Generates Datasets Pages

03 Writing Algorithms/14 Datasets/02 QuantConnect/01 Binance Crypto Future Margin Rate Data/01 Introduction.html

@@ -1,5 +1,5 @@
 <p>The Binance Crypto Future Margin Rate Data by QuantConnect is for crypto-currency futures margin interest data points. The data covers 421 Cryptocurrency pairs, starts in August 2020, and is delivered on a daily update frequency. This dataset is created by downloading data using Binance API.</p>
 
 <p>This dataset is an important companion to the <a href="/datasets/binance-cryptofuture-price-data">Binance Crypto Future Price Data</a> dataset because it contains information on margin interest data to model margin costs.</p>
-                
+
 <p>For more information about the Binance Crypto Future Margin Rate Data dataset, including CLI commands and pricing, see the <a href="/datasets/binance-cryptofuture-margin-rate-data">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/02 Bybit Crypto Future Margin Rate Data/01 Introduction.html

@@ -1,5 +1,5 @@
 <p>The Bybit Crypto Future Margin Rate Data by QuantConnect is for Cryptocurrency Futures margin interest data points. The data covers 433 Cryptocurrency pairs, starts in August 2020, and is delivered on a daily update frequency. This dataset is created by downloading data using Bybit API.</p>
 
 <p>This dataset is an important companion to the <a href="/datasets/bybit-cryptofuture-price-data">Bybit Crypto Future Price Data</a> dataset because it contains information on margin interest data to model margin costs.</p>
-                
+
 <p>For more information about the Bybit Crypto Future Margin Rate Data dataset, including CLI commands and pricing, see the <a href="/datasets/bybit-cryptofuture-margin-rate-data">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/02 Bybit Crypto Future Margin Rate Data/08 Requesting Data.html

@@ -1,12 +1,12 @@
 <p>To add Bybit Crypto Future Margin Rate data to your algorithm, call the <b class="csharp">AddCryptoFuture</b><b class="python">add_crypto_future</b> method. Save a reference to the Crypto Future <b>Symbol</b> so you can access the data later in your algorithm.</p>
 
 <div class="section-example-container">
-<pre><code class="python">from AlgorithmImports import *
+<pre class="python">from AlgorithmImports import *
 from QuantConnect.DataSource import *
 
 class CoinAPIDataAlgorithm(QCAlgorithm):
 
-    def initialize(self) -> None:
+    def initialize(self) -&gt; None:
         self.set_start_date(2020, 6, 1)
         self.set_end_date(2021, 6, 1)
 
@@ -17,7 +17,7 @@
 
         crypto_future = self.add_crypto_future("BTCUSDT", Resolution.MINUTE)
         # perpetual futures does not have a filter function
-        self.btcusdt = crypto_future.symbol</code></pre>
+        self.btcusdt = crypto_future.symbol</pre>
 <pre class="csharp">namespace QuantConnect
 {
     public class CoinAPIDataAlgorithm : QCAlgorithm

03 Writing Algorithms/14 Datasets/02 QuantConnect/02 Bybit Crypto Future Margin Rate Data/09 Accessing Data.html

@@ -1,10 +1,10 @@
 <p>To get the current Bybit Crypto Margin Rate data, index the <b class="csharp">MarginInterestRates</b><b class="python">margin_interest_rates</b> property of the current <a href="/docs/v2/writing-algorithms/key-concepts/time-modeling/timeslices"><b>Slice</b></a> with the Crypto Future <b>Symbol</b>. <b>Slice</b> objects deliver unique events to your algorithm as they happen, but the <b>Slice</b> may not contain data for your security at every time step. To avoid issues, check if the <b>Slice</b> contains the data you want before you index it.</p>
 
 <div class="section-example-container">
-<pre><code class="python">def on_data(self, slice: Slice) -> None:
+<pre class="python">def on_data(self, slice: Slice) -&gt; None:
         if self.btcusdt in slice.margin_interest_rates:
             interest_rate = slice.margin_interest_rates[self.btcusdt].interest_rate
-            self.log(f"{self.btcusdt} close at {slice.time}: {interest_rate}")</code></pre>
+            self.log(f"{self.btcusdt} close at {slice.time}: {interest_rate}")</pre>
 <pre class="csharp">public override void OnData(Slice slice)
 {
     if (slice.MarginInterestRates.ContainsKey(_symbol))
@@ -18,10 +18,10 @@
 <p>You can also iterate through all of the data objects in the current <b>Slice</b>.</p>
 
