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Posted to commits@wayang.apache.org by be...@apache.org on 2021/02/22 17:32:44 UTC
[incubator-wayang-website] 01/01: Lastest site built on successful
travis build 5 auto-pushed to github
This is an automated email from the ASF dual-hosted git repository.
bertty pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-wayang-website.git
commit d7736ee9470a7f1cfba1e574dcc5184f013dd56b
Author: Travis CI User <tr...@example.org>
AuthorDate: Mon Feb 22 17:32:32 2021 +0000
Lastest site built on successful travis build 5 auto-pushed to github
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+I"�<p>The world is fast moving towards a data-driven society where data is the most valuable asset. Organizations need to perform very diverse analytic tasks using various data processing platforms. In doing so, they face many challenges; chiefly, platform dependence, poor interoperability, and poor performance when using multiple platforms. We present RHEEM, our vision for big data analytics over diverse data processing platforms. RHEEM provides a threelayer data processing and stor [...]
+:ET
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@@ -0,0 +1,2 @@
+I"Y<p>There is a zoo of data processing platforms which help users and organizations to extract value out of their data. Although each of these platforms excels in specific aspects, users typically end up running their data analytics on suboptimal platforms. This is not only because choosing the right platform among the myriad of big data platforms is a daunting task, but also due to the fact that today’s data analytics are moving beyond the limits of a single platform. Thus, there i [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/4f/8074d17766c0ff93d79eb6752e31beb126bb9545f6763b541953904fd748bf b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/4f/8074d17766c0ff93d79eb6752e31beb126bb9545f6763b541953904fd748bf
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@@ -0,0 +1,2 @@
+I"L<p>Inequality joins, which join relational tables on inequality conditions, are used in various applications. While there have been a wide range of optimization methods for joins in database systems, from algorithms such as sort-merge join and band join, to various indices such as B+-tree, R∗-tree and Bitmap, inequality joins have received little attention and queries containing such joins are usually very slow. In this paper, we introduce fast inequality join algorithms. We put c [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/57/7f147ca7aef7374dc3f988611757982a2139b114352f97e3c2b0a276618b22 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/57/7f147ca7aef7374dc3f988611757982a2139b114352f97e3c2b0a276618b22
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@@ -0,0 +1,375 @@
+I"��<p>In contrast to classical data processing systems that provide one dedicated execution engine, Apache Wayang rather is a <em>meta processing framework</em>: You can specify your data processing app via one of Apache Wayang’s API and then Apache Wayang will pick an optimal configuration of classical processing frameworks, such as Java Streams or Apache Spark, to run your app on. Finally, Apache Wayang will also perform the execution, thereby hiding the different specific platform [...]
+
+<p>This approach aims at freeing data engineers and software developers from the burden of knowing the zoo of different data processing systems, their APIs, strengths and weakness; the intricacies of coordinating and integrating different processing platforms; and the inflexibility when tying to a fix set of processing platforms. As of now, Apache Wayang has built in support for the following processing platforms:</p>
+
+<ul>
+ <li>Java 8 Streams</li>
+ <li><a href="https://spark.apache.org/">Apache Spark</a></li>
+ <li><a href="https://github.com/GraphChi/graphchi-java">GraphChi</a></li>
+ <li><a href="http://www.postgresql.org">Postgres</a></li>
+ <li><a href="https://www.sqlite.org/">SQLite</a></li>
+</ul>
+
+<h2 id="how-to-use-apache-wayang">How to use Apache Wayang</h2>
+
+<h3 id="requirements">Requirements:</h3>
+
+<p>Apache Wayang is built with Java 8 and Scala 2.11. However, to execute Apache Wayang it is sufficient to have Java 8 installed. If you want to build Apache Wayang yourself, you will also need to have <a href="http://maven.apache.org">Apache Maven</a> installed. Please also consider that processing platforms employed by Apache Wayang might have further requirements.</p>
+
+<h3 id="get-apache-wayang">Get Apache Wayang:</h3>
+
+<p>Apache Wayang is available via Maven Central. To use it with Maven, for instance, include the following into you POM file:</p>
+
+<div class="language-xml highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nt"><dependency></span>
+ <span class="nt"><groupId></span>org.apache.wayang<span class="nt"></groupId></span>
+ <span class="nt"><artifactId></span>wayang-***<span class="nt"></artifactId></span>
+ <span class="nt"><version></span>0.3.0<span class="nt"></version></span>
+<span class="nt"></dependency></span>
+</code></pre></div></div>
+
+<p>Note the <code class="language-plaintext highlighter-rouge">***</code>: Apache Wayang ships with multiple modules that can be included in your app, depending on how you want to use it:</p>
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang-core</code>: provides core data structures and the optimizer (required)</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang-basic</code>: provides common operators and data types for your apps (recommended)</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang-api</code>: provides an easy-to-use Scala and Java API to assemble wayang plans (recommended)</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang-java</code>, <code class="language-plaintext highlighter-rouge">wayang-spark</code>, <code class="language-plaintext highlighter-rouge">wayang-graphchi</code>, <code class="language-plaintext highlighter-rouge">wayang-sqlite3</code>, <code class="language-plaintext highlighter-rouge">wayang-postgres</code>: adapters for the various supported processing platforms</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang-profiler</code>: provides functionality to learn operator and UDF cost functions from historical execution data</li>
+</ul>
+
+<p>For the sake of version flexibility, you still have to include your Hadoop (<code class="language-plaintext highlighter-rouge">hadoop-hdfs</code> and <code class="language-plaintext highlighter-rouge">hadoop-common</code>) and Spark (<code class="language-plaintext highlighter-rouge">spark-core</code> and <code class="language-plaintext highlighter-rouge">spark-graphx</code>) version of choice.</p>
+
+<p>In addition, you can obtain the most recent snapshot version of Apache Wayang via Apache’s snapshot repository. Just included</p>
+
+<div class="language-xml highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nt"><repositories></span>
+ <span class="nt"><repository></span>
+ <span class="nt"><id></span>apache-snapshots<span class="nt"></id></span>
+ <span class="nt"><url></span>https://repository.apache.org/content/repositories/snapshots<span class="nt"></url></span>
+ <span class="nt"><releases></span>
+ <span class="nt"><enabled></span>false<span class="nt"></enabled></span>
+ <span class="nt"></releases></span>
+ <span class="nt"><snapshots></span>
+ <span class="nt"><enabled></span>true<span class="nt"></enabled></span>
+ <span class="nt"></snapshots></span>
+ <span class="nt"></repository></span>
+<span class="nt"></repositories></span>
+</code></pre></div></div>
+
+<p>If you need to rebuild Apache Wayang, e.g., to use a different Scala version, you can simply do so via Maven:</p>
+
+<ol>
+ <li>Adapt the version variables (e.g., <code class="language-plaintext highlighter-rouge">spark.version</code>) in the main <code class="language-plaintext highlighter-rouge">pom.xml</code> file.</li>
+ <li>Build Apache Wayang with the adapted versions.<code class="language-plaintext highlighter-rouge">$ mvn clean install</code>. <strong>Note</strong> the <code class="language-plaintext highlighter-rouge">standalone</code> profile to fix Hadoop and Spark versions, so that Apache Wayang apps do not explicitly need to declare the corresponding dependencies. Also, note the <code class="language-plaintext highlighter-rouge">distro</code> profile, which assembles a binary Apache Wayang dis [...]
+</ol>
+
+<h3 id="configure-apache-wayang">Configure Apache Wayang:</h3>
+
+<p>In order for Apache Wayang to work properly, it is necessary to tell Apache Wayang about the capacities of your processing platforms and how to reach them. While there is a default configuration that allows to test Apache Wayang right away, we recommend to create a properties file to adapt the configuration where necessary. To have Apache Wayang use that configuration transparently, just run you app via</p>
+
+<div class="language-shell highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="nv">$ </span>java <span class="nt">-Dwayang</span>.configuration<span class="o">=</span>url://to/my/wayang.properties ...
+</code></pre></div></div>
+
+<p>You can find the most relevant settings in the following:</p>
+
+<h4 id="general-settings">General settings</h4>
+
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang.core.log.enabled (= true)</code>: whether to log execution statistics to allow learning better cardinality and cost estimators for the optimizer</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.core.log.executions (= ~/.wayang/executions.json)</code> where to log execution times of operator groups</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.core.log.cardinalities (= ~/.wayang/cardinalities.json)</code> where to log cardinality measurements</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.core.optimizer.instrumentation (= org.apache.wayang.core.profiling.OutboundInstrumentationStrategy)</code>: where to measure cardinalities in Apache Wayang plans; other options are <code class="language-plaintext highlighter-rouge">org.apache.wayang.core.profiling.NoInstrumentationStrategy</code> and <code class="language-plaintext highlighter-rouge">org.apache.wayang.core.profiling.FullInstrumentationStrategy</code></li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.core.optimizer.reoptimize (= false)</code>: whether to progressively optimize Apache Wayang plans</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.basic.tempdir (= file:///tmp)</code>: where to store temporary files, in particular for inter-platform communication</li>
+</ul>
+
+<h4 id="java-streams">Java Streams</h4>
+
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang.java.cpu.mhz (= 2700)</code>: clock frequency of processor the JVM runs on in MHz</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.java.hdfs.ms-per-mb (= 2.7)</code>: average throughput from HDFS to JVM in ms/MB</li>
+</ul>
+
+<h4 id="apache-spark">Apache Spark</h4>
+
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">spark.master (= local)</code>: Spark master</li>
+ <li>various other Spark settings are supported, e.g., <code class="language-plaintext highlighter-rouge">spark.executor.memory</code>, <code class="language-plaintext highlighter-rouge">spark.serializer</code>, …</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.spark.cpu.mhz (= 2700)</code>: clock frequency of processor the Spark workers run on in MHz</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.spark.hdfs.ms-per-mb (= 2.7)</code>: average throughput from HDFS to the Spark workers in ms/MB</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.spark.network.ms-per-mb (= 8.6)</code>: average network throughput of the Spark workers in ms/MB</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.spark.init.ms (= 4500)</code>: time it takes Spark to initialize in ms</li>
+</ul>
+
+<h4 id="graphchi">GraphChi</h4>
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang.graphchi.cpu.mhz (= 2700)</code>: clock frequency of processor GraphChi runs on in MHz</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.graphchi.cpu.cores (= 2)</code>: number of cores GraphChi runs on</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.graphchi.hdfs.ms-per-mb (= 2.7)</code>: average throughput from HDFS to GraphChi in ms/MB</li>
+</ul>
+
+<h4 id="sqlite">SQLite</h4>
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang.sqlite3.jdbc.url</code>: JDBC URL to use SQLite</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.sqlite3.jdbc.user</code>: optional user name</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.sqlite3.jdbc.password</code>: optional password</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.sqlite3.cpu.mhz (= 2700)</code>: clock frequency of processor SQLite runs on in MHz</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.sqlite3.cpu.cores (= 2)</code>: number of cores SQLite runs on</li>
+</ul>
+
+<h4 id="postgresql">PostgreSQL</h4>
+<ul>
+ <li><code class="language-plaintext highlighter-rouge">wayang.postgres.jdbc.url</code>: JDBC URL to use PostgreSQL</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.postgres.jdbc.user</code>: optional user name</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.postgres.jdbc.password</code>: optional password</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.postgres.cpu.mhz (= 2700)</code>: clock frequency of processor PostgreSQL runs on in MHz</li>
+ <li><code class="language-plaintext highlighter-rouge">wayang.postgres.cpu.cores (= 2)</code>: number of cores PostgreSQL runs on</li>
+</ul>
+
+<h3 id="code-with-apache-wayang">Code with Apache Wayang:</h3>
+
+<p>The recommended way to specify your apps with Apache Wayang is via its Scala or Java API from the <code class="language-plaintext highlighter-rouge">wayang-api</code> module. You can find examples below.</p>
+
+<h3 id="learn-cost-functions">Learn cost functions:</h3>
+
+<p>Apache Wayang provides a utility to learn cost functions from historical execution data. Specifically, Apache Wayang can learn configurations for load profile estimators (that estimate CPU load, disk load etc.) for both operators and UDFs, as long as the configuration provides a template for those estimators. As an example, the <code class="language-plaintext highlighter-rouge">JavaMapOperator</code> draws its load profile estimator configuration via the configuration key <code class= [...]
+
+<div class="language-json highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="err">wayang.java.map.load.template</span><span class="w"> </span><span class="err">=</span><span class="w"> </span><span class="p">{</span><span class="err">\</span><span class="w">
+ </span><span class="nl">"in"</span><span class="p">:</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="nl">"out"</span><span class="p">:</span><span class="mi">1</span><span class="p">,</span><span class="err">\</span><span class="w">
+ </span><span class="nl">"cpu"</span><span class="p">:</span><span class="s2">"?*in0"</span><span class="err">\</span><span class="w">
+</span><span class="p">}</span><span class="w">
+</span></code></pre></div></div>
+
+<p>This template specifies a load profile estimator that expects (at least) one input cardinality and one output cardinality. Further, it models a CPU load that is proportional to the input cardinality. However, more complex functions are possible. In particular, you can use</p>
+
+<ul>
+ <li>the variables <code class="language-plaintext highlighter-rouge">in0</code>, <code class="language-plaintext highlighter-rouge">in1</code>, … and <code class="language-plaintext highlighter-rouge">out0</code>, <code class="language-plaintext highlighter-rouge">out1</code>, … to incorporate the input and output cardinalities, respectively;</li>
+ <li>operator properties, such as <code class="language-plaintext highlighter-rouge">numIterations</code> for the <code class="language-plaintext highlighter-rouge">PageRankOperator</code> implementations;</li>
+ <li>the operators <code class="language-plaintext highlighter-rouge">+</code>, <code class="language-plaintext highlighter-rouge">-</code>, <code class="language-plaintext highlighter-rouge">*</code>, <code class="language-plaintext highlighter-rouge">/</code>, <code class="language-plaintext highlighter-rouge">%</code>, <code class="language-plaintext highlighter-rouge">^</code>, and parantheses;</li>
+ <li>the functions <code class="language-plaintext highlighter-rouge">min(x0, x1, ...))</code>, <code class="language-plaintext highlighter-rouge">max(x0, x1, ...)</code>, <code class="language-plaintext highlighter-rouge">abs(x)</code>, <code class="language-plaintext highlighter-rouge">log(x, base)</code>, <code class="language-plaintext highlighter-rouge">ln(x)</code>, <code class="language-plaintext highlighter-rouge">ld(x)</code>;</li>
+ <li>and the constants <code class="language-plaintext highlighter-rouge">e</code> and <code class="language-plaintext highlighter-rouge">pi</code>.</li>
+</ul>
+
+<p>While Apache Wayang specifies templates for all execution operators, you will need to specify that your UDFs are modelled by some configuration-based cost function (see the k-means example below) and create the according initial specification and template yourself. Once, you gathered execution data, you can run</p>
+
+<div class="language-shell highlighter-rouge"><div class="highlight"><pre class="highlight"><code>java ... org.apache.wayang.profiler.ga.GeneticOptimizerApp <span class="o">[</span>configuration URL <span class="o">[</span>execution log]]
+</code></pre></div></div>
+
+<p>This app will try to find appropriate values for the question marks (<code class="language-plaintext highlighter-rouge">?</code>) in the load profile estimator templates to fit the gathered execution data and ready-made configuration entries for the load profile estimators. You can then copy them into your configuration.</p></p>
+
+<h2 id="examples">Examples</h2>
+
+<p>For some executable examples, have a look at <a href="https://www.github.com/sekruse/Apache Wayang-examples">this repository</a>.</p>
+
+<h3 id="wordcount">WordCount</h3>
+
+<p>The “Hello World!”; of data processing systems is the wordcount.</p>
+
+<h4 id="java-api">Java API</h4>
+<div class="language-java highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">org.apache.wayang.api.JavaPlanBuilder</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.basic.data.Tuple2</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.core.api.Configuration</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.core.api.WayangContext</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.core.optimizer.cardinality.DefaultCardinalityEstimator</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.java.Java</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">org.apache.wayang.spark.Spark</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">java.util.Collection</span><span class="o">;</span>
+<span class="kn">import</span> <span class="nn">java.util.Arrays</span><span class="o">;</span>
+
+<span class="kd">public</span> <span class="kd">class</span> <span class="nc">WordcountJava</span> <span class="o">{</span>
+
+ <span class="kd">public</span> <span class="kd">static</span> <span class="kt">void</span> <span class="nf">main</span><span class="o">(</span><span class="nc">String</span><span class="o">[]</span> <span class="n">args</span><span class="o">){</span>
+
+ <span class="c1">// Settings</span>
+ <span class="nc">String</span> <span class="n">inputUrl</span> <span class="o">=</span> <span class="o">&</span><span class="n">quot</span><span class="o">;</span><span class="nl">file:</span><span class="o">/</span><span class="n">tmp</span><span class="o">.</span><span class="na">txt</span><span class="o">&</span><span class="n">quot</span><span class="o">;;</span>
+
+ <span class="c1">// Get a plan builder.</span>
+ <span class="nc">WayangContext</span> <span class="n">wayangContext</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">WayangContext</span><span class="o">(</span><span class="k">new</span> <span class="nc">Configuration</span><span class="o">())</span>
+ <span class="o">.</span><span class="na">withPlugin</span><span class="o">(</span><span class="nc">Java</span><span class="o">.</span><span class="na">basicPlugin</span><span class="o">())</span>
+ <span class="o">.</span><span class="na">withPlugin</span><span class="o">(</span><span class="nc">Spark</span><span class="o">.</span><span class="na">basicPlugin</span><span class="o">());</span>
+ <span class="nc">JavaPlanBuilder</span> <span class="n">planBuilder</span> <span class="o">=</span> <span class="k">new</span> <span class="nc">JavaPlanBuilder</span><span class="o">(</span><span class="n">wayangContext</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">withJobName</span><span class="o">(</span><span class="nc">String</span><span class="o">.</span><span class="na">format</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="nc">WordCount</span> <span class="o">(%</span><span class="n">s</span><span class="o">)&</span><span class="n">quot</span><span class="o">;,</span> <span class="n">inputUrl</span><span class="o">))</span>
+ <span class="o">.</span><span class="na">withUdfJarOf</span><span class="o">(</span><span class="nc">WordcountJava</span><span class="o">.</span><span class="na">class</span><span class="o">);</span>
+
+ <span class="c1">// Start building the Apache WayangPlan.</span>
+ <span class="nc">Collection</span><span class="o">&</span><span class="n">lt</span><span class="o">;</span><span class="nc">Tuple2</span><span class="o">&</span><span class="n">lt</span><span class="o">;</span><span class="nc">String</span><span class="o">,</span> <span class="nc">Integer</span><span class="o">&</span><span class="n">gt</span><span class="o">;&</span><span class="n">gt</span><span class="o">;</span> <span class="n">wordcounts</span> <span class="o [...]
+ <span class="c1">// Read the text file.</span>
+ <span class="o">.</span><span class="na">readTextFile</span><span class="o">(</span><span class="n">inputUrl</span><span class="o">).</span><span class="na">withName</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="nc">Load</span> <span class="n">file</span><span class="o">&</span><span class="n">quot</span><span class="o">;)</span>
+
+ <span class="c1">// Split each line by non-word characters.</span>
+ <span class="o">.</span><span class="na">flatMap</span><span class="o">(</span><span class="n">line</span> <span class="o">-&</span><span class="n">gt</span><span class="o">;</span> <span class="nc">Arrays</span><span class="o">.</span><span class="na">asList</span><span class="o">(</span><span class="n">line</span><span class="o">.</span><span class="na">split</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="err">\\</ [...]
