add structural pattern matching

khuyentran1401 · Aug 20, 2024 · 21aa9ee · 21aa9ee
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diff --git a/Chapter1/python_new_features.ipynb b/Chapter1/python_new_features.ipynb
@@ -122,28 +122,108 @@
    ]
   },
   {
-   "attachments": {},
    "cell_type": "markdown",
-   "id": "b7169caa",
+   "id": "ce7a6d1c",
+   "metadata": {},
+   "source": [
+    "Extracting data from nested structures often leads to complex, error-prone code with multiple checks and conditionals. Consider this traditional approach:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "69ff114d",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "Have you ever wanted to match complex data types and extract their information? \n",
+    "def get_youngest_pet(pet_info):\n",
+    "    if isinstance(pet_info, list) and len(pet_info) == 2:\n",
+    "        if all(\"age\" in pet for pet in pet_info):\n",
+    "            print(\"Age is extracted from a list\")\n",
+    "            return min(pet_info[0][\"age\"], pet_info[1][\"age\"])\n",
+    "    elif isinstance(pet_info, dict) and \"age\" in pet_info:\n",
+    "        if isinstance(pet_info[\"age\"], dict):\n",
+    "            print(\"Age is extracted from a dict\")\n",
+    "            ages = pet_info[\"age\"].values()\n",
+    "            return min(ages)\n",
     "\n",
-    "Python 3.10 allows you to do exactly that with the `match` statement and the `case` statements. "
+    "    # Handle other cases or raise an exception\n",
+    "    raise ValueError(\"Invalid input format\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "976c0668",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Age is extracted from a list\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pet_info1 = [\n",
+    "    {\"name\": \"bim\", \"age\": 1},\n",
+    "    {\"name\": \"pepper\", \"age\": 9},\n",
+    "]\n",
+    "get_youngest_pet(pet_info1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "99225ef8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Age is extracted from a dict\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pet_info2 = {'age': {\"bim\": 1, \"pepper\": 9}}\n",
+    "get_youngest_pet(pet_info2)"
    ]
   },
   {
    "attachments": {},
    "cell_type": "markdown",
-   "id": "42104aba",
+   "id": "b7169caa",
    "metadata": {},
    "source": [
-    "The code below uses structural pattern matching to extract ages from the matching data structure.  "
+    "Python 3.10's pattern matching provides a more declarative and readable way to handle complex data structures, reducing the need for nested conditionals and type checks."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "a181f881",
    "metadata": {},
    "outputs": [],
@@ -157,12 +237,15 @@
     "        case {'age': {}}:\n",
     "            print(\"Age is extracted from a dict\")\n",
     "            ages = pet_info['age'].values()\n",
-    "            return min(ages)\n"
+    "            return min(ages)\n",
+    "\n",
+    "        case _:\n",
+    "            raise ValueError(\"Invalid input format\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "9604eb87",
    "metadata": {},
    "outputs": [
@@ -179,18 +262,22 @@
        "1"
       ]
      },
+     "execution_count": 23,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "pet_info1 = [{\"name\": \"bim\", \"age\": 1}, {\"name\": \"pepper\", \"age\": 9}]\n",
+    "pet_info1 = [\n",
+    "    {\"name\": \"bim\", \"age\": 1},\n",
+    "    {\"name\": \"pepper\", \"age\": 9},\n",
+    "]\n",
     "get_youngest_pet(pet_info1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "7f8f2b9f",
    "metadata": {},
    "outputs": [
@@ -207,8 +294,9 @@
        "1"
       ]
      },
+     "execution_count": 8,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     }
    ],
    "source": [

diff --git a/Chapter5/SQL.ipynb b/Chapter5/SQL.ipynb
@@ -1023,6 +1023,119 @@
    "source": [
     "[Link to sql-metadata](https://github.com/macbre/sql-metadata)."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "055e3474",
+   "metadata": {},
+   "source": [
+    "### SQLGlot: Write Once, Run Anywhere SQL"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d257860",
+   "metadata": {
+    "tags": [
+     "hide-cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "!pip install \"sqlglot[rs]\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "49d7f225",
+   "metadata": {},
+   "source": [
+    "SQL dialects vary across databases, making it challenging to port queries between different database systems.\n",
+    "\n",
+    "SQLGlot addresses this by providing a parser and transpiler supporting 21 dialects. This enables automatic SQL translation between systems, eliminating the need for manual query rewrites."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "72644346",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sqlglot"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "733ad01f",
+   "metadata": {},
+   "source": [
+    "Convert a DuckDB-specific date formatting query into an equivalent query in Hive SQL:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8f46784d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"SELECT DATE_FORMAT(x, 'yy-M-ss')\""
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sqlglot.transpile(\"SELECT STRFTIME(x, '%y-%-m-%S')\", read=\"duckdb\", write=\"hive\")[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "123e7f07",
+   "metadata": {},
+   "source": [
+    "Convert a SQL query to Spark SQL:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "397512c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SELECT\n",
+      "  `id`,\n",
+      "  `name`,\n",
+      "  CAST(`price` AS FLOAT) AS `converted_price`\n",
+      "FROM `products`\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Spark SQL requires backticks (`) for delimited identifiers and uses `FLOAT` over `REAL`\n",
+    "sql = \"SELECT id, name, CAST(price AS REAL) AS converted_price FROM products\"\n",
+    "\n",
+    "# Translates the query into Spark SQL, formats it, and delimits all of its identifiers\n",
+    "print(sqlglot.transpile(sql, write=\"spark\", identify=True, pretty=True)[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a983e21",
+   "metadata": {},
+   "source": [
+    "[Link to SQLGlot](https://bit.ly/4dGyTmP)."
+   ]
   }
  ],
  "metadata": {