 <div class="section-example-container">
-<pre><code class="python">def on_data(self, slice: Slice) -> None:
+<pre class="python">def on_data(self, slice: Slice) -&gt; None:
     for symbol, margin_interest_rate in slice.margin_interest_rates.items():
         interest_rate = margin_interest_rate.interest_rate
-        self.log(f"{symbol} close at {slice.time}: {interest_rate}")</code></pre>
+        self.log(f"{symbol} close at {slice.time}: {interest_rate}")</pre>
 <pre class="csharp">public override void OnData(Slice slice)
 {
     foreach (var kvp in slice.MarginInterestRates)

03 Writing Algorithms/14 Datasets/02 QuantConnect/03 CFD Data/01 Introduction.html

@@ -1,3 +1,3 @@
 <p>The CFD Data by QuantConnect serves 51 <a href="https://www.investopedia.com/terms/c/contractfordifferences.asp">contracts for differences</a> (CFD). The data starts as early as May 2002 and is delivered on any frequency from tick to daily. This dataset is created by QuantConnect processing raw tick data from OANDA.</p>
-                
+
 <p>For more information about the CFD Data dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-cfd">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/04 FOREX Data/01 Introduction.html

@@ -1,3 +1,3 @@
 <p>The FOREX Data by QuantConnect serves 71 <a href="https://www.investopedia.com/terms/f/forex.asp">foreign exchange</a> (FOREX) pairs, starts on various dates from January 2007, and is delivered on any frequency from tick to daily. This dataset is created by QuantConnect processing raw tick data from OANDA.</p>
-                
+
 <p>For more information about the FOREX Data dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-forex">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/05 US ETF Constituents/01 Introduction.html

@@ -2,5 +2,5 @@
 </p>
 
 <p>This dataset depends on the <a href="/datasets/quantconnect-us-equity-security-master">US Equity Security Master</a> dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes.</p>
-                
+
 <p>For more information about the US ETF Constituents dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-etf-constituents">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/05 US ETF Constituents/10 Historical Data.html

@@ -44,4 +44,4 @@ <h4>Historical Universe Data in Research</h4>
        print(f"{constituent.symbol} weight at {constituent.end_time}: {constituent.weight}")</pre>
 </div>
 
-<p>You can call the <b class="csharp">History</b><b class="python">history</b> method in Research.</p>
+<p>You can call the <b class="csharp">History</b><b class="python">history</b> method in Research.</p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/06 US Equities Short Availability/01 Introduction.html

@@ -2,5 +2,5 @@
 </p>
 
 <p>This dataset depends on the <a href="/datasets/quantconnect-us-equity-security-master">US Equity Security Master</a> dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes.</p>
-                
+
 <p>For more information about the US Equities Short Availability dataset, including CLI commands and pricing, see the <a href="/datasets/us-equities-short-availability">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/07 US Equity Coarse Universe/01 Introduction.html

@@ -4,5 +4,5 @@
 <p>This dataset depends on the <a href="/datasets/algoseek-us-equities">US Equities by AlgoSeek</a> dataset because <a href="/docs/v2/writing-algorithms/universes/key-concepts#02-How-Universe-Selection-Works">universe selection</a> adds and removes market data subscriptions and on the <a href="/datasets/quantconnect-us-equity-security-master">US Equity Security Master</a> dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes.</p>
 
 <p>QuantConnect/LEAN combines the data of this dataset with <a href="/datasets/morning-star-us-fundamentals">MorningStar Fundamental data</a> in runtime. You can use this dataset in local development without the Morningstar counterpart.</p>
-                
+
 <p>For more information about the US Equity Coarse Universe dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-coarse-universe-constituents">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/07 US Equity Coarse Universe/03 Getting Started.html

@@ -22,7 +22,7 @@
 def fundamental_filter_function(self, fundamental: List[Fundamental]):
     # Sort all equities with price above $10 by dollar volume
     sorted_by_dollar_volume = sorted([f for f in fundamental if f.price > 10],
-                                key=lambda f: f.dollar_volume)
+                                key=lambda f: f.dollar_volume, reverse=True)
     # Take the top 10
     return [f.symbol for f in sorted_by_dollar_volume[:10]]</pre>
 <pre class="csharp">public override void Initialize()
@@ -36,7 +36,7 @@
     // Sort all equities with price above $10 by dollar volume, take the top 10
     return (from f in fundamental
             where f.Price &gt; 10
-            orderby f.DollarVolume
+            orderby f.DollarVolume descending
             select f.Symbol).Take(10);
 }</pre>
 </div>