+ <span class="o">.</span><span class="na">withSelectivity</span><span class="o">(</span><span class="mi">10</span><span class="o">,</span> <span class="mi">100</span><span class="o">,</span> <span class="mf">0.9</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">withName</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="nc">Split</span> <span class="n">words</span><span class="o">&</span><span class="n">quot</span><span class="o">;)</span>
+
+ <span class="c1">// Filter empty tokens.</span>
+ <span class="o">.</span><span class="na">filter</span><span class="o">(</span><span class="n">token</span> <span class="o">-&</span><span class="n">gt</span><span class="o">;</span> <span class="o">!</span><span class="n">token</span><span class="o">.</span><span class="na">isEmpty</span><span class="o">())</span>
+ <span class="o">.</span><span class="na">withSelectivity</span><span class="o">(</span><span class="mf">0.99</span><span class="o">,</span> <span class="mf">0.99</span><span class="o">,</span> <span class="mf">0.99</span><span class="o">)</span>
+ <span class="o">.</span><span class="na">withName</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="nc">Filter</span> <span class="n">empty</span> <span class="n">words</span><span class="o">&</span><span class="n">quot</span><span class="o">;)</span>
+
+ <span class="c1">// Attach counter to each word.</span>
+ <span class="o">.</span><span class="na">map</span><span class="o">(</span><span class="n">word</span> <span class="o">-&</span><span class="n">gt</span><span class="o">;</span> <span class="k">new</span> <span class="nc">Tuple2</span><span class="o">&</span><span class="n">lt</span><span class="o">;&</span><span class="n">gt</span><span class="o">;(</span><span class="n">word</span><span class="o">.</span><span class="na">toLowerCase</span><span class="o">(), [...]
+
+ <span class="c1">// Sum up counters for every word.</span>
+ <span class="o">.</span><span class="na">reduceByKey</span><span class="o">(</span>
+ <span class="nl">Tuple2:</span><span class="o">:</span><span class="n">getField0</span><span class="o">,</span>
+ <span class="o">(</span><span class="n">t1</span><span class="o">,</span> <span class="n">t2</span><span class="o">)</span> <span class="o">-&</span><span class="n">gt</span><span class="o">;</span> <span class="k">new</span> <span class="nc">Tuple2</span><span class="o">&</span><span class="n">lt</span><span class="o">;&</span><span class="n">gt</span><span class="o">;(</span><span class="n">t1</span><span class="o">.</span><span class="na">getField0< [...]
+ <span class="o">)</span>
+ <span class="o">.</span><span class="na">withCardinalityEstimator</span><span class="o">(</span><span class="k">new</span> <span class="nc">DefaultCardinalityEstimator</span><span class="o">(</span><span class="mf">0.9</span><span class="o">,</span> <span class="mi">1</span><span class="o">,</span> <span class="kc">false</span><span class="o">,</span> <span class="n">in</span> <span class="o">-&</span><span class="n">gt</span><span class="o">;</span> <span class="nc"> [...]
+<span class="o"><</span><span class="n">li</span><span class="o">></span>
+<span class="n">in</span><span class="o">[</span><span class="mi">0</span><span class="o">])))</span>
+ <span class="o">.</span><span class="na">withName</span><span class="o">(&</span><span class="n">quot</span><span class="o">;</span><span class="nc">Add</span> <span class="n">counters</span><span class="o">&</span><span class="n">quot</span><span class="o">;)</span>
+
+ <span class="c1">// Execute the plan and collect the results.</span>
+ <span class="o">.</span><span class="na">collect</span><span class="o">();</span>
+
+ <span class="nc">System</span><span class="o">.</span><span class="na">out</span><span class="o">.</span><span class="na">println</span><span class="o">(</span><span class="n">wordcounts</span><span class="o">);</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</code></pre></div></div>
+
+<h4 id="scala-api">Scala API</h4>
+
+<div class="language-scala highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">import</span> <span class="nn">org.apache.wayang.api._</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.core.api.</span><span class="o">{</span><span class="nc">Configuration</span><span class="o">,</span> <span class="nc">WayangContext</span><span class="o">}</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.java.Java</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.spark.Spark</span>
+
+<span class="k">object</span> <span class="nc">WordcountScala</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="nf">main</span><span class="o">(</span><span class="n">args</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">String</span><span class="o">])</span> <span class="o">{</span>
+
+ <span class="c1">// Settings</span>
+ <span class="k">val</span> <span class="nv">inputUrl</span> <span class="k">=</span> <span class="s">"file:/tmp.txt"</span>
+
+ <span class="c1">// Get a plan builder.</span>
+ <span class="k">val</span> <span class="nv">wayangContext</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">WayangContext</span><span class="o">(</span><span class="k">new</span> <span class="nc">Configuration</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withPlugin</span><span class="o">(</span><span class="nv">Java</span><span class="o">.</span><span class="py">basicPlugin</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withPlugin</span><span class="o">(</span><span class="nv">Spark</span><span class="o">.</span><span class="py">basicPlugin</span><span class="o">)</span>
+ <span class="k">val</span> <span class="nv">planBuilder</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">PlanBuilder</span><span class="o">(</span><span class="n">wayangContext</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withJobName</span><span class="o">(</span><span class="n">s</span><span class="s">"WordCount ($inputUrl)"</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withUdfJarsOf</span><span class="o">(</span><span class="k">this</span><span class="o">.</span><span class="py">getClass</span><span class="o">)</span>
+
+ <span class="k">val</span> <span class="nv">wordcounts</span> <span class="k">=</span> <span class="n">planBuilder</span>
+ <span class="c1">// Read the text file.</span>
+ <span class="o">.</span><span class="py">readTextFile</span><span class="o">(</span><span class="n">inputUrl</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Load file"</span><span class="o">)</span>
+
+ <span class="c1">// Split each line by non-word characters.</span>
+ <span class="o">.</span><span class="py">flatMap</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">split</span><span class="o">(</span><span class="s">"\\W+"</span><span class="o">),</span> <span class="n">selectivity</span> <span class="k">=</span> <span class="mi">10</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Split words"</span><span class="o">)</span>
+
+ <span class="c1">// Filter empty tokens.</span>
+ <span class="o">.</span><span class="py">filter</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">nonEmpty</span><span class="o">,</span> <span class="n">selectivity</span> <span class="k">=</span> <span class="mf">0.99</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Filter empty words"</span><span class="o">)</span>
+
+ <span class="c1">// Attach counter to each word.</span>
+ <span class="o">.</span><span class="py">map</span><span class="o">(</span><span class="n">word</span> <span class="k">=></span> <span class="o">(</span><span class="nv">word</span><span class="o">.</span><span class="py">toLowerCase</span><span class="o">,</span> <span class="mi">1</span><span class="o">)).</span><span class="py">withName</span><span class="o">(</span><span class="s">"To lower case, add counter"</span><span class="o">)</span>
+
+ <span class="c1">// Sum up counters for every word.</span>
+ <span class="o">.</span><span class="py">reduceByKey</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">_1</span><span class="o">,</span> <span class="o">(</span><span class="n">c1</span><span class="o">,</span> <span class="n">c2</span><span class="o">)</span> <span class="k">=></span> <span class="o">(</span><span class="nv">c1</span><span class="o">.</span><span class="py">_1</span><span class="o">,</span> <span class="nv">c1</span [...]
+ <span class="o">.</span><span class="py">withCardinalityEstimator</span><span class="o">((</span><span class="n">in</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span> <span class="k">=></span> <span class="nv">math</span><span class="o">.</span><span class="py">round</span><span class="o">(</span><span class="n">in</span>
+
+ <span class="mf">0.01</span><span class="o">))</span>
+
+ <span class="c1">// Execute the plan and collect the results.</span>
+ <span class="o">.</span><span class="py">collect</span><span class="o">()</span>
+
+ <span class="nf">println</span><span class="o">(</span><span class="n">wordcounts</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</code></pre></div></div>
+
+<h3 id="k-means">K-means</h3>
+
+<p>Apache Wayang is also capable of iterative processing, which is, e.g., very important for machine learning algorithms, such as k-means.</p>
+
+<h4 id="scala-api-1">Scala API</h4>
+
+<div class="language-scala highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="k">import</span> <span class="nn">org.apache.wayang.api._</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.core.api.</span><span class="o">{</span><span class="nc">Configuration</span><span class="o">,</span> <span class="nc">WayangContext</span><span class="o">}</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.core.function.FunctionDescriptor.ExtendedSerializableFunction</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.core.function.ExecutionContext</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.core.optimizer.costs.LoadProfileEstimators</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.java.Java</span>
+<span class="k">import</span> <span class="nn">org.apache.wayang.spark.Spark</span>
+
+<span class="k">import</span> <span class="nn">scala.util.Random</span>
+<span class="k">import</span> <span class="nn">scala.collection.JavaConversions._</span>
+
+<span class="k">object</span> <span class="nc">kmeans</span> <span class="o">{</span>
+ <span class="k">def</span> <span class="nf">main</span><span class="o">(</span><span class="n">args</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">String</span><span class="o">])</span> <span class="o">{</span>
+
+ <span class="c1">// Settings</span>
+ <span class="k">val</span> <span class="nv">inputUrl</span> <span class="k">=</span> <span class="s">"file:/kmeans.txt"</span>
+ <span class="k">val</span> <span class="nv">k</span> <span class="k">=</span> <span class="mi">5</span>
+ <span class="k">val</span> <span class="nv">iterations</span> <span class="k">=</span> <span class="mi">100</span>
+ <span class="k">val</span> <span class="nv">configuration</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">Configuration</span>
+
+ <span class="c1">// Get a plan builder.</span>
+ <span class="k">val</span> <span class="nv">wayangContext</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">WayangContext</span><span class="o">(</span><span class="k">new</span> <span class="nc">Configuration</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withPlugin</span><span class="o">(</span><span class="nv">Java</span><span class="o">.</span><span class="py">basicPlugin</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withPlugin</span><span class="o">(</span><span class="nv">Spark</span><span class="o">.</span><span class="py">basicPlugin</span><span class="o">)</span>
+ <span class="k">val</span> <span class="nv">planBuilder</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">PlanBuilder</span><span class="o">(</span><span class="n">wayangContext</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withJobName</span><span class="o">(</span><span class="n">s</span><span class="s">"k-means ($inputUrl, k=$k, $iterations iterations)"</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withUdfJarsOf</span><span class="o">(</span><span class="k">this</span><span class="o">.</span><span class="py">getClass</span><span class="o">)</span>
+
+ <span class="k">case</span> <span class="k">class</span> <span class="nc">Point</span><span class="o">(</span><span class="n">x</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">y</span><span class="k">:</span> <span class="kt">Double</span><span class="o">)</span>
+ <span class="k">case</span> <span class="k">class</span> <span class="nc">TaggedPoint</span><span class="o">(</span><span class="n">x</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">y</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">cluster</span><span class="k">:</span> <span class="kt">Int</span><span class="o">)</span>
+ <span class="k">case</span> <span class="k">class</span> <span class="nc">TaggedPointCounter</span><span class="o">(</span><span class="n">x</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">y</span><span class="k">:</span> <span class="kt">Double</span><span class="o">,</span> <span class="n">cluster</span><span class="k">:</span> <span class="kt">Int</span><span class="o">,</span> <span class="n">count</span><span class="k">:</spa [...]
+ <span class="k">def</span> <span class="nf">add_points</span><span class="o">(</span><span class="n">that</span><span class="k">:</span> <span class="kt">TaggedPointCounter</span><span class="o">)</span> <span class="k">=</span> <span class="nc">TaggedPointCounter</span><span class="o">(</span><span class="k">this</span><span class="o">.</span><span class="py">x</span> <span class="o">+</span> <span class="nv">that</span><span class="o">.</span><span class="py">x</span><span class= [...]
+ <span class="k">def</span> <span class="nf">average</span> <span class="k">=</span> <span class="nc">TaggedPointCounter</span><span class="o">(</span><span class="n">x</span> <span class="o">/</span> <span class="n">count</span><span class="o">,</span> <span class="n">y</span> <span class="o">/</span> <span class="n">count</span><span class="o">,</span> <span class="n">cluster</span><span class="o">,</span> <span class="mi">0</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Read and parse the input file(s).</span>
+ <span class="k">val</span> <span class="nv">points</span> <span class="k">=</span> <span class="n">planBuilder</span>
+ <span class="o">.</span><span class="py">readTextFile</span><span class="o">(</span><span class="n">inputUrl</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Read file"</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">map</span> <span class="o">{</span> <span class="n">line</span> <span class="k">=></span>
+ <span class="k">val</span> <span class="nv">fields</span> <span class="k">=</span> <span class="nv">line</span><span class="o">.</span><span class="py">split</span><span class="o">(</span><span class="s">","</span><span class="o">)</span>
+ <span class="nc">Point</span><span class="o">(</span><span class="nf">fields</span><span class="o">(</span><span class="mi">0</span><span class="o">).</span><span class="py">toDouble</span><span class="o">,</span> <span class="nf">fields</span><span class="o">(</span><span class="mi">1</span><span class="o">).</span><span class="py">toDouble</span><span class="o">)</span>
+ <span class="o">}.</span><span class="py">withName</span><span class="o">(</span><span class="s">"Create points"</span><span class="o">)</span>
+
+
+ <span class="c1">// Create initial centroids.</span>
+ <span class="k">val</span> <span class="nv">random</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">Random</span>
+ <span class="k">val</span> <span class="nv">initialCentroids</span> <span class="k">=</span> <span class="n">planBuilder</span>
+ <span class="o">.</span><span class="py">loadCollection</span><span class="o">(</span><span class="nf">for</span> <span class="o">(</span><span class="n">i</span> <span class="k"><-</span> <span class="mi">1</span> <span class="n">to</span> <span class="n">k</span><span class="o">)</span> <span class="k">yield</span> <span class="nc">TaggedPointCounter</span><span class="o">(</span><span class="nv">random</span><span class="o">.</span><span class="py">nextGaussian</span><span cl [...]
+
+ <span class="c1">// Declare UDF to select centroid for each data point.</span>
+ <span class="k">class</span> <span class="nc">SelectNearestCentroid</span> <span class="k">extends</span> <span class="nc">ExtendedSerializableFunction</span><span class="o">[</span><span class="kt">Point</span>, <span class="kt">TaggedPointCounter</span><span class="o">]</span> <span class="o">{</span>
+
+ <span class="cm">/*Keeps the broadcasted centroids. */</span>
+ <span class="k">var</span> <span class="n">centroids</span><span class="k">:</span> <span class="kt">Iterable</span><span class="o">[</span><span class="kt">TaggedPointCounter</span><span class="o">]</span> <span class="k">=</span> <span class="k">_</span>
+
+ <span class="k">override</span> <span class="k">def</span> <span class="nf">open</span><span class="o">(</span><span class="n">executionCtx</span><span class="k">:</span> <span class="kt">ExecutionContext</span><span class="o">)</span> <span class="k">=</span> <span class="o">{</span>
+ <span class="n">centroids</span> <span class="k">=</span> <span class="nv">executionCtx</span><span class="o">.</span><span class="py">getBroadcast</span><span class="o">[</span><span class="kt">TaggedPointCounter</span><span class="o">](</span><span class="s">"centroids"</span><span class="o">)</span>
+ <span class="o">}</span>
+
+ <span class="k">override</span> <span class="k">def</span> <span class="nf">apply</span><span class="o">(</span><span class="n">point</span><span class="k">:</span> <span class="kt">Point</span><span class="o">)</span><span class="k">:</span> <span class="kt">TaggedPointCounter</span> <span class="o">=</span> <span class="o">{</span>
+ <span class="k">var</span> <span class="n">minDistance</span> <span class="k">=</span> <span class="nv">Double</span><span class="o">.</span><span class="py">PositiveInfinity</span>
+ <span class="k">var</span> <span class="n">nearestCentroidId</span> <span class="k">=</span> <span class="o">-</span><span class="mi">1</span>
+ <span class="nf">for</span> <span class="o">(</span><span class="n">centroid</span> <span class="k"><-</span> <span class="n">centroids</span><span class="o">)</span> <span class="o">{</span>
+ <span class="k">val</span> <span class="nv">distance</span> <span class="k">=</span> <span class="nv">Math</span><span class="o">.</span><span class="py">pow</span><span class="o">(</span><span class="nv">Math</span><span class="o">.</span><span class="py">pow</span><span class="o">(</span><span class="nv">point</span><span class="o">.</span><span class="py">x</span> <span class="o">-</span> <span class="nv">centroid</span><span class="o">.</span><span class="py">x</span><span [...]
+ <span class="nf">if</span> <span class="o">(</span><span class="n">distance</span> <span class="o"><</span> <span class="n">minDistance</span><span class="o">)</span> <span class="o">{</span>
+ <span class="n">minDistance</span> <span class="k">=</span> <span class="n">distance</span>
+ <span class="n">nearestCentroidId</span> <span class="k">=</span> <span class="nv">centroid</span><span class="o">.</span><span class="py">cluster</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+ <span class="k">new</span> <span class="nc">TaggedPointCounter</span><span class="o">(</span><span class="nv">point</span><span class="o">.</span><span class="py">x</span><span class="o">,</span> <span class="nv">point</span><span class="o">.</span><span class="py">y</span><span class="o">,</span> <span class="n">nearestCentroidId</span><span class="o">,</span> <span class="mi">1</span><span class="o">)</span>
+ <span class="o">}</span>
+ <span class="o">}</span>
+
+ <span class="c1">// Do the k-means loop.</span>
+ <span class="k">val</span> <span class="nv">finalCentroids</span> <span class="k">=</span> <span class="nv">initialCentroids</span><span class="o">.</span><span class="py">repeat</span><span class="o">(</span><span class="n">iterations</span><span class="o">,</span> <span class="o">{</span> <span class="n">currentCentroids</span> <span class="k">=></span>
+ <span class="n">points</span>
+ <span class="o">.</span><span class="py">mapJava</span><span class="o">(</span><span class="k">new</span> <span class="nc">SelectNearestCentroid</span><span class="o">,</span>
+ <span class="n">udfLoad</span> <span class="k">=</span> <span class="nv">LoadProfileEstimators</span><span class="o">.</span><span class="py">createFromSpecification</span><span class="o">(</span>
+ <span class="s">"my.udf.costfunction.key"</span><span class="o">,</span> <span class="n">configuration</span>
+ <span class="o">))</span>
+ <span class="o">.</span><span class="py">withBroadcast</span><span class="o">(</span><span class="n">currentCentroids</span><span class="o">,</span> <span class="s">"centroids"</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Find nearest centroid"</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">reduceByKey</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">cluster</span><span class="o">,</span> <span class="nv">_</span><span class="o">.</span><span class="py">add_points</span><span class="o">(</span><span class="k">_</span><span class="o">)).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Add up points"</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">withCardinalityEstimator</span><span class="o">(</span><span class="n">k</span><span class="o">)</span>
+ <span class="o">.</span><span class="py">map</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">average</span><span class="o">).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Average points"</span><span class="o">)</span>
+ <span class="o">}).</span><span class="py">withName</span><span class="o">(</span><span class="s">"Loop"</span><span class="o">)</span>
+
+ <span class="c1">// Collect the results.</span>
+ <span class="o">.</span><span class="py">collect</span><span class="o">()</span>
+
+ <span class="nf">println</span><span class="o">(</span><span class="n">finalCentroids</span><span class="o">)</span>
+ <span class="o">}</span>
+<span class="o">}</span>
+</code></pre></div></div>
+:ET
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new file mode 100644
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@@ -0,0 +1,6 @@
+I"�<p>Bored of keep moving your app to the newest data processing platform to achieve high performance? Tired of dealing with a zoo of processing platforms to get the best performance for your analytic tasks? Then, this tutorial is for you!</p>
+
+<p>Indeed, we are witnessing a plethora of innovative data processing platforms in the last few years. While this is generally great, leveraging these new technologies in practice bears quite some challenges, just to name a few, developers must: (i) find among the plethora of processing platforms the best one for their applications; (ii) migrate their applications to newer and faster platforms every now and then; and (iii) orchestrate different platforms so that applications leverage the [...]
