalized financial data from dozens of data sources, without having to built your own integration or relying on multiple third-party packages. Let's explore how we can do that.
-
-First, you will need to load in the desired ticker. If it's not on the top of your mind, make use of our search functionality.
-
-```python
-openbb.stocks.search("apple")
-```
-
-
-
-We want to load `Apple Inc.` listed on US exchange, so our ticker should be `AAPL`. If you want to load `Apple Inc.` from Brazilian exchange, you should load in `AAPL34.SA`.
-
-```python
-df = openbb.stocks.load("AAPL")
-```
-
-What's extremely powerful about OpenBB SDK is that you can specify the data source. Depending on the asset class, we have a list of available data sources and it's only getting bigger with contributions from our open-source community.
-
-```python
-## From YahooFinance
-df_yf = openbb.stocks.load("AAPL", source='YahooFinance')
-
-## From AlphaVantage
-df_av = openbb.stocks.load("AAPL", source='AlphaVantage')
-
-## From Polygon
-df_pol = openbb.stocks.load("AAPL", source='Polygon')
-```
-
-### **Easy option to switch between obtaining underlying data and charts**
-
-Depending on your needs, you can get the outputs in form of data (e.g. `pandas dataframe`) or charts. If the latter is what you want, simple add `chart=True` as the last parameter.
-
-### 1. Getting underlying data
-
-```python
-openbb.economy.index(indices = ['sp500', 'nyse_ny', 'russell1000'], start_date = '2010-01-01')
-```
-
-
-
-You might be wondering how to find all the available indices. This type of information should be available in the docstring. Let's give it a try.
-
-
-
-As mentioned in the docstring, you can access it with the following helper function.
-
-```python
-openbb.economy.available_indices()
-```
-
-
-
-### 2. Getting charts
-
-```python
-openbb.economy.index(indices = ['sp500', 'nyse_ny', 'russell1000'], start_date = '2010-01-01', chart=True)
-```
-
-
-
-## 2. Toolbox Layer
-
-In addition to financial data, you can also get access to a robust and powerful toolbox to perform analysis on different asset classes and on your portfolio.
-
-Imagine that you would like to leverage existing financial calculations from OpenBB and apply them on your own data. This can be done easily - OpenBB SDK's commands usually accept a `dataframe` as an input. Here you can load it your data, either via a `csv`, `excel` file, or connecting directly with an `API` or a `database`. The possibilities are endless.
-
-Let's go through an example to see how we can do it in a few simple steps. Here we shall see how to use `portfolio optimization` functionalities from OpenBB SDK.
-
-### Step 1. Loading order book
-
-Here we will use an example orderbook for illustration purposes. You can choose to upload your own orderbook instead.
-
-```python
-order_book_path = "portfolio/allocation/60_40_Portfolio.xlsx"
-tickers, categories = openbb.portfolio.po.load(excel_file = order_book_path)
-```
-
-### Step 2. Optimizing portfolio
-
-We provide multiple portfolio optimization techniques. You can utilize basic mean-variance techniques, such as optimizing for the maximum Sharpe ratio, or minimum variance, as well as advanced optimization techniques including Hierarchical Risk Parity and Nested Clustered Optimization.
-
-```python
-## Max Sharpe optimization
-weights_max_sharpe, data_returns_max_sharpe = openbb.portfolio.po.maxsharpe(tickers)
-
-print("Max Sharpe")
-weights_max_sharpe
-```
-
-
-
-```python
-## Minimum risk optimization
-weights_min_risk, data_returns_min_risk = openbb.portfolio.po.minrisk(tickers)
-
-print("Min Risk")
-weights_min_risk
-```
-
-
-
-```python
-## Hierarchical Risk Parity optimization
-
-weights_hrp, data_returns_hrp = openbb.portfolio.po.hrp(tickers)
-
-print("Hierarchical Risk Parity")
-weights_hrp
-```
-
-
-
-After having obtained the asset allocation outcomes, you can plot a correlation heatmap across tickers, as well as their individual risk contribution.
-
-```python
-openbb.portfolio.po.plot(data=data_returns_hrp,weights=weights_hrp,heat=True)
-```
-
-
-
-```python
-openbb.portfolio.po.plot(data=data_returns_hrp,weights=weights_hrp,rc_chart=True)
-```
-
-
-
-These techniques have an extensive list of parameters and thus the optimization outcome is highly dependent on the chosen parameters. For instance, you can refer to the documentation below.
-
-
-This allows us to alter certain assumption which also modify the asset allocation.
-
-```python
-weights_hrp_2, data_returns_hrp_2 = openbb.portfolio.po.hrp(
- tickers,
- interval="5y",
- risk_measure="cVaR",
- risk_aversion=0.8
-)
-
-pd.DataFrame([weights_hrp, weights_hrp_2], index=["Basic", "Extended"]).T
-```
-
-
-
-The basic method was optimized for *variance*. The extended method increases the period of historical data, optimizes for conditional Value at Risk and has a lower risk aversion.