diff --git a/docs/Chapter1/python_new_features.html b/docs/Chapter1/python_new_features.html
@@ -234,6 +234,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../Chapter2/dataclasses.html">3.7. Data Classes</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../Chapter2/typing.html">3.8. Typing</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../Chapter2/pathlib.html">3.9. pathlib</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../Chapter2/pydantic.html">3.10. Pydantic</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../Chapter3/Chapter3.html">4. Pandas</a><input class="toctree-checkbox" id="toctree-checkbox-4" name="toctree-checkbox-4" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-4"><i class="fa-solid fa-chevron-down"></i></label><ul>
@@ -587,9 +588,62 @@ <h2><span class="section-number">2.10.1. </span>Simplify Conditional Execution w
 </section>
 <section id="structural-pattern-matching-in-python-3-10">
 <h2><span class="section-number">2.10.2. </span>Structural Pattern Matching in Python 3.10<a class="headerlink" href="#structural-pattern-matching-in-python-3-10" title="Permalink to this heading">#</a></h2>
-<p>Have you ever wanted to match complex data types and extract their information?</p>
-<p>Python 3.10 allows you to do exactly that with the <code class="docutils literal notranslate"><span class="pre">match</span></code> statement and the <code class="docutils literal notranslate"><span class="pre">case</span></code> statements.</p>
-<p>The code below uses structural pattern matching to extract ages from the matching data structure.</p>
+<p>Extracting data from nested structures often leads to complex, error-prone code with multiple checks and conditionals. Consider this traditional approach:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">get_youngest_pet</span><span class="p">(</span><span class="n">pet_info</span><span class="p">):</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">pet_info</span><span class="p">,</span> <span class="nb">list</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">pet_info</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
+        <span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="s2">&quot;age&quot;</span> <span class="ow">in</span> <span class="n">pet</span> <span class="k">for</span> <span class="n">pet</span> <span class="ow">in</span> <span class="n">pet_info</span><span class="p">):</span>
+            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Age is extracted from a list&quot;</span><span class="p">)</span>
+            <span class="k">return</span> <span class="nb">min</span><span class="p">(</span><span class="n">pet_info</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s2">&quot;age&quot;</span><span class="p">],</span> <span class="n">pet_info</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s2">&quot;age&quot;</span><span class="p">])</span>
+    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">pet_info</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">and</span> <span class="s2">&quot;age&quot;</span> <span class="ow">in</span> <span class="n">pet_info</span><span class="p">:</span>
+        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">pet_info</span><span class="p">[</span><span class="s2">&quot;age&quot;</span><span class="p">],</span> <span class="nb">dict</span><span class="p">):</span>
+            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Age is extracted from a dict&quot;</span><span class="p">)</span>
+            <span class="n">ages</span> <span class="o">=</span> <span class="n">pet_info</span><span class="p">[</span><span class="s2">&quot;age&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">()</span>
+            <span class="k">return</span> <span class="nb">min</span><span class="p">(</span><span class="n">ages</span><span class="p">)</span>
+
+    <span class="c1"># Handle other cases or raise an exception</span>
+    <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Invalid input format&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">pet_info1</span> <span class="o">=</span> <span class="p">[</span>
+    <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;bim&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">},</span>
+    <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;pepper&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">9</span><span class="p">},</span>
+<span class="p">]</span>
+<span class="n">get_youngest_pet</span><span class="p">(</span><span class="n">pet_info1</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Age is extracted from a list
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>1
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">pet_info2</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;age&#39;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;bim&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;pepper&quot;</span><span class="p">:</span> <span class="mi">9</span><span class="p">}}</span>
+<span class="n">get_youngest_pet</span><span class="p">(</span><span class="n">pet_info2</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Age is extracted from a dict
+</pre></div>
+</div>
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>1
+</pre></div>
+</div>
+</div>
+</div>
+<p>Python 3.10’s pattern matching provides a more declarative and readable way to handle complex data structures, reducing the need for nested conditionals and type checks.</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">get_youngest_pet</span><span class="p">(</span><span class="n">pet_info</span><span class="p">):</span>
@@ -602,13 +656,19 @@ <h2><span class="section-number">2.10.2. </span>Structural Pattern Matching in P
             <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Age is extracted from a dict&quot;</span><span class="p">)</span>
             <span class="n">ages</span> <span class="o">=</span> <span class="n">pet_info</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">()</span>
             <span class="k">return</span> <span class="nb">min</span><span class="p">(</span><span class="n">ages</span><span class="p">)</span>
+
+        <span class="k">case</span><span class="w"> </span><span class="k">_</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Invalid input format&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">pet_info1</span> <span class="o">=</span> <span class="p">[{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;bim&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">},</span> <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;pepper&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">9</span><span class="p">}]</span>
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">pet_info1</span> <span class="o">=</span> <span class="p">[</span>
+    <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;bim&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">},</span>
+    <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;pepper&quot;</span><span class="p">,</span> <span class="s2">&quot;age&quot;</span><span class="p">:</span> <span class="mi">9</span><span class="p">},</span>
+<span class="p">]</span>
 <span class="n">get_youngest_pet</span><span class="p">(</span><span class="n">pet_info1</span><span class="p">)</span>
 </pre></div>
 </div>