+
+<p>We address these issues with Rheem, a system that enables big data analytics over multiple data processing platforms in a seamless manner. It provides a three-layer data processing abstraction with that applications can achieve both platform independence and interoperability across multiple platforms. With Rheem, dRheemers (Rheem developers) can focus on the logics of their applications. Rheem, in turn, takes care of efficiently executing applications by choosing either a single or mu [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/90/fab0eb04d5ceb428c615f07b9bbd1c8ab0531c09070944f942fbf497cafa2a b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/90/fab0eb04d5ceb428c615f07b9bbd1c8ab0531c09070944f942fbf497cafa2a
new file mode 100644
index 0000000..539e568
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/90/fab0eb04d5ceb428c615f07b9bbd1c8ab0531c09070944f942fbf497cafa2a
@@ -0,0 +1,2 @@
+I"]<p>Many of today’s applications need several data processing platforms for complex analytics. Thus, recent systems have taken steps towards supporting cross-platform data analytics. Yet, current cross-platform systems lack of ease-of-use, which is crucial for their adoption. This demo presents RHEEMStudio, a visual IDE on top of RHEEM. It allows users to easily specify their cross-platform data analytic tasks. In this demo, we will demonstrate five main features of RHEEMStudio: dr [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/a0/d2acea403db1ae3045ff584eac177c53440b70f8a9f2b18721a682b2404d15 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/a0/d2acea403db1ae3045ff584eac177c53440b70f8a9f2b18721a682b2404d15
new file mode 100644
index 0000000..1326964
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/a0/d2acea403db1ae3045ff584eac177c53440b70f8a9f2b18721a682b2404d15
@@ -0,0 +1,2 @@
+I"�<p>Data cleansing approaches have usually focused on detecting and fixing errors with little attention to scaling to big datasets. This presents a serious impediment since data cleansing often involves costly computations such as enumerating pairs of tuples, handling inequality joins, and dealing with user-defined functions. In this paper, we present BigDansing, a Big Data Cleansing system to tackle efficiency, scalability, and ease-of-use issues in data cleansing. The system can [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c1/dc439f391d65cd287144dd96c7f713b2d0b5f9c25a93081dda810f666ea7f4 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c1/dc439f391d65cd287144dd96c7f713b2d0b5f9c25a93081dda810f666ea7f4
new file mode 100644
index 0000000..b0ffb67
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c1/dc439f391d65cd287144dd96c7f713b2d0b5f9c25a93081dda810f666ea7f4
@@ -0,0 +1,2 @@
+I"�<p>Solving business problems increasingly requires going beyond the limits of a single data processing platform (platform for short), such as Hadoop or a DBMS. As a result, organizations typically perform tedious and costly tasks to juggle their code and data across different platforms. Addressing this pain and achieving automatic cross-platform data processing is quite challenging: finding the most efficient platform for a given task requires quite good expertise for all the avai [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c6/3d5b9c3eabb56b0cc7041a34ab5d28e0a30c4007398b1629b071d56cbbe8b7 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c6/3d5b9c3eabb56b0cc7041a34ab5d28e0a30c4007398b1629b071d56cbbe8b7
new file mode 100644
index 0000000..a6a2483
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/c6/3d5b9c3eabb56b0cc7041a34ab5d28e0a30c4007398b1629b071d56cbbe8b7
@@ -0,0 +1,2 @@
+I"$<p>Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases Rheem, a framework that provides multi-platform task execution for such applications. It features a three-layer data processing abstraction and a new query optimization approach for multi-platform settings. We will demonstrate the strengths of Rheem by using real-world scenarios from three different applications, [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/da/63ee9b13d5b72da8eb4a533af8658fa1eed991e5d0cf0e10171a4c56ee7277 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/da/63ee9b13d5b72da8eb4a533af8658fa1eed991e5d0cf0e10171a4c56ee7277
new file mode 100644
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--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/da/63ee9b13d5b72da8eb4a533af8658fa1eed991e5d0cf0e10171a4c56ee7277
@@ -0,0 +1,3 @@
+I"�<p>Apache Wayang has a three-layer data processing abstraction that sits between user applications and data processing platforms, such as Hadoop and Spark. The figure below depicts the Apache Wayang architecture: (i) an application layer that models all application-specific logic; (ii) a core layer that provides the intermediate representation between applications and processing platforms; and (iii) a platform layer that embraces the underlying processing platforms. Overall, the i [...]
+
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e2/8d244d4ca5eeb087f2ecf7602c0141adb0e2e3e3296b46c8e63c997127a35d b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e2/8d244d4ca5eeb087f2ecf7602c0141adb0e2e3e3296b46c8e63c997127a35d
new file mode 100644
index 0000000..e65b554
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e2/8d244d4ca5eeb087f2ecf7602c0141adb0e2e3e3296b46c8e63c997127a35d
@@ -0,0 +1,4 @@
+I"�<p>We are witnessing a proliferation of big data, which has lead to a zoo of data processing systems. Each system providing a different set of features. For example, Spark provides scalability to analytic tasks, but Java 8 Streams provides low-latency. Furthermore, complex applications, such as ETL and ML, are now requiring a mixture of platforms to perform tasks efficiently. In such complex data analytics pipelines, the use of multiple data processing system is not only for perfo [...]
+
+<p>In this talk, we will present Rheem, an open source scalable cross-platform system that frees developers from these burdens. Rheem provides an abstraction layer on top of Spark (and other processing platforms) with the aim of enabling cross-platform optimization and interoperability. It automatically selects the best data processing platforms for a given task and also handles the cross-platform execution. In particular, we will discuss how Rheem allows Spark to work in tandem with oth [...]
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e3/b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855 b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e3/b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
new file mode 100644
index 0000000..80ef94b
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e3/b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
@@ -0,0 +1,2 @@
+I"
+:ET
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diff --git a/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e7/e1235752257de8d1de8b76ca9176e61c58be965b9378ef46f0abf5e495464a b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e7/e1235752257de8d1de8b76ca9176e61c58be965b9378ef46f0abf5e495464a
new file mode 100644
index 0000000..48c0c44
--- /dev/null
+++ b/.jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown/e7/e1235752257de8d1de8b76ca9176e61c58be965b9378ef46f0abf5e495464a
@@ -0,0 +1,2 @@
+I"�<p>As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a speci [...]
+:ET
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diff --git a/about.html b/about.html
new file mode 100644
index 0000000..01bb585
--- /dev/null
+++ b/about.html
@@ -0,0 +1,369 @@
+<!DOCTYPE html>
+<html lang="en"><head>
+ <!-- Required meta tags -->
+ <meta charset="utf-8">
+ <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+
+ <title>Apache Wayang - About</title>
+ <!-- Bootstrap CSS -->
+ <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.0/dist/css/bootstrap.min.css" integrity="sha384-B0vP5xmATw1+K9KRQjQERJvTumQW0nPEzvF6L/Z6nronJ3oUOFUFpCjEUQouq2+l" crossorigin="anonymous">
+ <link rel="stylesheet" href="https://wayang.apache.org/assets/css/color.css">
+ <link rel="stylesheet" href="https://wayang.apache.org/assets/fa/css/all.min.css">
+
+ <link rel="stylesheet" href="https://wayang.apache.org/assets/css/monokai.css">
+ <link rel="stylesheet" href="https://wayang.apache.org/assets/css/home.css">
+
+</head><body>
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+<nav class="navbar navbar-expand-lg navbar-light bg-light sticky-top shadow-lg">
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+ <li class="nav-item ">
+ <a class="nav-link" href="https://wayang.apache.org/documentation">
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+ <li class="nav-item dropdown ">
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+ <a class="dropdown-item" href="http://www.apache.org/foundation/thanks.html">
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+ </a>
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+</nav><div class="container-fluid p-0">
+ <div class="title-post mb-3 mt-n5 d-flex align-items-center shadow" >
+ <div class="col pt-4" style="text-align: center">
+ <h1 class="mb-n2 mt-1" style="color: white; font-size: 4em">About</h1>
+
+ </div>
+</div>
+
+<section>
+ <div class="container">
+ <div class="row" style="margin-top: 15px;">
+ <div class="col-md-12 col-sm-12">
+ <div style="text-align: justify">
+ <p>Apache Wayang has a three-layer data processing abstraction that sits between user applications and data processing platforms, such as Hadoop and Spark. The figure below depicts the Apache Wayang architecture: (i) an application layer that models all application-specific logic; (ii) a core layer that provides the intermediate representation between applications and processing platforms; and (iii) a platform layer that embraces the underlying processing platforms. O [...]
+
+
+ </div>
+ </div>
+ </div>
+ </div>
+</section>
+
+
+<section>
+ <div class="container">
+ <div class="row">
+ <div class="col-md-6 col-sm-12 text-center ">
+ <img src="https://wayang.apache.org/assets/img/architecture.png" style="width: 100%;"/>
+ <br>
+ <em>Architecture of Apache Wayang</em>
+ </div>
+ <div class="col-md-6 col-sm-12 text-center ">
+ <img src="https://wayang.apache.org/assets/img/plan.png" style="width: 100%;"/>
+ <br>
+ <em>SGD plans</em>
+ </div>
+ </div>
+ </div>
+</section>
+
+<div class="subtitle-post d-flex align-items-center mt-5 shadow" >
+ <div class="col" style="text-align: center">
+ <h1 style="color: white; font-size: 4em">Features</h1>
+ </div>
+</div>
+
+<section id="feature_about" class="container-fluid">
+
+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-2">
+ <div class="service-item">
+ <i class="fas fa-bezier-curve fa-5x"></i>
+ <h4>Cross-platform</h4>
+ <strong>
+ Run a single data analytic task on top of any set of data processing platforms.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-1">
+ <p class="text-justify">
+ The most salient feature of Apache Wayang is its cross-platform optimizer. Besides deciding the best processing platform to run any incoming task, Apache Wayang can run a single task on multiple processing platforms. Overall, it applies an extensible set of graph transformations to a Apache Wayang plan to find alternative execution plans. Then, it compares all execution plans by using a platform-specific cost model. Cost functions can either be given or learne [...]
+
+ </p>
+ </div>
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+
+ </div>
+
+ </div>
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+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-1">
+ <div class="service-item">
+ <i class="fa fa-clock fa-5x"></i>
+ <h4>High-Efficiency</h4>
+ <strong>
+ It selects the best available data processing platform for any incoming query.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-2">
+ <p class="text-justify">
+ Apache Wayang provides a number of optimized operators and novel query optimization process that allows it to efficiently deal with big (as well as small) datasets. Furthermore, as its data processing abstraction is based on UDFs, Apache Wayang lets applications expose semantic properties about their functions, optimization hints (e.g., numbers of iterations), constraints (e.g., physical collocation of operators), and alternative plans. The optimizer then uses [...]
+
+ </p>
+ </div>
+ </div>
+
+ </div>
+
+ </div>
+
+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-2">
+ <div class="service-item">
+ <i class="fa fa-puzzle-piece fa-5x"></i>
+ <h4>Flexibility</h4>
+ <strong>
+ User defined functions (UDFs) as first-class citizens, enabling extensibility and adaptability.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-1">
+ <p class="text-justify">
+ Apache Wayang provides a set of Wayang operators, which applications use to specify their tasks, as well as a set of execution operators, which processing platform provide to run application tasks. The key aspect is that Apache Wayang provides a flexible operator mapping structure allowing developers to add, modify, or delete mappings among Wayang and execution operators. As a result, developers can also add or remove Wayang and execution operators.
+
+ </p>
+ </div>
+ </div>
+
+ </div>
+
+ </div>
+
+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-1">
+ <div class="service-item">
+ <i class="fas fa-child fa-5x"></i>
+ <h4>Ease-of-Use</h4>
+ <strong>
+ A simple interface that allows developers to focus only on the logics of their application.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-2">
+ <p class="text-justify">
+ Apache Wayang exposes a simple Java API to developers whereby they can implement their tasks. Developers focus on the logics of their tasks rather than on low-level details specific to data processing platforms. The figure of the SGD plans above shows the Wayang plan for a scalable gradient descent implementation: we clearly see that this tedious implementation task is now much easier!
+
+ </p>
+ </div>
+ </div>
+
+ </div>
+
+ </div>
+
+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-2">
+ <div class="service-item">
+ <i class="fa fa-piggy-bank fa-5x"></i>
+ <h4>Cost Saving</h4>
+ <strong>
+ Fast development of data analytic applications.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-1">
+ <p class="text-justify">
+ Users do not have to know the intricacies of the underlying platforms: they focus on the logic of their application only. This not only speeds up the development of applications, but also it is no longer a must to be an expert in big data infrastructures. Apache Wayang takes care of how and on which data processing platforms to deploy your applications.
+
+ </p>
+ </div>
+ </div>
+
+ </div>
+
+ </div>
+
+
+
+ <div class="row">
+ <div class="container">
+ <div class="row d-flex flex-nowrap">
+ <div class="col-sm-12 col-md-3 col-md-push-9 text-center align-self-center p-2 order-1">
+ <div class="service-item">
+ <i class="fa fa-code-branch fa-5x"></i>
+ <h4>Open Source</h4>
+ <strong>
+ All code is on GitHub under Apache License.
+ </strong>
+ </div>
+ </div>
+ <div class="col-sm-12 col-md-9 col-md-pull-3 align-self-center p-2 order-2">
+ <p class="text-justify">
+ Apache Wayang has been open source from its very beginnings and will keep being open source until its very endings. Feel free to download it, try it, and contribute to it. Help us to make it better!
+ </p>
+ </div>
+ </div>
+
+ </div>
+
+ </div>
+
+
+
+</section>
+
+</div><footer class="footer position-sticky sticky-bottom">
+ <nav class="navbar navbar-light bg-light " style="background: #A6A6A6;">
+ <div class="container">
+ <div class="row justify-content-center">
+ <div class="col-12 text-center">
+ <a href="http://incubator.apache.org/">
+ <img src="https://wayang.apache.org/assets/img/egg-logo.png">
+ </a>
+ <br />
+ <p style="text-align: justify">
+ Apache Wayang is an effort undergoing Incubation at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate [...]
+ </p>
+ <p class="text-center">
+ Copyright © 2021 The Apache Software Foundation.<br />
+ Licensed under the Apache License, Version 2.0.<br />
+ Apache, the Apache Feather logo, and the Apache Incubator project logo are trademarks of The Apache Software Foundation.