-
-```python
-openbb.portfolio.po.plot(data=data_returns_hrp,weights=weights_hrp,pie=True)
-```
-
-
-
-```python
-openbb.portfolio.po.plot(data=data_returns_hrp_2,weights=weights_hrp_2,pie=True)
-```
-
-
-
-## Useful tips
-
-### 1. Display matplotlib charts in Jupyter Notebook
-
-To display matplotlib charts inside the Jupyter notebook output cells, you can use the block of code below, and initialize it at the top of the Notebook.
-
-```python
-import matplotlib.pyplot as plt
-import matplotlib_inline.backend_inline
-from openbb_terminal.sdk import openbb
-%matplotlib inline
-matplotlib_inline.backend_inline.set_matplotlib_formats("svg")
-```
-
-### 2. Take advantage of `external_axes`
-
-The code below utilizes the `external_axes` parameter to get two axis in one chart.
-
-```python
-import matplotlib.pyplot as plt
-from openbb_terminal.sdk import openbb
-fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)
-openbb.stocks.dps.dpotc(
- "aapl",
- external_axes=[ax1, ax2],
- chart=True,
-)
-fig.tight_layout()
-```
-
-You can also do this to save output charts in a variable for later uses.
-
-### For more examples, we'd recommend checking out our [curated Jupyter Notebook reports](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/reports). They are excellent demonstration on how to use the SDK to its fullest extent
diff --git a/openbb_terminal/reporting.md b/openbb_terminal/reporting.md
deleted file mode 100644
index 011b06705d9..00000000000
--- a/openbb_terminal/reporting.md
+++ /dev/null
@@ -1,71 +0,0 @@
-# `Reporting`
-
-This document explains `OpenBBTerminal` `Reporting` feature.
-
-## 1. Purpose
-
-**CONTRIBUTE**
-
-Code is not the only way you can contribute to improve `OpenBBTerminal`.
-
-You can help the `OpenBBTerminal` Community by enabling sending logs about the usage of the terminal and errors.
-
-If you are concerned about privacy, be assured, we do **not** collect any:
-
-- Personal Identifiable Information (PII).
-- Credentials.
-
-This means that you will stay anonymous at all time.
-
-**REASONS**
-
-With your these reports, we can:
-
-1. See what your favorite features are, understand why and further improve them.
-2. Have a look at the most common errors and improve on the ease of use of the terminal.
-3. Check for incompatibilities of different operating systems and python versions.
-
-This helps to resolve bugs faster and focus the attention of the developers on what is important to you.
-
-`OpenBBTerminal` is an on-site application: you install it on your computer.
-
-On a contrary of a web application that can track the usage of every button and page, we need logs to be sent to us to understand where to spend our time and effort.
-
-## 2. Disable/Enable `Reporting` ?
-
-By default Reporting is enabled.
-
-You can disable it running the command: `/settings/logcollection`
-
-The key `logcollection` should appear in red in the `/settings/help` table when disabled.
-
-You can do the same operation to re-enable it : `logcollection` will appear in green.
-
-## 3. What is and is not collected ?
-
-**NOT COLLECTED**
-
-We have a filter in place, to prevent any Personal Identifiable information saved in the reports.
-
-Credentials are not reported at all.
-
-Here is a list of data we are not collecting :
-
-|**Data**|**Description**|**Collected ?**|
-|:-|:-|:-|
-|User IP Address|User IP address.|NO|
-|User API KEYS|API Keys to connect to third parties API, like : - ALPHAVANTAGE
- COINBASE,
- COINPAPRIKA
- DEGIRO
- REDDIT|NO| -|User information|Other information that can let identify the users, like :
- LastName
- Firstname|NO| -|File/Folder paths|When errors occurs usually computers paths are shown : we filter those.|NO| - -**COLLECTED** - -Here is an exhaustive list of what can be collected : - -|**Data**|**Description**|**Examples**|**Collected ?**| -|:-|:-|:-|:-| -|Python version|Python version on which `OpenBBTerminal`|
- 3.8.12
- 3.9|YES| -|OS|Platform on which `OpenBBTerminal`, is running like|
- Linux
- Darwin
- Windows|YES| -|Exception/Error|When there is a crash of a command.||YES| -|Timestamp|Timestamp associated with logged information.|
- Launch
- Start of command
- End of command
- Exit
- Exception/Error|YES| -|Command|Commands and arguments run during a session|
- /help
- /crypto/disc/cpsearch -q eth
- /crypto/ov/cpinfo --help
- /stocks/load TSLA
- /stocks/candle --trend|YES|