03 Writing Algorithms/14 Datasets/02 QuantConnect/07 US Equity Coarse Universe/06 Data Point Attributes.html

@@ -1,2 +1,2 @@
-<p>The US Equity Coarse Universe dataset provides its data within <b>Fundamental</b> objects, which have the following attributes:</p>
+<p>The US Equity Coarse Universe dataset provides its data within <b>Fundamental</b> objects, which have the following . The attributes from <b class='python'>market_cap</b><b class='csharp'>MarketCap</b> to <b class='python'>asset_classification</b><b class='csharp'>AssetClassification</b> listed in the following widget are NaN until this dataset is combined with the <a href='/datasets/morning-star-us-fundamentals'>MorningStar Fundamental</a> dataset.</p>
 <div data-tree="QuantConnect.Data.Fundamental.Fundamental"></div>

03 Writing Algorithms/14 Datasets/02 QuantConnect/07 US Equity Coarse Universe/09 Historical Data.html

@@ -62,4 +62,4 @@ <h4>Historical Universe Data in Research</h4>
         print(f"{fundamental.symbol} dollar volume at {fundamental.end_time}: {fundamental.dollar_volume}")</pre>
 </div>
 
-<p>For more information about historical US Equity fundamental data, see <a href="/docs/v2/research-environment/datasets/equity-fundamental-data">Equity Fundamental Data</a>.</p>
+<p>For more information about historical US Equity fundamental data, see <a href="/docs/v2/research-environment/datasets/equity-fundamental-data">Equity Fundamental Data</a>.</p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/08 US Equity Option Universe/01 Introduction.html

@@ -5,5 +5,5 @@
 <p>This dataset depends on the <a href="/datasets/quantconnect-us-equity-security-master">US Equity Security Master</a> dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes of the underlying security.</p>
 
 <p>This dataset <b>does not</b> contain market data. For market data, see <a href="/datasets/algoseek-us-equity-options">US Equity Options by AlgoSeek</a>.</p>
-                
+
 <p>For more information about the US Equity Option Universe dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-equity-option-universe">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/08 US Equity Option Universe/03 Getting Started.html

@@ -4,7 +4,7 @@
 <pre class="python">option = self.add_option("GOOG")
 self.option_symbol = option.symbol
 option.set_filter(lambda universe: universe.delta(0.4, 0.6))</pre>
-<pre><code class="csharp">var option = AddOption("GOOG");
+<pre class="csharp">var option = AddOption("GOOG");
 _optionSymbol = option.Symbol;
-option.SetFilter(universe => universe.delta(0.4m, 0.6m));</code></pre>
+option.SetFilter(universe =&gt; universe.delta(0.4m, 0.6m));</pre>
 </div>

03 Writing Algorithms/14 Datasets/02 QuantConnect/08 US Equity Option Universe/04 Data Summary.html

@@ -12,4 +12,4 @@
             <td>Daily</td>
         </tr><tr><td>Timezone</td>
             <td>New York</td>
-        </tr></tbody></table
+        </tr></tbody></table>

03 Writing Algorithms/14 Datasets/02 QuantConnect/08 US Equity Option Universe/08 Requesting Data.html

@@ -3,7 +3,7 @@
 <p>The <b class="csharp">AddOption</b><b class="python">add_option</b> method provides a daily stream of Option chain data. To get the most recent daily chain, call the <b class="csharp">OptionChain</b><b class="python">option_chain</b> method with the underlying Equity Symbol. The <b class="csharp">OptionChain</b><b class="python">option_chain</b> method returns data on all the tradable contracts, not just the contracts that pass your universe filter.</p>
 
 <div class="section-example-container">
-<pre><code class="python">class USEquityOptionsDataAlgorithm(QCAlgorithm):
+<pre class="python">class USEquityOptionsDataAlgorithm(QCAlgorithm):
 
     def initialize(self) -&gt; None:
         self.set_start_date(2020, 6, 1)
@@ -17,7 +17,7 @@
         # Get the entire Option chain for the current day.
         chain = self.option_chain(option.symbol.underlying, flatten=True).data_frame
 