+ </p>
+ </div>
+ </div>
+ </div>
+
+ </nav>
+</footer>
+<script src="https://code.jquery.com/jquery-3.5.1.slim.min.js" integrity="sha384-DfXdz2htPH0lsSSs5nCTpuj/zy4C+OGpamoFVy38MVBnE+IbbVYUew+OrCXaRkfj" crossorigin="anonymous"></script>
+<script src="https://cdn.jsdelivr.net/npm/bootstrap@4.6.0/dist/js/bootstrap.bundle.min.js" integrity="sha384-Piv4xVNRyMGpqkS2by6br4gNJ7DXjqk09RmUpJ8jgGtD7zP9yug3goQfGII0yAns" crossorigin="anonymous"></script>
+
+<script src="https://wayang.apache.org/assets/js/add_numbers.js"></script>
+</body>
+
+</html>
\ No newline at end of file
diff --git a/assets/css/color.css b/assets/css/color.css
new file mode 100644
index 0000000..be8a4e5
--- /dev/null
+++ b/assets/css/color.css
@@ -0,0 +1,56 @@
+.bg-gray-dark {
+ background-color: #4C5459 !important;
+}
+
+.bg-gray-light {
+ #background-color: #A6A6A6 !important;
+ background-color: #111111 !important;
+}
+
+.bg-brown-light {
+ background-color: #D9C2A7 !important;
+}
+
+.bg-brown-dark {
+ background-color: #593825 !important;
+}
+
+.bg-black {
+ background-color: #261816 !important;
+}
+
+.letter-gray-dark {
+ color: #4C5459 !important;
+}
+
+.letter-grey-light {
+ color: #A6A6A6 !important;
+}
+
+.letter-brown-light {
+ color: #D9C2A7 !important;
+}
+
+.letter-brown-dark {
+ color: #593825 !important;
+}
+
+.letter-black {
+ color: #261816 !important;
+}
+
+#logo-full {
+ background-image: url(../img/wayang-logo.svg);
+}
+
+.rotateimg15 {
+ -webkit-transform:rotate(-15deg);
+ -moz-transform: rotate(-15deg);
+ -ms-transform: rotate(-15deg);
+ -o-transform: rotate(-15deg);
+ transform: rotate(-15deg);
+}
+
+.service-item > *{
+ text-align: center;
+}
\ No newline at end of file
diff --git a/assets/css/home.css b/assets/css/home.css
new file mode 100644
index 0000000..8fc288b
--- /dev/null
+++ b/assets/css/home.css
@@ -0,0 +1,155 @@
+#full-screen
+{
+ height: 100vh;
+ width: 100vw;
+ background-image: url('https://wayang.apache.org/assets/img/keyword.png');
+ background-repeat: no-repeat;
+ background-size: cover;
+ background-attachment: fixed;
+}
+#full-screen-2
+{
+ height: 100vh;
+ width: 100vw;
+ background-image: url('https://wayang.apache.org/assets/img/wayang-banner.png');
+ background-repeat: no-repeat;
+ background-size: cover;
+ background-attachment: fixed;
+}
+
+.title-post
+{
+ height: 10em;
+ background-position: 50%;
+ background-image: url('https://wayang.apache.org/assets/img/keyword.png');
+ background-repeat: no-repeat;
+ background-size: cover;
+ background-attachment: fixed;
+}
+
+.subtitle-post
+{
+ height: 7em;
+ background-position: 50%;
+ background-image: url('https://wayang.apache.org/assets/img/keyword.png');
+ background-repeat: no-repeat;
+ background-size: cover;
+ background-attachment: fixed;
+}
+
+.service-item {
+ text-align: center;
+}
+/*--
+service Start
+--*/
+#service {
+ text-align: center;
+ padding: 30px 0;
+}
+#service .service-item {
+ padding-bottom: 30px;
+}
+#service .service-item i {
+ font-size: 60px;
+ color: #4A4656;
+}
+#service .service-item h4 {
+ padding-top: 20px;
+ margin: 0;
+ color: #666;
+}
+#service .service-item p {
+ color: #888;
+ padding-top: 10px;
+ margin: 0;
+ font-size: 17px;
+ line-height: 1.8;
+}
+#feature_about > .row:nth-child(odd) {
+ background: linear-gradient(to left, rgba(139,134,163, 0.2), rgba(50,46,64, 0.0));
+}
+#feature_about > .row:nth-child(even) {
+ background: linear-gradient(to left, rgba(50,46,64, 0.0), rgba(139,134,163, 0.2));
+}
+
+.italic {
+ font-style: italic;
+}
+.bold {
+ font-weight: bold;
+}
+hr {
+ border: 1px dotted #555555;
+ width: 80%;
+}
+p {
+ text-align: justify;
+}
+
+.tx-shadow {
+ color: white;
+ text-shadow:
+ 0.05em 0 black,
+ 0 0.05em black,
+ -0.05em 0 black,
+ 0 -0.05em black,
+ -0.05em -0.05em black,
+ -0.05em 0.05em black,
+ 0.05em -0.05em black,
+ 0.05em 0.05em black;
+}
+.tx-shadow .lead {
+ font-size: 1.7em;
+}
+
+.container-circle {
+ min-height: 25em;
+}
+
+.circle {
+ height: 15em;
+ width: 15em;
+ background-color: #bbb;
+ border-radius: 100%;
+ display: inline-block;
+ text-align: center;
+ padding-top: 3em;
+ background: rgb(255,255,255);
+ background: linear-gradient(180deg, rgba(255,255,255,0.8) 0%, rgba(255,255,255,0.8) 92%, rgba(255,255,255,0) 100%); }
+
+.hide {
+ display: none;
+ width: 100%;
+ padding-inline: 0.5em;
+ padding-top: -0.2em;
+ font-size: 1.4em;
+}
+
+.circle:hover {
+ height: 25em;
+ transition: height 0.25s ease-in, border-radius 0.5s;
+ -webkit-transition: height 0.25s ease-in, border-radius 0.5s;
+ border-bottom-left-radius: 0% ;
+ border-bottom-right-radius: 0% ;
+}
+
+.circle:hover > .hide {
+ display: block;
+}
+
+.timeline {
+ padding-left: 2em;
+}
+
+.timeline > .row {
+ border-left-style: solid;
+ border-left-color: #212529;
+ border-left-width: 5px;
+}
+
+.line-top{
+ border-top-style: dotted;
+ border-top-color: #212529;
+ border-top-width: 1px;
+}
diff --git a/assets/css/main.css b/assets/css/main.css
new file mode 100644
index 0000000..5c9c7e6
--- /dev/null
+++ b/assets/css/main.css
@@ -0,0 +1,3 @@
+body { background: #ffffff; color: #000000; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; }
+
+/*# sourceMappingURL=main.css.map */
\ No newline at end of file
diff --git a/assets/css/main.css.map b/assets/css/main.css.map
new file mode 100644
index 0000000..d5d95b5
--- /dev/null
+++ b/assets/css/main.css.map
@@ -0,0 +1,14 @@
+{
+ "version": 3,
+ "file": "main.css",
+ "sources": [
+ "main.scss",
+ "_sass/main.scss"
+ ],
+ "sourcesContent": [
+ "@import \"main\";\n",
+ "$backgroundColor: #ffffff;\n$bodyColor: #000000;\n$bodyFont: -apple-system,BlinkMacSystemFont,\"Segoe UI\",Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\",\"Segoe UI Symbol\";\n\nbody {\n background: $backgroundColor;\n color: $bodyColor;\n font-family: $bodyFont;\n}\n"
+ ],
+ "names": [],
+ "mappings": "ACIA,AAAA,IAAI,CAAC,EACH,UAAU,EALM,OAAO,EAMvB,KAAK,EALK,OAAO,EAMjB,WAAW,EALF,aAAa,EAAC,kBAAkB,EAAC,UAAU,EAAC,SAAS,EAAC,KAAK,EAAC,UAAU,EAAC,mBAAmB,EAAC,gBAAgB,EAAC,iBAAiB,GAMvI"
+}
\ No newline at end of file
diff --git a/assets/css/monokai.css b/assets/css/monokai.css
new file mode 100644
index 0000000..1881d50
--- /dev/null
+++ b/assets/css/monokai.css
@@ -0,0 +1,98 @@
+.highlight pre {
+ background-color: #272822;
+ padding: 0.5em;
+ border-radius: 25px;
+}
+.highlight .hll { background-color: #272822; }
+.highlight .c { color: #75715e } /* Comment */
+.highlight .err { /* Error */
+ color: #f92672;
+}
+.highlight .k { color: #66d9ef } /* Keyword */
+.highlight .l { color: #ae81ff } /* Literal */
+.highlight .n { color: #f8f8f2 } /* Name */
+.highlight .o { color: #f92672 } /* Operator */
+.highlight .p { color: #f8f8f2 } /* Punctuation */
+.highlight .cm { color: #75715e } /* Comment.Multiline */
+.highlight .cp { color: #75715e } /* Comment.Preproc */
+.highlight .c1 { color: #75715e } /* Comment.Single */
+.highlight .cs { color: #75715e } /* Comment.Special */
+.highlight .ge { font-style: italic } /* Generic.Emph */
+.highlight .gs { font-weight: bold } /* Generic.Strong */
+.highlight .kc { color: #66d9ef } /* Keyword.Constant */
+.highlight .kd { color: #66d9ef } /* Keyword.Declaration */
+.highlight .kn { color: #f92672 } /* Keyword.Namespace */
+.highlight .kp { color: #66d9ef } /* Keyword.Pseudo */
+.highlight .kr { color: #66d9ef } /* Keyword.Reserved */
+.highlight .kt { color: #66d9ef } /* Keyword.Type */
+.highlight .ld { color: #e6db74 } /* Literal.Date */
+.highlight .m { color: #ae81ff } /* Literal.Number */
+.highlight .s { color: #e6db74 } /* Literal.String */
+.highlight .na { color: #a6e22e } /* Name.Attribute */
+.highlight .nb { color: #f8f8f2 } /* Name.Builtin */
+.highlight .nc { color: #a6e22e } /* Name.Class */
+.highlight .no { color: #66d9ef } /* Name.Constant */
+.highlight .nd { color: #a6e22e } /* Name.Decorator */
+.highlight .ni { color: #f8f8f2 } /* Name.Entity */
+.highlight .ne { color: #a6e22e } /* Name.Exception */
+.highlight .nf { color: #a6e22e } /* Name.Function */
+.highlight .nl { color: #f8f8f2 } /* Name.Label */
+.highlight .nn { color: #f8f8f2 } /* Name.Namespace */
+.highlight .nx { color: #a6e22e } /* Name.Other */
+.highlight .py { color: #f8f8f2 } /* Name.Property */
+.highlight .nt { color: #f92672 } /* Name.Tag */
+.highlight > code { color: #f8f8f2 } /* Name.Tag */
+.highlight .nv { color: #f8f8f2 } /* Name.Variable */
+.highlight .ow { color: #f92672 } /* Operator.Word */
+.highlight .w { color: #f8f8f2 } /* Text.Whitespace */
+.highlight .mf { color: #ae81ff } /* Literal.Number.Float */
+.highlight .mh { color: #ae81ff } /* Literal.Number.Hex */
+.highlight .mi { color: #ae81ff } /* Literal.Number.Integer */
+.highlight .mo { color: #ae81ff } /* Literal.Number.Oct */
+.highlight .sb { color: #e6db74 } /* Literal.String.Backtick */
+.highlight .sc { color: #e6db74 } /* Literal.String.Char */
+.highlight .sd { color: #e6db74 } /* Literal.String.Doc */
+.highlight .s2 { color: #e6db74 } /* Literal.String.Double */
+.highlight .se { color: #ae81ff } /* Literal.String.Escape */
+.highlight .sh { color: #e6db74 } /* Literal.String.Heredoc */
+.highlight .si { color: #e6db74 } /* Literal.String.Interpol */
+.highlight .sx { color: #e6db74 } /* Literal.String.Other */
+.highlight .sr { color: #e6db74 } /* Literal.String.Regex */
+.highlight .s1 { color: #e6db74 } /* Literal.String.Single */
+.highlight .ss { color: #e6db74 } /* Literal.String.Symbol */
+.highlight .bp { color: #f8f8f2 } /* Name.Builtin.Pseudo */
+.highlight .vc { color: #f8f8f2 } /* Name.Variable.Class */
+.highlight .vg { color: #f8f8f2 } /* Name.Variable.Global */
+.highlight .vi { color: #f8f8f2 } /* Name.Variable.Instance */
+.highlight .il { color: #ae81ff } /* Literal.Number.Integer.Long */
+
+.highlight .gh { } /* Generic Heading & Diff Header */
+.highlight .gu { color: #75715e; } /* Generic.Subheading & Diff Unified/Comment? */
+.highlight .gd { color: #f92672; } /* Generic.Deleted & Diff Deleted */
+.highlight .gi { color: #a6e22e; } /* Generic.Inserted & Diff Inserted */
+
+/** Number in the lines*/
+pre .line-number {
+ color:black;
+ display:block;
+ color: #f8f8f2;
+}
+
+pre .line-number {
+ float:left;
+ margin:0 1em 0 -1em;
+ border-right:1px solid;
+ text-align:right;
+}
+
+pre .line-number span {
+ display:block;
+ padding:0 .5em 0 1em;
+ margin-left: 0.5em;
+}
+
+pre .cl {
+ display:block;
+ clear:both;
+ color: #f8f8f2;
+}
\ No newline at end of file
diff --git a/assets/fa/LICENSE.txt b/assets/fa/LICENSE.txt
new file mode 100644
index 0000000..f31bef9
--- /dev/null
+++ b/assets/fa/LICENSE.txt
@@ -0,0 +1,34 @@
+Font Awesome Free License
+-------------------------
+
+Font Awesome Free is free, open source, and GPL friendly. You can use it for
+commercial projects, open source projects, or really almost whatever you want.
+Full Font Awesome Free license: https://fontawesome.com/license/free.
+
+# Icons: CC BY 4.0 License (https://creativecommons.org/licenses/by/4.0/)
+In the Font Awesome Free download, the CC BY 4.0 license applies to all icons
+packaged as SVG and JS file types.
+
+# Fonts: SIL OFL 1.1 License (https://scripts.sil.org/OFL)
+In the Font Awesome Free download, the SIL OFL license applies to all icons
+packaged as web and desktop font files.
+
+# Code: MIT License (https://opensource.org/licenses/MIT)
+In the Font Awesome Free download, the MIT license applies to all non-font and
+non-icon files.
+
+# Attribution
+Attribution is required by MIT, SIL OFL, and CC BY licenses. Downloaded Font
+Awesome Free files already contain embedded comments with sufficient
+attribution, so you shouldn't need to do anything additional when using these
+files normally.
+
+We've kept attribution comments terse, so we ask that you do not actively work
+to remove them from files, especially code. They're a great way for folks to
+learn about Font Awesome.
+
+# Brand Icons
+All brand icons are trademarks of their respective owners. The use of these
+trademarks does not indicate endorsement of the trademark holder by Font
+Awesome, nor vice versa. **Please do not use brand logos for any purpose except
+to represent the company, product, or service to which they refer.**
diff --git a/assets/fa/attribution.js b/assets/fa/attribution.js
new file mode 100644
index 0000000..2af8326
--- /dev/null
+++ b/assets/fa/attribution.js
@@ -0,0 +1,3 @@
+console.log(`Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+`)
\ No newline at end of file
diff --git a/assets/fa/css/all.css b/assets/fa/css/all.css
new file mode 100644
index 0000000..1a404e7
--- /dev/null
+++ b/assets/fa/css/all.css
@@ -0,0 +1,4619 @@
+/*!
+ * Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ */
+.fa,
+.fas,
+.far,
+.fal,
+.fad,
+.fab {
+ -moz-osx-font-smoothing: grayscale;
+ -webkit-font-smoothing: antialiased;
+ display: inline-block;
+ font-style: normal;
+ font-variant: normal;
+ text-rendering: auto;
+ line-height: 1; }
+
+.fa-lg {
+ font-size: 1.33333em;
+ line-height: 0.75em;
+ vertical-align: -.0667em; }
+
+.fa-xs {
+ font-size: .75em; }
+
+.fa-sm {
+ font-size: .875em; }
+
+.fa-1x {
+ font-size: 1em; }
+
+.fa-2x {
+ font-size: 2em; }
+
+.fa-3x {
+ font-size: 3em; }
+
+.fa-4x {
+ font-size: 4em; }
+
+.fa-5x {
+ font-size: 5em; }
+
+.fa-6x {
+ font-size: 6em; }
+
+.fa-7x {
+ font-size: 7em; }
+
+.fa-8x {
+ font-size: 8em; }
+
+.fa-9x {
+ font-size: 9em; }
+
+.fa-10x {
+ font-size: 10em; }
+
+.fa-fw {
+ text-align: center;
+ width: 1.25em; }
+
+.fa-ul {
+ list-style-type: none;
+ margin-left: 2.5em;
+ padding-left: 0; }
+ .fa-ul > li {
+ position: relative; }
+
+.fa-li {
+ left: -2em;
+ position: absolute;
+ text-align: center;
+ width: 2em;
+ line-height: inherit; }
+
+.fa-border {
+ border: solid 0.08em #eee;
+ border-radius: .1em;
+ padding: .2em .25em .15em; }
+
+.fa-pull-left {
+ float: left; }
+
+.fa-pull-right {
+ float: right; }
+
+.fa.fa-pull-left,
+.fas.fa-pull-left,
+.far.fa-pull-left,
+.fal.fa-pull-left,
+.fab.fa-pull-left {
+ margin-right: .3em; }
+
+.fa.fa-pull-right,
+.fas.fa-pull-right,
+.far.fa-pull-right,
+.fal.fa-pull-right,
+.fab.fa-pull-right {
+ margin-left: .3em; }
+
+.fa-spin {
+ -webkit-animation: fa-spin 2s infinite linear;
+ animation: fa-spin 2s infinite linear; }
+
+.fa-pulse {
+ -webkit-animation: fa-spin 1s infinite steps(8);
+ animation: fa-spin 1s infinite steps(8); }
+
+@-webkit-keyframes fa-spin {
+ 0% {
+ -webkit-transform: rotate(0deg);
+ transform: rotate(0deg); }
+ 100% {
+ -webkit-transform: rotate(360deg);
+ transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+ 0% {
+ -webkit-transform: rotate(0deg);
+ transform: rotate(0deg); }
+ 100% {
+ -webkit-transform: rotate(360deg);
+ transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
+ -webkit-transform: rotate(90deg);
+ transform: rotate(90deg); }
+
+.fa-rotate-180 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
+ -webkit-transform: rotate(180deg);
+ transform: rotate(180deg); }
+
+.fa-rotate-270 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
+ -webkit-transform: rotate(270deg);
+ transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
+ -webkit-transform: scale(-1, 1);
+ transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
+ -webkit-transform: scale(1, -1);
+ transform: scale(1, -1); }
+
+.fa-flip-both, .fa-flip-horizontal.fa-flip-vertical {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
+ -webkit-transform: scale(-1, -1);
+ transform: scale(-1, -1); }
+
+:root .fa-rotate-90,
+:root .fa-rotate-180,
+:root .fa-rotate-270,
+:root .fa-flip-horizontal,
+:root .fa-flip-vertical,
+:root .fa-flip-both {
+ -webkit-filter: none;
+ filter: none; }
+
+.fa-stack {
+ display: inline-block;
+ height: 2em;
+ line-height: 2em;
+ position: relative;
+ vertical-align: middle;
+ width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+ left: 0;
+ position: absolute;
+ text-align: center;
+ width: 100%; }
+
+.fa-stack-1x {
+ line-height: inherit; }
+
+.fa-stack-2x {
+ font-size: 2em; }
+
+.fa-inverse {
+ color: #fff; }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+.fa-500px:before {
+ content: "\f26e"; }
+
+.fa-accessible-icon:before {
+ content: "\f368"; }
+
+.fa-accusoft:before {
+ content: "\f369"; }
+
+.fa-acquisitions-incorporated:before {
+ content: "\f6af"; }
+
+.fa-ad:before {
+ content: "\f641"; }
+
+.fa-address-book:before {
+ content: "\f2b9"; }
+
+.fa-address-card:before {
+ content: "\f2bb"; }
+
+.fa-adjust:before {
+ content: "\f042"; }
+
+.fa-adn:before {
+ content: "\f170"; }
+
+.fa-adversal:before {
+ content: "\f36a"; }
+
+.fa-affiliatetheme:before {
+ content: "\f36b"; }
+
+.fa-air-freshener:before {
+ content: "\f5d0"; }
+
+.fa-airbnb:before {
+ content: "\f834"; }
+
+.fa-algolia:before {
+ content: "\f36c"; }
+
+.fa-align-center:before {
+ content: "\f037"; }
+
+.fa-align-justify:before {
+ content: "\f039"; }
+
+.fa-align-left:before {
+ content: "\f036"; }
+
+.fa-align-right:before {
+ content: "\f038"; }
+
+.fa-alipay:before {
+ content: "\f642"; }
+
+.fa-allergies:before {
+ content: "\f461"; }
+
+.fa-amazon:before {
+ content: "\f270"; }
+
+.fa-amazon-pay:before {
+ content: "\f42c"; }
+
+.fa-ambulance:before {
+ content: "\f0f9"; }
+
+.fa-american-sign-language-interpreting:before {
+ content: "\f2a3"; }
+
+.fa-amilia:before {
+ content: "\f36d"; }
+
+.fa-anchor:before {
+ content: "\f13d"; }
+
+.fa-android:before {
+ content: "\f17b"; }
+
+.fa-angellist:before {
+ content: "\f209"; }
+
+.fa-angle-double-down:before {
+ content: "\f103"; }
+
+.fa-angle-double-left:before {
+ content: "\f100"; }
+
+.fa-angle-double-right:before {
+ content: "\f101"; }
+
+.fa-angle-double-up:before {
+ content: "\f102"; }
+
+.fa-angle-down:before {
+ content: "\f107"; }
+
+.fa-angle-left:before {
+ content: "\f104"; }
+
+.fa-angle-right:before {
+ content: "\f105"; }
+
+.fa-angle-up:before {
+ content: "\f106"; }
+
+.fa-angry:before {
+ content: "\f556"; }
+
+.fa-angrycreative:before {
+ content: "\f36e"; }
+
+.fa-angular:before {
+ content: "\f420"; }
+
+.fa-ankh:before {
+ content: "\f644"; }
+
+.fa-app-store:before {
+ content: "\f36f"; }
+
+.fa-app-store-ios:before {
+ content: "\f370"; }
+
+.fa-apper:before {
+ content: "\f371"; }
+
+.fa-apple:before {
+ content: "\f179"; }
+
+.fa-apple-alt:before {
+ content: "\f5d1"; }
+
+.fa-apple-pay:before {
+ content: "\f415"; }
+
+.fa-archive:before {
+ content: "\f187"; }
+
+.fa-archway:before {
+ content: "\f557"; }
+
+.fa-arrow-alt-circle-down:before {
+ content: "\f358"; }
+
+.fa-arrow-alt-circle-left:before {
+ content: "\f359"; }
+
+.fa-arrow-alt-circle-right:before {
+ content: "\f35a"; }
+
+.fa-arrow-alt-circle-up:before {
+ content: "\f35b"; }
+
+.fa-arrow-circle-down:before {
+ content: "\f0ab"; }
+
+.fa-arrow-circle-left:before {
+ content: "\f0a8"; }
+
+.fa-arrow-circle-right:before {
+ content: "\f0a9"; }
+
+.fa-arrow-circle-up:before {
+ content: "\f0aa"; }
+
+.fa-arrow-down:before {
+ content: "\f063"; }
+
+.fa-arrow-left:before {
+ content: "\f060"; }
+
+.fa-arrow-right:before {
+ content: "\f061"; }
+
+.fa-arrow-up:before {
+ content: "\f062"; }
+
+.fa-arrows-alt:before {
+ content: "\f0b2"; }
+
+.fa-arrows-alt-h:before {
+ content: "\f337"; }
+
+.fa-arrows-alt-v:before {
+ content: "\f338"; }
+
+.fa-artstation:before {
+ content: "\f77a"; }
+
+.fa-assistive-listening-systems:before {
+ content: "\f2a2"; }
+
+.fa-asterisk:before {
+ content: "\f069"; }
+
+.fa-asymmetrik:before {
+ content: "\f372"; }
+
+.fa-at:before {
+ content: "\f1fa"; }
+
+.fa-atlas:before {
+ content: "\f558"; }
+
+.fa-atlassian:before {
+ content: "\f77b"; }
+
+.fa-atom:before {
+ content: "\f5d2"; }
+
+.fa-audible:before {
+ content: "\f373"; }
+
+.fa-audio-description:before {
+ content: "\f29e"; }
+
+.fa-autoprefixer:before {
+ content: "\f41c"; }
+
+.fa-avianex:before {
+ content: "\f374"; }
+
+.fa-aviato:before {
+ content: "\f421"; }
+
+.fa-award:before {
+ content: "\f559"; }
+
+.fa-aws:before {
+ content: "\f375"; }
+
+.fa-baby:before {
+ content: "\f77c"; }
+
+.fa-baby-carriage:before {
+ content: "\f77d"; }
+
+.fa-backspace:before {
+ content: "\f55a"; }
+
+.fa-backward:before {
+ content: "\f04a"; }
+
+.fa-bacon:before {
+ content: "\f7e5"; }
+
+.fa-bacteria:before {
+ content: "\e059"; }
+
+.fa-bacterium:before {
+ content: "\e05a"; }
+
+.fa-bahai:before {
+ content: "\f666"; }
+
+.fa-balance-scale:before {
+ content: "\f24e"; }
+
+.fa-balance-scale-left:before {
+ content: "\f515"; }
+
+.fa-balance-scale-right:before {
+ content: "\f516"; }
+
+.fa-ban:before {
+ content: "\f05e"; }
+
+.fa-band-aid:before {
+ content: "\f462"; }
+
+.fa-bandcamp:before {
+ content: "\f2d5"; }
+
+.fa-barcode:before {
+ content: "\f02a"; }
+
+.fa-bars:before {
+ content: "\f0c9"; }
+
+.fa-baseball-ball:before {
+ content: "\f433"; }
+
+.fa-basketball-ball:before {
+ content: "\f434"; }
+
+.fa-bath:before {
+ content: "\f2cd"; }
+
+.fa-battery-empty:before {
+ content: "\f244"; }
+
+.fa-battery-full:before {
+ content: "\f240"; }
+
+.fa-battery-half:before {
+ content: "\f242"; }
+
+.fa-battery-quarter:before {
+ content: "\f243"; }
+
+.fa-battery-three-quarters:before {
+ content: "\f241"; }
+
+.fa-battle-net:before {
+ content: "\f835"; }
+
+.fa-bed:before {
+ content: "\f236"; }
+
+.fa-beer:before {
+ content: "\f0fc"; }
+
+.fa-behance:before {
+ content: "\f1b4"; }
+
+.fa-behance-square:before {
+ content: "\f1b5"; }
+
+.fa-bell:before {
+ content: "\f0f3"; }
+
+.fa-bell-slash:before {
+ content: "\f1f6"; }
+
+.fa-bezier-curve:before {
+ content: "\f55b"; }
+
+.fa-bible:before {
+ content: "\f647"; }
+
+.fa-bicycle:before {
+ content: "\f206"; }
+
+.fa-biking:before {
+ content: "\f84a"; }
+
+.fa-bimobject:before {
+ content: "\f378"; }
+
+.fa-binoculars:before {
+ content: "\f1e5"; }
+
+.fa-biohazard:before {
+ content: "\f780"; }
+
+.fa-birthday-cake:before {
+ content: "\f1fd"; }
+
+.fa-bitbucket:before {
+ content: "\f171"; }
+
+.fa-bitcoin:before {
+ content: "\f379"; }
+
+.fa-bity:before {
+ content: "\f37a"; }
+
+.fa-black-tie:before {
+ content: "\f27e"; }
+
+.fa-blackberry:before {
+ content: "\f37b"; }
+
+.fa-blender:before {
+ content: "\f517"; }
+
+.fa-blender-phone:before {
+ content: "\f6b6"; }
+
+.fa-blind:before {
+ content: "\f29d"; }
+
+.fa-blog:before {
+ content: "\f781"; }
+
+.fa-blogger:before {
+ content: "\f37c"; }
+
+.fa-blogger-b:before {
+ content: "\f37d"; }
+
+.fa-bluetooth:before {
+ content: "\f293"; }
+
+.fa-bluetooth-b:before {
+ content: "\f294"; }
+
+.fa-bold:before {
+ content: "\f032"; }
+
+.fa-bolt:before {
+ content: "\f0e7"; }
+
+.fa-bomb:before {
+ content: "\f1e2"; }
+
+.fa-bone:before {
+ content: "\f5d7"; }
+
+.fa-bong:before {
+ content: "\f55c"; }
+
+.fa-book:before {
+ content: "\f02d"; }
+
+.fa-book-dead:before {
+ content: "\f6b7"; }
+
+.fa-book-medical:before {
+ content: "\f7e6"; }
+
+.fa-book-open:before {
+ content: "\f518"; }
+
+.fa-book-reader:before {
+ content: "\f5da"; }
+
+.fa-bookmark:before {
+ content: "\f02e"; }
+
+.fa-bootstrap:before {
+ content: "\f836"; }
+
+.fa-border-all:before {
+ content: "\f84c"; }
+
+.fa-border-none:before {
+ content: "\f850"; }
+
+.fa-border-style:before {
+ content: "\f853"; }
+
+.fa-bowling-ball:before {
+ content: "\f436"; }
+
+.fa-box:before {
+ content: "\f466"; }
+
+.fa-box-open:before {
+ content: "\f49e"; }
+
+.fa-box-tissue:before {
+ content: "\e05b"; }
+
+.fa-boxes:before {
+ content: "\f468"; }
+
+.fa-braille:before {
+ content: "\f2a1"; }
+
+.fa-brain:before {
+ content: "\f5dc"; }
+
+.fa-bread-slice:before {
+ content: "\f7ec"; }
+
+.fa-briefcase:before {
+ content: "\f0b1"; }
+
+.fa-briefcase-medical:before {
+ content: "\f469"; }
+
+.fa-broadcast-tower:before {
+ content: "\f519"; }
+
+.fa-broom:before {
+ content: "\f51a"; }
+
+.fa-brush:before {
+ content: "\f55d"; }
+
+.fa-btc:before {
+ content: "\f15a"; }
+
+.fa-buffer:before {
+ content: "\f837"; }
+
+.fa-bug:before {
+ content: "\f188"; }
+
+.fa-building:before {
+ content: "\f1ad"; }
+
+.fa-bullhorn:before {
+ content: "\f0a1"; }
+
+.fa-bullseye:before {
+ content: "\f140"; }
+
+.fa-burn:before {
+ content: "\f46a"; }
+
+.fa-buromobelexperte:before {
+ content: "\f37f"; }
+
+.fa-bus:before {
+ content: "\f207"; }
+
+.fa-bus-alt:before {
+ content: "\f55e"; }
+
+.fa-business-time:before {
+ content: "\f64a"; }
+
+.fa-buy-n-large:before {
+ content: "\f8a6"; }
+
+.fa-buysellads:before {
+ content: "\f20d"; }
+
+.fa-calculator:before {
+ content: "\f1ec"; }
+
+.fa-calendar:before {
+ content: "\f133"; }
+
+.fa-calendar-alt:before {
+ content: "\f073"; }
+
+.fa-calendar-check:before {
+ content: "\f274"; }
+
+.fa-calendar-day:before {
+ content: "\f783"; }
+
+.fa-calendar-minus:before {
+ content: "\f272"; }
+
+.fa-calendar-plus:before {
+ content: "\f271"; }
+
+.fa-calendar-times:before {
+ content: "\f273"; }
+
+.fa-calendar-week:before {
+ content: "\f784"; }
+
+.fa-camera:before {
+ content: "\f030"; }
+
+.fa-camera-retro:before {
+ content: "\f083"; }
+
+.fa-campground:before {
+ content: "\f6bb"; }
+
+.fa-canadian-maple-leaf:before {
+ content: "\f785"; }
+
+.fa-candy-cane:before {
+ content: "\f786"; }
+
+.fa-cannabis:before {
+ content: "\f55f"; }
+
+.fa-capsules:before {
+ content: "\f46b"; }
+
+.fa-car:before {
+ content: "\f1b9"; }
+
+.fa-car-alt:before {
+ content: "\f5de"; }
+
+.fa-car-battery:before {
+ content: "\f5df"; }
+
+.fa-car-crash:before {
+ content: "\f5e1"; }
+
+.fa-car-side:before {
+ content: "\f5e4"; }
+
+.fa-caravan:before {
+ content: "\f8ff"; }
+
+.fa-caret-down:before {
+ content: "\f0d7"; }
+
+.fa-caret-left:before {
+ content: "\f0d9"; }
+
+.fa-caret-right:before {
+ content: "\f0da"; }
+
+.fa-caret-square-down:before {
+ content: "\f150"; }
+
+.fa-caret-square-left:before {
+ content: "\f191"; }
+
+.fa-caret-square-right:before {
+ content: "\f152"; }
+
+.fa-caret-square-up:before {
+ content: "\f151"; }
+
+.fa-caret-up:before {
+ content: "\f0d8"; }
+
+.fa-carrot:before {
+ content: "\f787"; }
+
+.fa-cart-arrow-down:before {
+ content: "\f218"; }
+
+.fa-cart-plus:before {
+ content: "\f217"; }
+
+.fa-cash-register:before {
+ content: "\f788"; }
+
+.fa-cat:before {
+ content: "\f6be"; }
+
+.fa-cc-amazon-pay:before {
+ content: "\f42d"; }
+
+.fa-cc-amex:before {
+ content: "\f1f3"; }
+
+.fa-cc-apple-pay:before {
+ content: "\f416"; }
+
+.fa-cc-diners-club:before {
+ content: "\f24c"; }
+
+.fa-cc-discover:before {
+ content: "\f1f2"; }
+
+.fa-cc-jcb:before {
+ content: "\f24b"; }
+
+.fa-cc-mastercard:before {
+ content: "\f1f1"; }
+
+.fa-cc-paypal:before {
+ content: "\f1f4"; }
+
+.fa-cc-stripe:before {
+ content: "\f1f5"; }
+
+.fa-cc-visa:before {
+ content: "\f1f0"; }
+
+.fa-centercode:before {
+ content: "\f380"; }
+
+.fa-centos:before {
+ content: "\f789"; }
+
+.fa-certificate:before {
+ content: "\f0a3"; }
+
+.fa-chair:before {
+ content: "\f6c0"; }
+
+.fa-chalkboard:before {
+ content: "\f51b"; }
+
+.fa-chalkboard-teacher:before {
+ content: "\f51c"; }
+
+.fa-charging-station:before {
+ content: "\f5e7"; }
+
+.fa-chart-area:before {
+ content: "\f1fe"; }
+
+.fa-chart-bar:before {
+ content: "\f080"; }
+
+.fa-chart-line:before {
+ content: "\f201"; }
+
+.fa-chart-pie:before {
+ content: "\f200"; }
+
+.fa-check:before {
+ content: "\f00c"; }
+
+.fa-check-circle:before {
+ content: "\f058"; }
+
+.fa-check-double:before {
+ content: "\f560"; }
+
+.fa-check-square:before {
+ content: "\f14a"; }
+
+.fa-cheese:before {
+ content: "\f7ef"; }
+
+.fa-chess:before {
+ content: "\f439"; }
+
+.fa-chess-bishop:before {
+ content: "\f43a"; }
+
+.fa-chess-board:before {
+ content: "\f43c"; }
+
+.fa-chess-king:before {
+ content: "\f43f"; }
+
+.fa-chess-knight:before {
+ content: "\f441"; }
+
+.fa-chess-pawn:before {
+ content: "\f443"; }
+
+.fa-chess-queen:before {
+ content: "\f445"; }
+
+.fa-chess-rook:before {
+ content: "\f447"; }
+
+.fa-chevron-circle-down:before {
+ content: "\f13a"; }
+
+.fa-chevron-circle-left:before {
+ content: "\f137"; }
+
+.fa-chevron-circle-right:before {
+ content: "\f138"; }
+
+.fa-chevron-circle-up:before {
+ content: "\f139"; }
+
+.fa-chevron-down:before {
+ content: "\f078"; }
+
+.fa-chevron-left:before {
+ content: "\f053"; }
+
+.fa-chevron-right:before {
+ content: "\f054"; }
+
+.fa-chevron-up:before {
+ content: "\f077"; }
+
+.fa-child:before {
+ content: "\f1ae"; }
+
+.fa-chrome:before {
+ content: "\f268"; }
+
+.fa-chromecast:before {
+ content: "\f838"; }
+
+.fa-church:before {
+ content: "\f51d"; }
+
+.fa-circle:before {
+ content: "\f111"; }
+
+.fa-circle-notch:before {
+ content: "\f1ce"; }
+
+.fa-city:before {
+ content: "\f64f"; }
+
+.fa-clinic-medical:before {
+ content: "\f7f2"; }
+
+.fa-clipboard:before {
+ content: "\f328"; }
+
+.fa-clipboard-check:before {
+ content: "\f46c"; }
+
+.fa-clipboard-list:before {
+ content: "\f46d"; }
+
+.fa-clock:before {
+ content: "\f017"; }
+
+.fa-clone:before {
+ content: "\f24d"; }
+
+.fa-closed-captioning:before {
+ content: "\f20a"; }
+
+.fa-cloud:before {
+ content: "\f0c2"; }
+
+.fa-cloud-download-alt:before {
+ content: "\f381"; }
+
+.fa-cloud-meatball:before {
+ content: "\f73b"; }
+
+.fa-cloud-moon:before {
+ content: "\f6c3"; }
+
+.fa-cloud-moon-rain:before {
+ content: "\f73c"; }
+
+.fa-cloud-rain:before {
+ content: "\f73d"; }
+
+.fa-cloud-showers-heavy:before {
+ content: "\f740"; }
+
+.fa-cloud-sun:before {
+ content: "\f6c4"; }
+
+.fa-cloud-sun-rain:before {
+ content: "\f743"; }
+
+.fa-cloud-upload-alt:before {
+ content: "\f382"; }
+
+.fa-cloudflare:before {
+ content: "\e07d"; }
+
+.fa-cloudscale:before {
+ content: "\f383"; }
+
+.fa-cloudsmith:before {
+ content: "\f384"; }
+
+.fa-cloudversify:before {
+ content: "\f385"; }
+
+.fa-cocktail:before {
+ content: "\f561"; }
+
+.fa-code:before {
+ content: "\f121"; }
+
+.fa-code-branch:before {
+ content: "\f126"; }
+
+.fa-codepen:before {
+ content: "\f1cb"; }
+
+.fa-codiepie:before {
+ content: "\f284"; }
+
+.fa-coffee:before {
+ content: "\f0f4"; }
+
+.fa-cog:before {
+ content: "\f013"; }
+
+.fa-cogs:before {
+ content: "\f085"; }
+
+.fa-coins:before {
+ content: "\f51e"; }
+
+.fa-columns:before {
+ content: "\f0db"; }
+
+.fa-comment:before {
+ content: "\f075"; }
+
+.fa-comment-alt:before {
+ content: "\f27a"; }
+
+.fa-comment-dollar:before {
+ content: "\f651"; }
+
+.fa-comment-dots:before {
+ content: "\f4ad"; }
+
+.fa-comment-medical:before {
+ content: "\f7f5"; }
+
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+ content: "\f4c1"; }
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+ content: "\f258"; }
+
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+ content: "\f806"; }
+
+.fa-hand-paper:before {
+ content: "\f256"; }
+
+.fa-hand-peace:before {
+ content: "\f25b"; }
+
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+ content: "\f0a7"; }
+
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+ content: "\f0a5"; }
+
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+ content: "\f0a4"; }
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+ content: "\f0a6"; }
+
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+ content: "\f25a"; }
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+ content: "\f255"; }
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+.fa-hand-scissors:before {
+ content: "\f257"; }
+
+.fa-hand-sparkles:before {
+ content: "\e05d"; }
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+.fa-hand-spock:before {
+ content: "\f259"; }
+
+.fa-hands:before {
+ content: "\f4c2"; }
+
+.fa-hands-helping:before {
+ content: "\f4c4"; }
+
+.fa-hands-wash:before {
+ content: "\e05e"; }
+
+.fa-handshake:before {
+ content: "\f2b5"; }
+
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+ content: "\e05f"; }
+
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+ content: "\e060"; }
+
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+ content: "\f6e6"; }
+
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+ content: "\f807"; }
+
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+ content: "\f292"; }
+
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+ content: "\f8c0"; }
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+ content: "\f8c1"; }
+
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+ content: "\f6e8"; }
+
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+ content: "\f0a0"; }
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+ content: "\e061"; }
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+ content: "\e062"; }
+
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+ content: "\e063"; }
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+ content: "\e064"; }
+
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+ content: "\f1dc"; }
+
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+ content: "\f025"; }
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+
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+ content: "\f004"; }
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+ content: "\f7a9"; }
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+ content: "\f21e"; }
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+ content: "\f591"; }
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+ content: "\f6ed"; }
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+ content: "\f452"; }
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+ content: "\f3b0"; }
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+ content: "\f1da"; }
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+ content: "\e07f"; }
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+
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+ content: "\f7aa"; }
+
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+ content: "\f592"; }
+
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+ content: "\f6f0"; }
+
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+ content: "\f7ab"; }
+
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+ content: "\f0f8"; }
+
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+
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+ content: "\f47e"; }
+
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+
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+ content: "\f593"; }
+
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+ content: "\f80f"; }
+
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+ content: "\f6f1"; }
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+ content: "\f27c"; }
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+ content: "\f3b2"; }
+
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+
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+ content: "\f810"; }
+
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+ content: "\f7ad"; }
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+ content: "\f86d"; }
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+ content: "\f2c1"; }
+
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+ content: "\f2c2"; }
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+ content: "\f47f"; }
+
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+ content: "\e013"; }
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+ content: "\f7ae"; }
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+ content: "\f03e"; }
+
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+ content: "\f302"; }
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+ content: "\f2d8"; }
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+ content: "\f01c"; }
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+ content: "\f03c"; }
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+ content: "\f275"; }
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+ content: "\f534"; }
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+ content: "\f129"; }
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+ content: "\f05a"; }
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+ content: "\e080"; }
+
+.fa-instagram:before {
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+ content: "\e081"; }
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+ content: "\f7af"; }
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+ content: "\f208"; }
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+ content: "\f033"; }
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+ content: "\f83a"; }
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+ content: "\f3b4"; }
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+ content: "\f3b5"; }
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+ content: "\f4e4"; }
+
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+ content: "\f669"; }
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+ content: "\f50e"; }
+
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+ content: "\f3b6"; }
+
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+ content: "\f7b1"; }
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+ content: "\f66a"; }
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+
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+ content: "\f1cc"; }
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+ content: "\f4f5"; }
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+ content: "\f11c"; }
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+ content: "\f3ba"; }
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+ content: "\f66d"; }
+
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+ content: "\f3bb"; }
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+ content: "\f3bc"; }
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+.fa-kiss:before {
+ content: "\f596"; }
+
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+ content: "\f597"; }
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+ content: "\f598"; }
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+ content: "\f535"; }
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+ content: "\f42f"; }
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+ content: "\f66f"; }
+
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+ content: "\f1ab"; }
+
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+ content: "\f109"; }
+
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+ content: "\f5fc"; }
+
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+ content: "\f812"; }
+
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+
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+ content: "\f202"; }
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+ content: "\f203"; }
+
+.fa-laugh:before {
+ content: "\f599"; }
+
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+ content: "\f59a"; }
+
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+ content: "\f59b"; }
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+ content: "\f5fd"; }
+
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+ content: "\f212"; }