-    def _option_filter(self, universe: OptionFilterUniverse) -> OptionFilterUniverse:
+    def _option_filter(self, universe: OptionFilterUniverse) -&gt; OptionFilterUniverse:
         # Contracts can be filtered by greeks, implied volatility, open interest:
         return universe \
             .delta(0.5, 1.5) \
@@ -27,7 +27,7 @@
             .rho(0.5, 3.0) \
             .implied_volatility(1, 3) \
             .open_interest(100,500)
-</code></pre>
+</pre>
 <pre class="csharp">namespace QuantConnect
 {
     public class USEquityOptionsDataAlgorithm : QCAlgorithm
@@ -67,4 +67,4 @@
 
 <p>The Equity resolution must be less than or equal to the Equity Option resolution. For example, if you set the Equity resolution to minute, then you must set the Equity Option resolution to minute, hour, or daily.</p>
 
-<p>For more information about creating US Equity Option Universes, see <a href="/docs/v2/writing-algorithms/universes/equity-options">Equity Options</a>.</p>
+<p>For more information about creating US Equity Option Universes, see <a href="/docs/v2/writing-algorithms/universes/equity-options">Equity Options</a>.</p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/08 US Equity Option Universe/10 Historical Data.html

@@ -33,8 +33,8 @@ <h4>Historical Data In Research</h4>
 {
     var endTime = chain.EndTime;
     var filteredContracts = chain.Data
-        .Select(contract => contract as OptionUniverse)
-        .Where(contract => contract.Greeks.Delta > 0.3m);
+        .Select(contract =&gt; contract as OptionUniverse)
+        .Where(contract =&gt; contract.Greeks.Delta > 0.3m);
     foreach (var contract in filteredContracts)
     {
         var price = contract.Price;
@@ -43,4 +43,4 @@ <h4>Historical Data In Research</h4>
 }</code></pre>
 </div>
 
-<p>For more information about historical Equity Options Universe data in the Research Environment, see <a href="/docs/v2/research-environment/datasets/equity-options/universes">Universes</a>.</p>
+<p>For more information about historical Equity Options Universe data in the Research Environment, see <a href="/docs/v2/research-environment/datasets/equity-options/universes">Universes</a>.</p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/09 US Equity Security Master/01 Introduction.html

@@ -1,5 +1,5 @@
 <p>
 The US Equity Security Master dataset by QuantConnect tracks US Equity corporate actions, including splits, dividends, delistings, mergers, and ticker changes through history. The data covers approximately 27,500 US Equities, starts in January 1998, and is delivered on a daily update frequency. You can easily download and install the dataset with the LEAN CLI so it's ready to use by LEAN. LEAN automatically handles all corporate actions and passes them into your algorithm as <a href="/docs/v2/writing-algorithms/securities/asset-classes/us-equity/corporate-actions">events</a>.
 </p>
-                
+
 <p>For more information about the US Equity Security Master dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-equity-security-master">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/10 US Futures Security Master/01 Introduction.html

@@ -5,5 +5,5 @@
 <p>VIX Futures don't support continous contract rolling with open interest.</p>
 
 <p>This is <em>not</em> the underlying Futures data (<a href='/datasets/algoseek-us-futures'>US Futures</a> dataset), which you need to purchase separately with a license from AlgoSeek. This security master dataset is required to purchase the US Futures or US Future Options datasets.</p>
-                
+
 <p>For more information about the US Futures Security Master dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-futures-security-master">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/11 US Index Option Universe/01 Introduction.html

@@ -3,5 +3,5 @@
 </p>
 
 <p>This dataset <b>does not</b> contain market data. For market data, see <a href="/datasets/algoseek-us-index-options">US Index Options by AlgoSeek</a>.</p>
-                
+
 <p>For more information about the US Index Option Universe dataset, including CLI commands and pricing, see the <a href="/datasets/quantconnect-us-index-option-universe">dataset listing</a>.<p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/11 US Index Option Universe/03 Getting Started.html