+
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+ content: "\f094"; }
+
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+ content: "\f41d"; }
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+ content: "\f536"; }
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+ content: "\f537"; }
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+ content: "\f3be"; }
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+ content: "\f3bf"; }
+
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+ content: "\f1cd"; }
+
+.fa-lightbulb:before {
+ content: "\f0eb"; }
+
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+ content: "\f3c0"; }
+
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+ content: "\f0c1"; }
+
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+ content: "\f08c"; }
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+ content: "\f0e1"; }
+
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+ content: "\f2b8"; }
+
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+ content: "\f17c"; }
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+ content: "\f195"; }
+
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+ content: "\f03a"; }
+
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+ content: "\f022"; }
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+ content: "\f0cb"; }
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+ content: "\f0ca"; }
+
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+ content: "\f124"; }
+
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+ content: "\f023"; }
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+ content: "\f3c1"; }
+
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+ content: "\f309"; }
+
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+ content: "\f30a"; }
+
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+ content: "\f30b"; }
+
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+ content: "\f30c"; }
+
+.fa-low-vision:before {
+ content: "\f2a8"; }
+
+.fa-luggage-cart:before {
+ content: "\f59d"; }
+
+.fa-lungs:before {
+ content: "\f604"; }
+
+.fa-lungs-virus:before {
+ content: "\e067"; }
+
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+ content: "\f3c3"; }
+
+.fa-magento:before {
+ content: "\f3c4"; }
+
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+ content: "\f0d0"; }
+
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+ content: "\f076"; }
+
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+ content: "\f674"; }
+
+.fa-mailchimp:before {
+ content: "\f59e"; }
+
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+ content: "\f183"; }
+
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+ content: "\f50f"; }
+
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+ content: "\f279"; }
+
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+ content: "\f59f"; }
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+ content: "\f5a0"; }
+
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+ content: "\f041"; }
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+ content: "\f3c5"; }
+
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+ content: "\f276"; }
+
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+ content: "\f277"; }
+
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+ content: "\f60f"; }
+
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+ content: "\f5a1"; }
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+ content: "\f222"; }
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+ content: "\f227"; }
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+ content: "\f229"; }
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+ content: "\f22b"; }
+
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+ content: "\f22a"; }
+
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+ content: "\f6fa"; }
+
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+ content: "\f4f6"; }
+
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+ content: "\f136"; }
+
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+ content: "\f8ca"; }
+
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+ content: "\f5a2"; }
+
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+ content: "\f3c6"; }
+
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+ content: "\f23a"; }
+
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+ content: "\f3c7"; }
+
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+ content: "\f0fa"; }
+
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+ content: "\f3c8"; }
+
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+ content: "\f2e0"; }
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+ content: "\f5a3"; }
+
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+ content: "\f11a"; }
+
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+ content: "\f5a4"; }
+
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+ content: "\f5a5"; }
+
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+ content: "\f538"; }
+
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+ content: "\f7b3"; }
+
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+ content: "\f676"; }
+
+.fa-mercury:before {
+ content: "\f223"; }
+
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+ content: "\f753"; }
+
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+ content: "\e01a"; }
+
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+ content: "\f2db"; }
+
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+ content: "\f130"; }
+
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+ content: "\f3c9"; }
+
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+ content: "\f539"; }
+
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+ content: "\f131"; }
+
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+ content: "\f610"; }
+
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+ content: "\f3ca"; }
+
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+ content: "\f068"; }
+
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+ content: "\f056"; }
+
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+ content: "\f146"; }
+
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+ content: "\f7b5"; }
+
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+ content: "\f3cb"; }
+
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+ content: "\f289"; }
+
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+ content: "\e056"; }
+
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+ content: "\f3cc"; }
+
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+ content: "\f10b"; }
+
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+ content: "\f3cd"; }
+
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+ content: "\f285"; }
+
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+ content: "\f3d0"; }
+
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+ content: "\f0d6"; }
+
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+ content: "\f3d1"; }
+
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+ content: "\f53a"; }
+
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+ content: "\f53b"; }
+
+.fa-money-check:before {
+ content: "\f53c"; }
+
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+ content: "\f53d"; }
+
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+ content: "\f5a6"; }
+
+.fa-moon:before {
+ content: "\f186"; }
+
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+ content: "\f5a7"; }
+
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+ content: "\f678"; }
+
+.fa-motorcycle:before {
+ content: "\f21c"; }
+
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+ content: "\f6fc"; }
+
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+ content: "\f8cc"; }
+
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+ content: "\f245"; }
+
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+ content: "\f7b6"; }
+
+.fa-music:before {
+ content: "\f001"; }
+
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+ content: "\f3d2"; }
+
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+ content: "\f612"; }
+
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+ content: "\f6ff"; }
+
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+ content: "\f22c"; }
+
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+ content: "\f1ea"; }
+
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+ content: "\f5a8"; }
+
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+ content: "\f419"; }
+
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+ content: "\f3d3"; }
+
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+ content: "\f53e"; }
+
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+ content: "\f481"; }
+
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+ content: "\f3d4"; }
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+ content: "\f3d5"; }
+
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+ content: "\f3d6"; }
+
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+ content: "\f247"; }
+
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+ content: "\f248"; }
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+ content: "\e082"; }
+
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+ content: "\f263"; }
+
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+ content: "\f264"; }
+
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+ content: "\f613"; }
+
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+ content: "\f510"; }
+
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+ content: "\f679"; }
+
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+ content: "\f23d"; }
+
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+ content: "\f19b"; }
+
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+ content: "\f26a"; }
+
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+ content: "\f23c"; }
+
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+ content: "\f8d2"; }
+
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+ content: "\f41a"; }
+
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+ content: "\f700"; }
+
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+ content: "\f03b"; }
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+ content: "\f3d7"; }
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+ content: "\f18c"; }
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+ content: "\f815"; }
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+ content: "\f1fc"; }
+
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+ content: "\f5aa"; }
+
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+ content: "\f53f"; }
+
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+ content: "\f3d8"; }
+
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+ content: "\f482"; }
+
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+ content: "\f1d8"; }
+
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+ content: "\f0c6"; }
+
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+ content: "\f4cd"; }
+
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+ content: "\f1dd"; }
+
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+ content: "\f540"; }
+
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+ content: "\f5ab"; }
+
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+ content: "\f67b"; }
+
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+ content: "\f0ea"; }
+
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+ content: "\f3d9"; }
+
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+ content: "\f04c"; }
+
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+ content: "\f28b"; }
+
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+ content: "\f1b0"; }
+
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+ content: "\f1ed"; }
+
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+ content: "\f67c"; }
+
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+ content: "\f304"; }
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+ content: "\f305"; }
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+ content: "\f5ac"; }
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+ content: "\f5ad"; }
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+ content: "\f14b"; }
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+ content: "\f303"; }
+
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+ content: "\f5ae"; }
+
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+ content: "\f704"; }
+
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+ content: "\e068"; }
+
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+ content: "\f4ce"; }
+
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+ content: "\f816"; }
+
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+ content: "\e083"; }
+
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+ content: "\f295"; }
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+ content: "\f541"; }
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+ content: "\f3da"; }
+
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+ content: "\f756"; }
+
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+ content: "\f3db"; }
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+ content: "\f3dc"; }
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+ content: "\f511"; }
+
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+ content: "\f095"; }
+
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+ content: "\f879"; }
+
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+ content: "\f3dd"; }
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+ content: "\f098"; }
+
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+ content: "\f87b"; }
+
+.fa-phone-volume:before {
+ content: "\f2a0"; }
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+ content: "\f072"; }
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+ content: "\f5af"; }
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+
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+ content: "\f144"; }
+
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+ content: "\f1e6"; }
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+ content: "\f2fe"; }
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+ content: "\f75a"; }
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+ content: "\f619"; }
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+ content: "\f011"; }
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+ content: "\f683"; }
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+ content: "\f684"; }
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+ content: "\f5b1"; }
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+ content: "\f485"; }
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+ content: "\f128"; }
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+ content: "\f059"; }
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+ content: "\f2c4"; }
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+ content: "\f10d"; }
+
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+ content: "\f10e"; }
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+ content: "\f687"; }
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+ content: "\f4f7"; }
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+ content: "\f7b9"; }
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+ content: "\f1b8"; }
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+ content: "\f1a2"; }
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+ content: "\f010"; }
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+ content: "\e057"; }
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+ content: "\f5b6"; }
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+ content: "\f4d9"; }
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+ content: "\f7c6"; }
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+ content: "\f7c9"; }
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+ content: "\f216"; }
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+ content: "\f160"; }
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+ content: "\f7d3"; }
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+ content: "\f3f3"; }
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+ content: "\f717"; }
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+ content: "\f5bc"; }
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+ content: "\f1bc"; }
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+ content: "\f5bd"; }
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+ content: "\f5be"; }
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+ content: "\f842"; }
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+ content: "\f5bf"; }
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+ content: "\f005"; }
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+ content: "\f699"; }
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+ content: "\f089"; }
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+ content: "\f5c0"; }
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+ content: "\f69a"; }
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+ content: "\f621"; }
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+ content: "\f3f5"; }
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+ content: "\f1b6"; }
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+ content: "\f3f6"; }
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+ content: "\f048"; }
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+ content: "\f051"; }
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+ content: "\f0f1"; }
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+ content: "\f249"; }
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+ content: "\f04d"; }
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+ content: "\f428"; }
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+ content: "\f550"; }
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+ content: "\f21d"; }
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+ content: "\f0cc"; }
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+ content: "\f429"; }
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+ content: "\f42a"; }
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+ content: "\f551"; }
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+ content: "\f3f8"; }
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+ content: "\f1a4"; }
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+ content: "\f1a3"; }
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+ content: "\f12c"; }
+
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+ content: "\f239"; }
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+ content: "\f0f2"; }
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+ content: "\f5c1"; }
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+ content: "\f185"; }
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+ content: "\f2dd"; }
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+ content: "\f12b"; }
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+ content: "\f3f9"; }
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+ content: "\f5c2"; }
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+ content: "\f7d6"; }
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+ content: "\f5c3"; }