@@ -4,7 +4,7 @@
 <pre class="python">option = self.add_index_option('VIX')
 option.set_filter(lambda universe: universe.delta(0.4, 0.6))
 self.option_symbol = option.symbol</pre>
-<pre><code class="csharp">var option = AddIndexOption("VIX");
-option.SetFilter(universe => universe.delta(0.4m, 0.6m));
-_optionSymbol = option.Symbol;</code></pre>
+<pre class="csharp">var option = AddIndexOption("VIX");
+option.SetFilter(universe =&gt; universe.delta(0.4m, 0.6m));
+_optionSymbol = option.Symbol;</pre>
 </div>

03 Writing Algorithms/14 Datasets/02 QuantConnect/11 US Index Option Universe/04 Data Summary.html

@@ -12,4 +12,4 @@
             <td>Daily</td>
         </tr><tr><td>Timezone</td>
             <td>New York</td>
-        </tr></tbody></table
+        </tr></tbody></table>

03 Writing Algorithms/14 Datasets/02 QuantConnect/11 US Index Option Universe/09 Requesting Data.html

@@ -3,7 +3,7 @@
 <p>The <b class="csharp">AddIndexOption</b><b class="python">add_index_option</b> method provides a daily stream of Option chain data. To get the most recent daily chain, call the <b class="csharp">OptionChain</b><b class="python">option_chain</b> method with the canonical Index Option Symbol. The <b class="csharp">OptionChain</b><b class="python">option_chain</b> method returns data on all the tradable contracts, not just the contracts that pass your universe filter.</p>
 
 <div class="section-example-container">
-<pre><code class="python">class IndexOptionsDataAlgorithm(QCAlgorithm):
+<pre class="python">class IndexOptionsDataAlgorithm(QCAlgorithm):
 
     def initialize(self) -&gt; None:
         self.set_start_date(2021, 1, 1)
@@ -26,7 +26,7 @@
         ]
 
 
-    def _option_filter(self, universe: OptionFilterUniverse) -> OptionFilterUniverse:
+    def _option_filter(self, universe: OptionFilterUniverse) -&gt; OptionFilterUniverse:
         # Contracts can be filtered by greeks, implied volatility, open interest:
         return universe \
             .delta(0.5, 1.5) \
@@ -35,8 +35,8 @@
             .theta(-2.0, -0.5) \
             .rho(0.5, 3.0) \
             .implied_volatility(1, 3) \
-            .open_interest(100,500)</code></pre>
-<pre><code class="csharp">namespace QuantConnect
+            .open_interest(100,500)</pre>
+<pre class="csharp">namespace QuantConnect
 {
     public class IndexOptionsDataAlgorithm : QCAlgorithm
     {
@@ -59,7 +59,7 @@
             weeklyOption.SetFilter(OptionFilter);
             _weeklyOptionSymbol = weeklyOption.Symbol;
             var weeklyChain = OptionChain(_weeklyOptionSymbol)
-                .Where(contract => !IndexOptionSymbol.IsStandard(contract.Symbol));
+                .Where(contract =&gt; !IndexOptionSymbol.IsStandard(contract.Symbol));
         }
 
         private virtual OptionFilterUniverse OptionFilter(OptionFilterUniverse universe)
@@ -75,9 +75,9 @@
                 .OpenInterest(100, 500);
         }
     }
-}</code></pre>
+}</pre>
 </div>
 
 <p>The Index resolution must be less than or equal to the Index Option resolution. For example, if you set the Index resolution to minute, then you must set the Index Option resolution to minute, hour, or daily.</p>
 
-<p>For more information about creating US Index Option subscriptions, see <a href="/docs/v2/writing-algorithms/universes/index-options">Index Options</a>.</p>
+<p>For more information about creating US Index Option subscriptions, see <a href="/docs/v2/writing-algorithms/universes/index-options">Index Options</a>.</p>

03 Writing Algorithms/14 Datasets/02 QuantConnect/11 US Index Option Universe/11 Historical Data.html

@@ -35,8 +35,8 @@ <h4>Historical Data In Research</h4>
 {
     var endTime = chain.EndTime;
     var filteredContracts = chain.Data
-        .Select(contract => contract as OptionUniverse)
-        .Where(contract => contract.Greeks.Delta > 0.3m);
+        .Select(contract =&gt; contract as OptionUniverse)
+        .Where(contract =&gt; contract.Greeks.Delta > 0.3m);
     foreach (var contract in filteredContracts)
     {
         var price = contract.Price;