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+ content: "\f8e1"; }
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+ content: "\f5c4"; }
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+ content: "\f5c5"; }
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+ content: "\f83d"; }
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+ content: "\f69b"; }
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+ content: "\f021"; }
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+ content: "\f2f1"; }
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+ content: "\f48e"; }
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+ content: "\f0ce"; }
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+ content: "\f45d"; }
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+ content: "\f10a"; }
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+ content: "\f490"; }
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+ content: "\f3fd"; }
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+ content: "\f02b"; }
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+ content: "\f02c"; }
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+ content: "\f4db"; }
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+ content: "\f0ae"; }
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+ content: "\f1ba"; }
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+ content: "\f4f9"; }
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+ content: "\f62e"; }
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+ content: "\f62f"; }
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+ content: "\f2c6"; }
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+ content: "\f3fe"; }
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+ content: "\f769"; }
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+ content: "\f76b"; }
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+ content: "\f1d5"; }
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+ content: "\f7d7"; }
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+ content: "\f120"; }
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+ content: "\f034"; }
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+ content: "\f035"; }
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+ content: "\f009"; }
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+ content: "\f00b"; }
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+ content: "\f69d"; }
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+ content: "\f630"; }
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+ content: "\f5c6"; }
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+ content: "\f2b2"; }
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+ content: "\f491"; }
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+ content: "\f2cb"; }
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+ content: "\f2c7"; }
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+ content: "\f2c9"; }
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+ content: "\f2ca"; }
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+ content: "\f2c8"; }
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+ content: "\f731"; }
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+ content: "\f165"; }
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+ content: "\f164"; }
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+ content: "\e07b"; }
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+ content: "\f00d"; }
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+ content: "\f057"; }
+
+.fa-tint:before {
+ content: "\f043"; }
+
+.fa-tint-slash:before {
+ content: "\f5c7"; }
+
+.fa-tired:before {
+ content: "\f5c8"; }
+
+.fa-toggle-off:before {
+ content: "\f204"; }
+
+.fa-toggle-on:before {
+ content: "\f205"; }
+
+.fa-toilet:before {
+ content: "\f7d8"; }
+
+.fa-toilet-paper:before {
+ content: "\f71e"; }
+
+.fa-toilet-paper-slash:before {
+ content: "\e072"; }
+
+.fa-toolbox:before {
+ content: "\f552"; }
+
+.fa-tools:before {
+ content: "\f7d9"; }
+
+.fa-tooth:before {
+ content: "\f5c9"; }
+
+.fa-torah:before {
+ content: "\f6a0"; }
+
+.fa-torii-gate:before {
+ content: "\f6a1"; }
+
+.fa-tractor:before {
+ content: "\f722"; }
+
+.fa-trade-federation:before {
+ content: "\f513"; }
+
+.fa-trademark:before {
+ content: "\f25c"; }
+
+.fa-traffic-light:before {
+ content: "\f637"; }
+
+.fa-trailer:before {
+ content: "\e041"; }
+
+.fa-train:before {
+ content: "\f238"; }
+
+.fa-tram:before {
+ content: "\f7da"; }
+
+.fa-transgender:before {
+ content: "\f224"; }
+
+.fa-transgender-alt:before {
+ content: "\f225"; }
+
+.fa-trash:before {
+ content: "\f1f8"; }
+
+.fa-trash-alt:before {
+ content: "\f2ed"; }
+
+.fa-trash-restore:before {
+ content: "\f829"; }
+
+.fa-trash-restore-alt:before {
+ content: "\f82a"; }
+
+.fa-tree:before {
+ content: "\f1bb"; }
+
+.fa-trello:before {
+ content: "\f181"; }
+
+.fa-tripadvisor:before {
+ content: "\f262"; }
+
+.fa-trophy:before {
+ content: "\f091"; }
+
+.fa-truck:before {
+ content: "\f0d1"; }
+
+.fa-truck-loading:before {
+ content: "\f4de"; }
+
+.fa-truck-monster:before {
+ content: "\f63b"; }
+
+.fa-truck-moving:before {
+ content: "\f4df"; }
+
+.fa-truck-pickup:before {
+ content: "\f63c"; }
+
+.fa-tshirt:before {
+ content: "\f553"; }
+
+.fa-tty:before {
+ content: "\f1e4"; }
+
+.fa-tumblr:before {
+ content: "\f173"; }
+
+.fa-tumblr-square:before {
+ content: "\f174"; }
+
+.fa-tv:before {
+ content: "\f26c"; }
+
+.fa-twitch:before {
+ content: "\f1e8"; }
+
+.fa-twitter:before {
+ content: "\f099"; }
+
+.fa-twitter-square:before {
+ content: "\f081"; }
+
+.fa-typo3:before {
+ content: "\f42b"; }
+
+.fa-uber:before {
+ content: "\f402"; }
+
+.fa-ubuntu:before {
+ content: "\f7df"; }
+
+.fa-uikit:before {
+ content: "\f403"; }
+
+.fa-umbraco:before {
+ content: "\f8e8"; }
+
+.fa-umbrella:before {
+ content: "\f0e9"; }
+
+.fa-umbrella-beach:before {
+ content: "\f5ca"; }
+
+.fa-uncharted:before {
+ content: "\e084"; }
+
+.fa-underline:before {
+ content: "\f0cd"; }
+
+.fa-undo:before {
+ content: "\f0e2"; }
+
+.fa-undo-alt:before {
+ content: "\f2ea"; }
+
+.fa-uniregistry:before {
+ content: "\f404"; }
+
+.fa-unity:before {
+ content: "\e049"; }
+
+.fa-universal-access:before {
+ content: "\f29a"; }
+
+.fa-university:before {
+ content: "\f19c"; }
+
+.fa-unlink:before {
+ content: "\f127"; }
+
+.fa-unlock:before {
+ content: "\f09c"; }
+
+.fa-unlock-alt:before {
+ content: "\f13e"; }
+
+.fa-unsplash:before {
+ content: "\e07c"; }
+
+.fa-untappd:before {
+ content: "\f405"; }
+
+.fa-upload:before {
+ content: "\f093"; }
+
+.fa-ups:before {
+ content: "\f7e0"; }
+
+.fa-usb:before {
+ content: "\f287"; }
+
+.fa-user:before {
+ content: "\f007"; }
+
+.fa-user-alt:before {
+ content: "\f406"; }
+
+.fa-user-alt-slash:before {
+ content: "\f4fa"; }
+
+.fa-user-astronaut:before {
+ content: "\f4fb"; }
+
+.fa-user-check:before {
+ content: "\f4fc"; }
+
+.fa-user-circle:before {
+ content: "\f2bd"; }
+
+.fa-user-clock:before {
+ content: "\f4fd"; }
+
+.fa-user-cog:before {
+ content: "\f4fe"; }
+
+.fa-user-edit:before {
+ content: "\f4ff"; }
+
+.fa-user-friends:before {
+ content: "\f500"; }
+
+.fa-user-graduate:before {
+ content: "\f501"; }
+
+.fa-user-injured:before {
+ content: "\f728"; }
+
+.fa-user-lock:before {
+ content: "\f502"; }
+
+.fa-user-md:before {
+ content: "\f0f0"; }
+
+.fa-user-minus:before {
+ content: "\f503"; }
+
+.fa-user-ninja:before {
+ content: "\f504"; }
+
+.fa-user-nurse:before {
+ content: "\f82f"; }
+
+.fa-user-plus:before {
+ content: "\f234"; }
+
+.fa-user-secret:before {
+ content: "\f21b"; }
+
+.fa-user-shield:before {
+ content: "\f505"; }
+
+.fa-user-slash:before {
+ content: "\f506"; }
+
+.fa-user-tag:before {
+ content: "\f507"; }
+
+.fa-user-tie:before {
+ content: "\f508"; }
+
+.fa-user-times:before {
+ content: "\f235"; }
+
+.fa-users:before {
+ content: "\f0c0"; }
+
+.fa-users-cog:before {
+ content: "\f509"; }
+
+.fa-users-slash:before {
+ content: "\e073"; }
+
+.fa-usps:before {
+ content: "\f7e1"; }
+
+.fa-ussunnah:before {
+ content: "\f407"; }
+
+.fa-utensil-spoon:before {
+ content: "\f2e5"; }
+
+.fa-utensils:before {
+ content: "\f2e7"; }
+
+.fa-vaadin:before {
+ content: "\f408"; }
+
+.fa-vector-square:before {
+ content: "\f5cb"; }
+
+.fa-venus:before {
+ content: "\f221"; }
+
+.fa-venus-double:before {
+ content: "\f226"; }
+
+.fa-venus-mars:before {
+ content: "\f228"; }
+
+.fa-vest:before {
+ content: "\e085"; }
+
+.fa-vest-patches:before {
+ content: "\e086"; }
+
+.fa-viacoin:before {
+ content: "\f237"; }
+
+.fa-viadeo:before {
+ content: "\f2a9"; }
+
+.fa-viadeo-square:before {
+ content: "\f2aa"; }
+
+.fa-vial:before {
+ content: "\f492"; }
+
+.fa-vials:before {
+ content: "\f493"; }
+
+.fa-viber:before {
+ content: "\f409"; }
+
+.fa-video:before {
+ content: "\f03d"; }
+
+.fa-video-slash:before {
+ content: "\f4e2"; }
+
+.fa-vihara:before {
+ content: "\f6a7"; }
+
+.fa-vimeo:before {
+ content: "\f40a"; }
+
+.fa-vimeo-square:before {
+ content: "\f194"; }
+
+.fa-vimeo-v:before {
+ content: "\f27d"; }
+
+.fa-vine:before {
+ content: "\f1ca"; }
+
+.fa-virus:before {
+ content: "\e074"; }
+
+.fa-virus-slash:before {
+ content: "\e075"; }
+
+.fa-viruses:before {
+ content: "\e076"; }
+
+.fa-vk:before {
+ content: "\f189"; }
+
+.fa-vnv:before {
+ content: "\f40b"; }
+
+.fa-voicemail:before {
+ content: "\f897"; }
+
+.fa-volleyball-ball:before {
+ content: "\f45f"; }
+
+.fa-volume-down:before {
+ content: "\f027"; }
+
+.fa-volume-mute:before {
+ content: "\f6a9"; }
+
+.fa-volume-off:before {
+ content: "\f026"; }
+
+.fa-volume-up:before {
+ content: "\f028"; }
+
+.fa-vote-yea:before {
+ content: "\f772"; }
+
+.fa-vr-cardboard:before {
+ content: "\f729"; }
+
+.fa-vuejs:before {
+ content: "\f41f"; }
+
+.fa-walking:before {
+ content: "\f554"; }
+
+.fa-wallet:before {
+ content: "\f555"; }
+
+.fa-warehouse:before {
+ content: "\f494"; }
+
+.fa-watchman-monitoring:before {
+ content: "\e087"; }
+
+.fa-water:before {
+ content: "\f773"; }
+
+.fa-wave-square:before {
+ content: "\f83e"; }
+
+.fa-waze:before {
+ content: "\f83f"; }
+
+.fa-weebly:before {
+ content: "\f5cc"; }
+
+.fa-weibo:before {
+ content: "\f18a"; }
+
+.fa-weight:before {
+ content: "\f496"; }
+
+.fa-weight-hanging:before {
+ content: "\f5cd"; }
+
+.fa-weixin:before {
+ content: "\f1d7"; }
+
+.fa-whatsapp:before {
+ content: "\f232"; }
+
+.fa-whatsapp-square:before {
+ content: "\f40c"; }
+
+.fa-wheelchair:before {
+ content: "\f193"; }
+
+.fa-whmcs:before {
+ content: "\f40d"; }
+
+.fa-wifi:before {
+ content: "\f1eb"; }
+
+.fa-wikipedia-w:before {
+ content: "\f266"; }
+
+.fa-wind:before {
+ content: "\f72e"; }
+
+.fa-window-close:before {
+ content: "\f410"; }
+
+.fa-window-maximize:before {
+ content: "\f2d0"; }
+
+.fa-window-minimize:before {
+ content: "\f2d1"; }
+
+.fa-window-restore:before {
+ content: "\f2d2"; }
+
+.fa-windows:before {
+ content: "\f17a"; }
+
+.fa-wine-bottle:before {
+ content: "\f72f"; }
+
+.fa-wine-glass:before {
+ content: "\f4e3"; }
+
+.fa-wine-glass-alt:before {
+ content: "\f5ce"; }
+
+.fa-wix:before {
+ content: "\f5cf"; }
+
+.fa-wizards-of-the-coast:before {
+ content: "\f730"; }
+
+.fa-wodu:before {
+ content: "\e088"; }
+
+.fa-wolf-pack-battalion:before {
+ content: "\f514"; }
+
+.fa-won-sign:before {
+ content: "\f159"; }
+
+.fa-wordpress:before {
+ content: "\f19a"; }
+
+.fa-wordpress-simple:before {
+ content: "\f411"; }
+
+.fa-wpbeginner:before {
+ content: "\f297"; }
+
+.fa-wpexplorer:before {
+ content: "\f2de"; }
+
+.fa-wpforms:before {
+ content: "\f298"; }
+
+.fa-wpressr:before {
+ content: "\f3e4"; }
+
+.fa-wrench:before {
+ content: "\f0ad"; }
+
+.fa-x-ray:before {
+ content: "\f497"; }
+
+.fa-xbox:before {
+ content: "\f412"; }
+
+.fa-xing:before {
+ content: "\f168"; }
+
+.fa-xing-square:before {
+ content: "\f169"; }
+
+.fa-y-combinator:before {
+ content: "\f23b"; }
+
+.fa-yahoo:before {
+ content: "\f19e"; }
+
+.fa-yammer:before {
+ content: "\f840"; }
+
+.fa-yandex:before {
+ content: "\f413"; }
+
+.fa-yandex-international:before {
+ content: "\f414"; }
+
+.fa-yarn:before {
+ content: "\f7e3"; }
+
+.fa-yelp:before {
+ content: "\f1e9"; }
+
+.fa-yen-sign:before {
+ content: "\f157"; }
+
+.fa-yin-yang:before {
+ content: "\f6ad"; }
+
+.fa-yoast:before {
+ content: "\f2b1"; }
+
+.fa-youtube:before {
+ content: "\f167"; }
+
+.fa-youtube-square:before {
+ content: "\f431"; }
+
+.fa-zhihu:before {
+ content: "\f63f"; }
+
+.sr-only {
+ border: 0;
+ clip: rect(0, 0, 0, 0);
+ height: 1px;
+ margin: -1px;
+ overflow: hidden;
+ padding: 0;
+ position: absolute;
+ width: 1px; }
+
+.sr-only-focusable:active, .sr-only-focusable:focus {
+ clip: auto;
+ height: auto;
+ margin: 0;
+ overflow: visible;
+ position: static;
+ width: auto; }
+@font-face {
+ font-family: 'Font Awesome 5 Brands';
+ font-style: normal;
+ font-weight: 400;
+ font-display: block;
+ src: url("../webfonts/fa-brands-400.eot");
+ src: url("../webfonts/fa-brands-400.eot?#iefix") format("embedded-opentype"), url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.woff") format("woff"), url("../webfonts/fa-brands-400.ttf") format("truetype"), url("../webfonts/fa-brands-400.svg#fontawesome") format("svg"); }
+
+.fab {
+ font-family: 'Font Awesome 5 Brands';
+ font-weight: 400; }
+@font-face {
+ font-family: 'Font Awesome 5 Free';
+ font-style: normal;
+ font-weight: 400;
+ font-display: block;
+ src: url("../webfonts/fa-regular-400.eot");
+ src: url("../webfonts/fa-regular-400.eot?#iefix") format("embedded-opentype"), url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.woff") format("woff"), url("../webfonts/fa-regular-400.ttf") format("truetype"), url("../webfonts/fa-regular-400.svg#fontawesome") format("svg"); }
+
+.far {
+ font-family: 'Font Awesome 5 Free';
+ font-weight: 400; }
+@font-face {
+ font-family: 'Font Awesome 5 Free';
+ font-style: normal;
+ font-weight: 900;
+ font-display: block;
+ src: url("../webfonts/fa-solid-900.eot");
+ src: url("../webfonts/fa-solid-900.eot?#iefix") format("embedded-opentype"), url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.woff") format("woff"), url("../webfonts/fa-solid-900.ttf") format("truetype"), url("../webfonts/fa-solid-900.svg#fontawesome") format("svg"); }
+
+.fa,
+.fas {
+ font-family: 'Font Awesome 5 Free';
+ font-weight: 900; }
diff --git a/assets/fa/css/all.min.css b/assets/fa/css/all.min.css
new file mode 100644
index 0000000..656a507
--- /dev/null
+++ b/assets/fa/css/all.min.css
@@ -0,0 +1,5 @@
+/*!
+ * Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ */
+.fa,.fab,.fad,.fal,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:inline-block;font-style:normal;font-variant:normal;text-rendering:auto;line-height:1}.fa-lg{font-size:1.33333em;line-height:.75em;vertical-align:-.0667em}.fa-xs{font-size:.75em}.fa-sm{font-size:.875em}.fa-1x{font-size:1em}.fa-2x{font-size:2em}.fa-3x{font-size:3em}.fa-4x{font-size:4em}.fa-5x{font-size:5em}.fa-6x{font-size:6em}.fa-7x{font-size:7em}.fa-8x{font-size:8em}.fa-9x{font-size: [...]
\ No newline at end of file
diff --git a/assets/fa/css/brands.css b/assets/fa/css/brands.css
new file mode 100644
index 0000000..a91c544
--- /dev/null
+++ b/assets/fa/css/brands.css
@@ -0,0 +1,15 @@
+/*!
+ * Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ */
+@font-face {
+ font-family: 'Font Awesome 5 Brands';
+ font-style: normal;
+ font-weight: 400;
+ font-display: block;
+ src: url("../webfonts/fa-brands-400.eot");
+ src: url("../webfonts/fa-brands-400.eot?#iefix") format("embedded-opentype"), url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.woff") format("woff"), url("../webfonts/fa-brands-400.ttf") format("truetype"), url("../webfonts/fa-brands-400.svg#fontawesome") format("svg"); }
+
+.fab {
+ font-family: 'Font Awesome 5 Brands';
+ font-weight: 400; }
diff --git a/assets/fa/css/brands.min.css b/assets/fa/css/brands.min.css
new file mode 100644
index 0000000..708c5fb
--- /dev/null
+++ b/assets/fa/css/brands.min.css
@@ -0,0 +1,5 @@
+/*!
+ * Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ */
+@font-face{font-family:"Font Awesome 5 Brands";font-style:normal;font-weight:400;font-display:block;src:url(../webfonts/fa-brands-400.eot);src:url(../webfonts/fa-brands-400.eot?#iefix) format("embedded-opentype"),url(../webfonts/fa-brands-400.woff2) format("woff2"),url(../webfonts/fa-brands-400.woff) format("woff"),url(../webfonts/fa-brands-400.ttf) format("truetype"),url(../webfonts/fa-brands-400.svg#fontawesome) format("svg")}.fab{font-family:"Font Awesome 5 Brands";font-weight:400}
\ No newline at end of file
diff --git a/assets/fa/css/fontawesome.css b/assets/fa/css/fontawesome.css
new file mode 100644
index 0000000..79b095b
--- /dev/null
+++ b/assets/fa/css/fontawesome.css
@@ -0,0 +1,4585 @@
+/*!
+ * Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ */
+.fa,
+.fas,
+.far,
+.fal,
+.fad,
+.fab {
+ -moz-osx-font-smoothing: grayscale;
+ -webkit-font-smoothing: antialiased;
+ display: inline-block;
+ font-style: normal;
+ font-variant: normal;
+ text-rendering: auto;
+ line-height: 1; }
+
+.fa-lg {
+ font-size: 1.33333em;
+ line-height: 0.75em;
+ vertical-align: -.0667em; }
+
+.fa-xs {
+ font-size: .75em; }
+
+.fa-sm {
+ font-size: .875em; }
+
+.fa-1x {
+ font-size: 1em; }
+
+.fa-2x {
+ font-size: 2em; }
+
+.fa-3x {
+ font-size: 3em; }
+
+.fa-4x {
+ font-size: 4em; }
+
+.fa-5x {
+ font-size: 5em; }
+
+.fa-6x {
+ font-size: 6em; }
+
+.fa-7x {
+ font-size: 7em; }
+
+.fa-8x {
+ font-size: 8em; }
+
+.fa-9x {
+ font-size: 9em; }
+
+.fa-10x {
+ font-size: 10em; }
+
+.fa-fw {
+ text-align: center;
+ width: 1.25em; }
+
+.fa-ul {
+ list-style-type: none;
+ margin-left: 2.5em;
+ padding-left: 0; }
+ .fa-ul > li {
+ position: relative; }
+
+.fa-li {
+ left: -2em;
+ position: absolute;
+ text-align: center;
+ width: 2em;
+ line-height: inherit; }
+
+.fa-border {
+ border: solid 0.08em #eee;
+ border-radius: .1em;
+ padding: .2em .25em .15em; }
+
+.fa-pull-left {
+ float: left; }
+
+.fa-pull-right {
+ float: right; }
+
+.fa.fa-pull-left,
+.fas.fa-pull-left,
+.far.fa-pull-left,
+.fal.fa-pull-left,
+.fab.fa-pull-left {
+ margin-right: .3em; }
+
+.fa.fa-pull-right,
+.fas.fa-pull-right,
+.far.fa-pull-right,
+.fal.fa-pull-right,
+.fab.fa-pull-right {
+ margin-left: .3em; }
+
+.fa-spin {
+ -webkit-animation: fa-spin 2s infinite linear;
+ animation: fa-spin 2s infinite linear; }
+
+.fa-pulse {
+ -webkit-animation: fa-spin 1s infinite steps(8);
+ animation: fa-spin 1s infinite steps(8); }
+
+@-webkit-keyframes fa-spin {
+ 0% {
+ -webkit-transform: rotate(0deg);
+ transform: rotate(0deg); }
+ 100% {
+ -webkit-transform: rotate(360deg);
+ transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+ 0% {
+ -webkit-transform: rotate(0deg);
+ transform: rotate(0deg); }
+ 100% {
+ -webkit-transform: rotate(360deg);
+ transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
+ -webkit-transform: rotate(90deg);
+ transform: rotate(90deg); }
+
+.fa-rotate-180 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
+ -webkit-transform: rotate(180deg);
+ transform: rotate(180deg); }
+
+.fa-rotate-270 {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
+ -webkit-transform: rotate(270deg);
+ transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
+ -webkit-transform: scale(-1, 1);
+ transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
+ -webkit-transform: scale(1, -1);
+ transform: scale(1, -1); }
+
+.fa-flip-both, .fa-flip-horizontal.fa-flip-vertical {
+ -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
+ -webkit-transform: scale(-1, -1);
+ transform: scale(-1, -1); }
+
+:root .fa-rotate-90,
+:root .fa-rotate-180,
+:root .fa-rotate-270,
+:root .fa-flip-horizontal,
+:root .fa-flip-vertical,
+:root .fa-flip-both {
+ -webkit-filter: none;
+ filter: none; }
+
+.fa-stack {
+ display: inline-block;
+ height: 2em;
+ line-height: 2em;
+ position: relative;
+ vertical-align: middle;
+ width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+ left: 0;
+ position: absolute;
+ text-align: center;
+ width: 100%; }
+
+.fa-stack-1x {
+ line-height: inherit; }
+
+.fa-stack-2x {
+ font-size: 2em; }
+
+.fa-inverse {
+ color: #fff; }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+.fa-500px:before {
+ content: "\f26e"; }
+
+.fa-accessible-icon:before {
+ content: "\f368"; }
+
+.fa-accusoft:before {
+ content: "\f369"; }
+
+.fa-acquisitions-incorporated:before {
+ content: "\f6af"; }
+
+.fa-ad:before {
+ content: "\f641"; }
+
+.fa-address-book:before {
+ content: "\f2b9"; }
+
+.fa-address-card:before {
+ content: "\f2bb"; }
+
+.fa-adjust:before {
+ content: "\f042"; }
+
+.fa-adn:before {
+ content: "\f170"; }
+
+.fa-adversal:before {
+ content: "\f36a"; }
+
+.fa-affiliatetheme:before {
+ content: "\f36b"; }
+
+.fa-air-freshener:before {
+ content: "\f5d0"; }
+
+.fa-airbnb:before {
+ content: "\f834"; }
+
+.fa-algolia:before {
+ content: "\f36c"; }
+
+.fa-align-center:before {
+ content: "\f037"; }
+
+.fa-align-justify:before {
+ content: "\f039"; }
+
+.fa-align-left:before {
+ content: "\f036"; }
+
+.fa-align-right:before {
+ content: "\f038"; }
+
+.fa-alipay:before {
+ content: "\f642"; }
+
+.fa-allergies:before {
+ content: "\f461"; }
+
+.fa-amazon:before {
+ content: "\f270"; }
+
+.fa-amazon-pay:before {
+ content: "\f42c"; }
+
+.fa-ambulance:before {
+ content: "\f0f9"; }
+
+.fa-american-sign-language-interpreting:before {
+ content: "\f2a3"; }
+
+.fa-amilia:before {
+ content: "\f36d"; }
+
+.fa-anchor:before {
+ content: "\f13d"; }
+
+.fa-android:before {
+ content: "\f17b"; }
+
+.fa-angellist:before {
+ content: "\f209"; }
+
+.fa-angle-double-down:before {
+ content: "\f103"; }
+
+.fa-angle-double-left:before {
+ content: "\f100"; }
+
+.fa-angle-double-right:before {
+ content: "\f101"; }
+
+.fa-angle-double-up:before {
+ content: "\f102"; }
+
+.fa-angle-down:before {
+ content: "\f107"; }
+
+.fa-angle-left:before {
+ content: "\f104"; }
+
+.fa-angle-right:before {
+ content: "\f105"; }
+
+.fa-angle-up:before {
+ content: "\f106"; }
+
+.fa-angry:before {
+ content: "\f556"; }
+
+.fa-angrycreative:before {
+ content: "\f36e"; }
+
+.fa-angular:before {
+ content: "\f420"; }
+
+.fa-ankh:before {
+ content: "\f644"; }
+
+.fa-app-store:before {
+ content: "\f36f"; }
+
+.fa-app-store-ios:before {
+ content: "\f370"; }
+
+.fa-apper:before {
+ content: "\f371"; }
+
+.fa-apple:before {
+ content: "\f179"; }
+
+.fa-apple-alt:before {
+ content: "\f5d1"; }
+
+.fa-apple-pay:before {
+ content: "\f415"; }
+
+.fa-archive:before {
+ content: "\f187"; }
+
+.fa-archway:before {
+ content: "\f557"; }
+
+.fa-arrow-alt-circle-down:before {
+ content: "\f358"; }
+
+.fa-arrow-alt-circle-left:before {
+ content: "\f359"; }
+
+.fa-arrow-alt-circle-right:before {
+ content: "\f35a"; }
+
+.fa-arrow-alt-circle-up:before {
+ content: "\f35b"; }
+
+.fa-arrow-circle-down:before {
+ content: "\f0ab"; }
+
+.fa-arrow-circle-left:before {
+ content: "\f0a8"; }
+
+.fa-arrow-circle-right:before {
+ content: "\f0a9"; }
+
+.fa-arrow-circle-up:before {
+ content: "\f0aa"; }
+
+.fa-arrow-down:before {
+ content: "\f063"; }
+
+.fa-arrow-left:before {
+ content: "\f060"; }
+
+.fa-arrow-right:before {
+ content: "\f061"; }
+
+.fa-arrow-up:before {
+ content: "\f062"; }
+
+.fa-arrows-alt:before {
+ content: "\f0b2"; }
+
+.fa-arrows-alt-h:before {
+ content: "\f337"; }
+
+.fa-arrows-alt-v:before {
+ content: "\f338"; }
+
+.fa-artstation:before {
+ content: "\f77a"; }
+
+.fa-assistive-listening-systems:before {
+ content: "\f2a2"; }
+
+.fa-asterisk:before {
+ content: "\f069"; }
+
+.fa-asymmetrik:before {
+ content: "\f372"; }
+
+.fa-at:before {
+ content: "\f1fa"; }
+
+.fa-atlas:before {
+ content: "\f558"; }
+
+.fa-atlassian:before {
+ content: "\f77b"; }
+
+.fa-atom:before {
+ content: "\f5d2"; }
+
+.fa-audible:before {
+ content: "\f373"; }
+
+.fa-audio-description:before {
+ content: "\f29e"; }
+
+.fa-autoprefixer:before {
+ content: "\f41c"; }
+
+.fa-avianex:before {
+ content: "\f374"; }
+
+.fa-aviato:before {
+ content: "\f421"; }
+
+.fa-award:before {
+ content: "\f559"; }
+
+.fa-aws:before {
+ content: "\f375"; }
+
+.fa-baby:before {
+ content: "\f77c"; }
+
+.fa-baby-carriage:before {
+ content: "\f77d"; }
+
+.fa-backspace:before {
+ content: "\f55a"; }
+
+.fa-backward:before {
+ content: "\f04a"; }
+
+.fa-bacon:before {
+ content: "\f7e5"; }
+
+.fa-bacteria:before {
+ content: "\e059"; }
+
+.fa-bacterium:before {
+ content: "\e05a"; }
+
+.fa-bahai:before {
+ content: "\f666"; }
+
+.fa-balance-scale:before {
+ content: "\f24e"; }
+
+.fa-balance-scale-left:before {
+ content: "\f515"; }
+
+.fa-balance-scale-right:before {
+ content: "\f516"; }
+
+.fa-ban:before {
+ content: "\f05e"; }
+
+.fa-band-aid:before {
+ content: "\f462"; }
+
+.fa-bandcamp:before {
+ content: "\f2d5"; }
+
+.fa-barcode:before {
+ content: "\f02a"; }
+
+.fa-bars:before {
+ content: "\f0c9"; }
+
+.fa-baseball-ball:before {
+ content: "\f433"; }
+
+.fa-basketball-ball:before {
+ content: "\f434"; }
+
+.fa-bath:before {
+ content: "\f2cd"; }
+
+.fa-battery-empty:before {
+ content: "\f244"; }
+
+.fa-battery-full:before {
+ content: "\f240"; }
+
+.fa-battery-half:before {
+ content: "\f242"; }
+
+.fa-battery-quarter:before {
+ content: "\f243"; }
+
+.fa-battery-three-quarters:before {
+ content: "\f241"; }
+
+.fa-battle-net:before {
+ content: "\f835"; }
+
+.fa-bed:before {
+ content: "\f236"; }
+
+.fa-beer:before {
+ content: "\f0fc"; }
+
+.fa-behance:before {
+ content: "\f1b4"; }
+
+.fa-behance-square:before {
+ content: "\f1b5"; }
+
+.fa-bell:before {
+ content: "\f0f3"; }
+
+.fa-bell-slash:before {
+ content: "\f1f6"; }
+
+.fa-bezier-curve:before {
+ content: "\f55b"; }
+
+.fa-bible:before {
+ content: "\f647"; }
+
+.fa-bicycle:before {
+ content: "\f206"; }
+
+.fa-biking:before {
+ content: "\f84a"; }
+
+.fa-bimobject:before {
+ content: "\f378"; }
+
+.fa-binoculars:before {
+ content: "\f1e5"; }
+
+.fa-biohazard:before {
+ content: "\f780"; }
+
+.fa-birthday-cake:before {
+ content: "\f1fd"; }
+
+.fa-bitbucket:before {
+ content: "\f171"; }
+
+.fa-bitcoin:before {
+ content: "\f379"; }
+
+.fa-bity:before {
+ content: "\f37a"; }
+
+.fa-black-tie:before {
+ content: "\f27e"; }
+
+.fa-blackberry:before {
+ content: "\f37b"; }
+
+.fa-blender:before {
+ content: "\f517"; }
+
+.fa-blender-phone:before {
+ content: "\f6b6"; }
+
+.fa-blind:before {
+ content: "\f29d"; }
+
+.fa-blog:before {
+ content: "\f781"; }
+
+.fa-blogger:before {
+ content: "\f37c"; }
+
+.fa-blogger-b:before {
+ content: "\f37d"; }
+
+.fa-bluetooth:before {
+ content: "\f293"; }
+
+.fa-bluetooth-b:before {
+ content: "\f294"; }
+
+.fa-bold:before {
+ content: "\f032"; }
+
+.fa-bolt:before {
+ content: "\f0e7"; }
+
+.fa-bomb:before {
+ content: "\f1e2"; }
+
+.fa-bone:before {
+ content: "\f5d7"; }
+
+.fa-bong:before {
+ content: "\f55c"; }
+
+.fa-book:before {
+ content: "\f02d"; }
+
+.fa-book-dead:before {
+ content: "\f6b7"; }
+
+.fa-book-medical:before {
+ content: "\f7e6"; }
+
+.fa-book-open:before {
+ content: "\f518"; }
+
+.fa-book-reader:before {
+ content: "\f5da"; }
+
+.fa-bookmark:before {
+ content: "\f02e"; }
+
+.fa-bootstrap:before {
+ content: "\f836"; }
+
+.fa-border-all:before {
+ content: "\f84c"; }
+
+.fa-border-none:before {
+ content: "\f850"; }
+
+.fa-border-style:before {
+ content: "\f853"; }
+
+.fa-bowling-ball:before {
+ content: "\f436"; }
+
+.fa-box:before {
+ content: "\f466"; }
+
+.fa-box-open:before {
+ content: "\f49e"; }
+
+.fa-box-tissue:before {
+ content: "\e05b"; }
+
+.fa-boxes:before {
+ content: "\f468"; }
+
+.fa-braille:before {
+ content: "\f2a1"; }
+
+.fa-brain:before {
+ content: "\f5dc"; }
+
+.fa-bread-slice:before {
+ content: "\f7ec"; }
+
+.fa-briefcase:before {
+ content: "\f0b1"; }
+
+.fa-briefcase-medical:before {
+ content: "\f469"; }
+
+.fa-broadcast-tower:before {
+ content: "\f519"; }
+
+.fa-broom:before {
+ content: "\f51a"; }
+
+.fa-brush:before {
+ content: "\f55d"; }
+
+.fa-btc:before {
+ content: "\f15a"; }
+
+.fa-buffer:before {
+ content: "\f837"; }
+
+.fa-bug:before {
+ content: "\f188"; }
+
+.fa-building:before {
+ content: "\f1ad"; }
+
+.fa-bullhorn:before {
+ content: "\f0a1"; }
+
+.fa-bullseye:before {
+ content: "\f140"; }
+
+.fa-burn:before {
+ content: "\f46a"; }
+
+.fa-buromobelexperte:before {
+ content: "\f37f"; }
+
+.fa-bus:before {
+ content: "\f207"; }
+
+.fa-bus-alt:before {
+ content: "\f55e"; }
+
+.fa-business-time:before {
+ content: "\f64a"; }
+
+.fa-buy-n-large:before {
+ content: "\f8a6"; }
+
+.fa-buysellads:before {
+ content: "\f20d"; }
+
+.fa-calculator:before {
+ content: "\f1ec"; }
+
+.fa-calendar:before {
+ content: "\f133"; }
+
+.fa-calendar-alt:before {
+ content: "\f073"; }
+
+.fa-calendar-check:before {
+ content: "\f274"; }
+
+.fa-calendar-day:before {
+ content: "\f783"; }
+
+.fa-calendar-minus:before {
+ content: "\f272"; }
+
+.fa-calendar-plus:before {
+ content: "\f271"; }
+
+.fa-calendar-times:before {
+ content: "\f273"; }
+
+.fa-calendar-week:before {
+ content: "\f784"; }
+
+.fa-camera:before {
+ content: "\f030"; }
+
+.fa-camera-retro:before {
+ content: "\f083"; }
+
+.fa-campground:before {
+ content: "\f6bb"; }
+
+.fa-canadian-maple-leaf:before {
+ content: "\f785"; }
+
+.fa-candy-cane:before {
+ content: "\f786"; }
+
+.fa-cannabis:before {
+ content: "\f55f"; }
+
+.fa-capsules:before {
+ content: "\f46b"; }
+
+.fa-car:before {
+ content: "\f1b9"; }
+
+.fa-car-alt:before {
+ content: "\f5de"; }
+
+.fa-car-battery:before {
+ content: "\f5df"; }
+
+.fa-car-crash:before {
+ content: "\f5e1"; }
+
+.fa-car-side:before {
+ content: "\f5e4"; }
+
+.fa-caravan:before {
+ content: "\f8ff"; }
+
+.fa-caret-down:before {
+ content: "\f0d7"; }
+
+.fa-caret-left:before {
+ content: "\f0d9"; }
+
+.fa-caret-right:before {
+ content: "\f0da"; }
+
+.fa-caret-square-down:before {
+ content: "\f150"; }
+
+.fa-caret-square-left:before {
+ content: "\f191"; }
+
+.fa-caret-square-right:before {
+ content: "\f152"; }
+
+.fa-caret-square-up:before {
+ content: "\f151"; }
+
+.fa-caret-up:before {
+ content: "\f0d8"; }
+
+.fa-carrot:before {
+ content: "\f787"; }
+
+.fa-cart-arrow-down:before {
+ content: "\f218"; }
+
+.fa-cart-plus:before {
+ content: "\f217"; }
+
+.fa-cash-register:before {
+ content: "\f788"; }
+
+.fa-cat:before {
+ content: "\f6be"; }
+
+.fa-cc-amazon-pay:before {
+ content: "\f42d"; }
+
+.fa-cc-amex:before {
+ content: "\f1f3"; }
+
+.fa-cc-apple-pay:before {
+ content: "\f416"; }
+
+.fa-cc-diners-club:before {
+ content: "\f24c"; }
+
+.fa-cc-discover:before {
+ content: "\f1f2"; }
+
+.fa-cc-jcb:before {
+ content: "\f24b"; }
+
+.fa-cc-mastercard:before {
+ content: "\f1f1"; }
+
+.fa-cc-paypal:before {
+ content: "\f1f4"; }
+
+.fa-cc-stripe:before {
+ content: "\f1f5"; }
+
+.fa-cc-visa:before {
+ content: "\f1f0"; }
+
+.fa-centercode:before {
+ content: "\f380"; }
+
+.fa-centos:before {
+ content: "\f789"; }
+
+.fa-certificate:before {
+ content: "\f0a3"; }
+
+.fa-chair:before {
+ content: "\f6c0"; }
+
+.fa-chalkboard:before {
+ content: "\f51b"; }
+
+.fa-chalkboard-teacher:before {
+ content: "\f51c"; }
+
+.fa-charging-station:before {
+ content: "\f5e7"; }
+
+.fa-chart-area:before {
+ content: "\f1fe"; }
+
+.fa-chart-bar:before {
+ content: "\f080"; }
+
+.fa-chart-line:before {
+ content: "\f201"; }
+
+.fa-chart-pie:before {
+ content: "\f200"; }
+
+.fa-check:before {
+ content: "\f00c"; }
+
+.fa-check-circle:before {
+ content: "\f058"; }
+
+.fa-check-double:before {
+ content: "\f560"; }
+
+.fa-check-square:before {
+ content: "\f14a"; }
+
+.fa-cheese:before {
+ content: "\f7ef"; }
+
+.fa-chess:before {
+ content: "\f439"; }
+
+.fa-chess-bishop:before {
+ content: "\f43a"; }
+
+.fa-chess-board:before {
+ content: "\f43c"; }
+
+.fa-chess-king:before {
+ content: "\f43f"; }
+
+.fa-chess-knight:before {
+ content: "\f441"; }
+
+.fa-chess-pawn:before {
+ content: "\f443"; }
+
+.fa-chess-queen:before {
+ content: "\f445"; }
+
+.fa-chess-rook:before {
+ content: "\f447"; }
+
+.fa-chevron-circle-down:before {
+ content: "\f13a"; }
+
+.fa-chevron-circle-left:before {
+ content: "\f137"; }
+
+.fa-chevron-circle-right:before {
+ content: "\f138"; }
+
+.fa-chevron-circle-up:before {
+ content: "\f139"; }
+
+.fa-chevron-down:before {
+ content: "\f078"; }
+
+.fa-chevron-left:before {
+ content: "\f053"; }
+
+.fa-chevron-right:before {
+ content: "\f054"; }
+
+.fa-chevron-up:before {
+ content: "\f077"; }
+
+.fa-child:before {
+ content: "\f1ae"; }
+
+.fa-chrome:before {
+ content: "\f268"; }
+
+.fa-chromecast:before {
+ content: "\f838"; }
+
+.fa-church:before {
+ content: "\f51d"; }
+
+.fa-circle:before {
+ content: "\f111"; }
+
+.fa-circle-notch:before {
+ content: "\f1ce"; }
+
+.fa-city:before {
+ content: "\f64f"; }
+
+.fa-clinic-medical:before {
+ content: "\f7f2"; }
+
+.fa-clipboard:before {
+ content: "\f328"; }
+
+.fa-clipboard-check:before {
+ content: "\f46c"; }
+
+.fa-clipboard-list:before {
+ content: "\f46d"; }
+
+.fa-clock:before {
+ content: "\f017"; }
+
+.fa-clone:before {
+ content: "\f24d"; }
+
+.fa-closed-captioning:before {
+ content: "\f20a"; }
+
+.fa-cloud:before {
+ content: "\f0c2"; }
+
+.fa-cloud-download-alt:before {
+ content: "\f381"; }
+
+.fa-cloud-meatball:before {
+ content: "\f73b"; }
+
+.fa-cloud-moon:before {
+ content: "\f6c3"; }
+
+.fa-cloud-moon-rain:before {
+ content: "\f73c"; }
+
+.fa-cloud-rain:before {
+ content: "\f73d"; }
+
+.fa-cloud-showers-heavy:before {
+ content: "\f740"; }
+
+.fa-cloud-sun:before {
+ content: "\f6c4"; }
+
+.fa-cloud-sun-rain:before {
+ content: "\f743"; }
+
+.fa-cloud-upload-alt:before {
+ content: "\f382"; }
+
+.fa-cloudflare:before {
+ content: "\e07d"; }
+
+.fa-cloudscale:before {
+ content: "\f383"; }
+
+.fa-cloudsmith:before {
+ content: "\f384"; }
+
+.fa-cloudversify:before {
+ content: "\f385"; }
+
+.fa-cocktail:before {
+ content: "\f561"; }
+
+.fa-code:before {
+ content: "\f121"; }
+
+.fa-code-branch:before {
+ content: "\f126"; }
+
+.fa-codepen:before {
+ content: "\f1cb"; }
+
+.fa-codiepie:before {
+ content: "\f284"; }
+
+.fa-coffee:before {
+ content: "\f0f4"; }
+
+.fa-cog:before {
+ content: "\f013"; }
+
+.fa-cogs:before {
+ content: "\f085"; }
+
+.fa-coins:before {
+ content: "\f51e"; }
+
+.fa-columns:before {
+ content: "\f0db"; }
+
+.fa-comment:before {
+ content: "\f075"; }
+
+.fa-comment-alt:before {
+ content: "\f27a"; }
+
+.fa-comment-dollar:before {
+ content: "\f651"; }
+
+.fa-comment-dots:before {
+ content: "\f4ad"; }
+
+.fa-comment-medical:before {
+ content: "\f7f5"; }
+
+.fa-comment-slash:before {
+ content: "\f4b3"; }
+
+.fa-comments:before {
+ content: "\f086"; }
+
+.fa-comments-dollar:before {
+ content: "\f653"; }
+
+.fa-compact-disc:before {
+ content: "\f51f"; }
+
+.fa-compass:before {
+ content: "\f14e"; }
+
+.fa-compress:before {
+ content: "\f066"; }
+
+.fa-compress-alt:before {
+ content: "\f422"; }
+
+.fa-compress-arrows-alt:before {
+ content: "\f78c"; }
+
+.fa-concierge-bell:before {
+ content: "\f562"; }
+
+.fa-confluence:before {
+ content: "\f78d"; }
+
+.fa-connectdevelop:before {
+ content: "\f20e"; }
+
+.fa-contao:before {
+ content: "\f26d"; }
+
+.fa-cookie:before {
+ content: "\f563"; }
+
+.fa-cookie-bite:before {
+ content: "\f564"; }
+
+.fa-copy:before {
+ content: "\f0c5"; }
+
+.fa-copyright:before {
+ content: "\f1f9"; }
+
+.fa-cotton-bureau:before {
+ content: "\f89e"; }
+
+.fa-couch:before {
+ content: "\f4b8"; }
+
+.fa-cpanel:before {
+ content: "\f388"; }
+
+.fa-creative-commons:before {
+ content: "\f25e"; }
+
+.fa-creative-commons-by:before {
+ content: "\f4e7"; }
+
+.fa-creative-commons-nc:before {
+ content: "\f4e8"; }
+
+.fa-creative-commons-nc-eu:before {
+ content: "\f4e9"; }
+
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+.fa-hanukiah:before {
+ content: "\f6e6"; }
+
+.fa-hard-hat:before {
+ content: "\f807"; }
+
+.fa-hashtag:before {
+ content: "\f292"; }
+
+.fa-hat-cowboy:before {
+ content: "\f8c0"; }
+
+.fa-hat-cowboy-side:before {
+ content: "\f8c1"; }
+
+.fa-hat-wizard:before {
+ content: "\f6e8"; }
+
+.fa-hdd:before {
+ content: "\f0a0"; }
+
+.fa-head-side-cough:before {
+ content: "\e061"; }
+
+.fa-head-side-cough-slash:before {
+ content: "\e062"; }
+
+.fa-head-side-mask:before {
+ content: "\e063"; }
+
+.fa-head-side-virus:before {
+ content: "\e064"; }
+
+.fa-heading:before {
+ content: "\f1dc"; }
+
+.fa-headphones:before {
+ content: "\f025"; }
+
+.fa-headphones-alt:before {
+ content: "\f58f"; }
+
+.fa-headset:before {
+ content: "\f590"; }
+
+.fa-heart:before {
+ content: "\f004"; }
+
+.fa-heart-broken:before {
+ content: "\f7a9"; }
+
+.fa-heartbeat:before {
+ content: "\f21e"; }
+
+.fa-helicopter:before {
+ content: "\f533"; }
+
+.fa-highlighter:before {
+ content: "\f591"; }
+
+.fa-hiking:before {
+ content: "\f6ec"; }
+
+.fa-hippo:before {
+ content: "\f6ed"; }
+
+.fa-hips:before {
+ content: "\f452"; }
+
+.fa-hire-a-helper:before {
+ content: "\f3b0"; }
+
+.fa-history:before {
+ content: "\f1da"; }
+
+.fa-hive:before {
+ content: "\e07f"; }
+
+.fa-hockey-puck:before {
+ content: "\f453"; }
+
+.fa-holly-berry:before {
+ content: "\f7aa"; }
+
+.fa-home:before {
+ content: "\f015"; }
+
+.fa-hooli:before {
+ content: "\f427"; }
+
+.fa-hornbill:before {
+ content: "\f592"; }
+
+.fa-horse:before {
+ content: "\f6f0"; }
+
+.fa-horse-head:before {
+ content: "\f7ab"; }
+
+.fa-hospital:before {
+ content: "\f0f8"; }
+
+.fa-hospital-alt:before {
+ content: "\f47d"; }
+
+.fa-hospital-symbol:before {
+ content: "\f47e"; }
+
+.fa-hospital-user:before {
+ content: "\f80d"; }
+
+.fa-hot-tub:before {
+ content: "\f593"; }
+
+.fa-hotdog:before {
+ content: "\f80f"; }
+
+.fa-hotel:before {
+ content: "\f594"; }
+
+.fa-hotjar:before {
+ content: "\f3b1"; }
+
+.fa-hourglass:before {
+ content: "\f254"; }
+
+.fa-hourglass-end:before {
+ content: "\f253"; }
+
+.fa-hourglass-half:before {
+ content: "\f252"; }
+
+.fa-hourglass-start:before {
+ content: "\f251"; }
+
+.fa-house-damage:before {
+ content: "\f6f1"; }
+
+.fa-house-user:before {
+ content: "\e065"; }
+
+.fa-houzz:before {
+ content: "\f27c"; }
+
+.fa-hryvnia:before {
+ content: "\f6f2"; }
+
+.fa-html5:before {
+ content: "\f13b"; }
+
+.fa-hubspot:before {
+ content: "\f3b2"; }
+
+.fa-i-cursor:before {
+ content: "\f246"; }
+
+.fa-ice-cream:before {
+ content: "\f810"; }
+
+.fa-icicles:before {
+ content: "\f7ad"; }
+
+.fa-icons:before {
+ content: "\f86d"; }
+
+.fa-id-badge:before {
+ content: "\f2c1"; }
+
+.fa-id-card:before {
+ content: "\f2c2"; }
+
+.fa-id-card-alt:before {
+ content: "\f47f"; }
+
+.fa-ideal:before {
+ content: "\e013"; }
+
+.fa-igloo:before {
+ content: "\f7ae"; }
+
+.fa-image:before {
+ content: "\f03e"; }
... 132824 lines suppressed ...