DOC add pipeline examples (#2240)

* DOC add pipeline examples

* Add pipeline notebook to the example.rst file

* retrigger checks

docs/examples.rst

@@ -10,4 +10,5 @@ Examples
    examples/asyncio_examples
    examples/search_json_examples
    examples/set_and_get_examples
-   examples/search_vector_similarity_examples
+   examples/search_vector_similarity_examples
+   examples/pipeline_examples

docs/examples/pipeline_examples.ipynb

@@ -0,0 +1,308 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pipeline examples\n",
+    "\n",
+    "This example show quickly how to use pipelines in `redis-py`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Checking that Redis is running"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import redis \n",
+    "\n",
+    "r = redis.Redis(decode_responses=True)\n",
+    "r.ping()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simple example"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Creating a pipeline instance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pipe = r.pipeline()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Adding commands to the pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Pipeline<ConnectionPool<Connection<host=localhost,port=6379,db=0>>>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pipe.set(\"a\", \"a value\")\n",
+    "pipe.set(\"b\", \"b value\")\n",
+    "\n",
+    "pipe.get(\"a\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Executing the pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[True, True, 'a value']"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pipe.execute()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The responses of the three commands are stored in a list. In the above example, the two first boolean indicates that the the `set` commands were successfull and the last element of the list is the result of the `get(\"a\")` comand."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Chained call\n",
+    "\n",
+    "The same result as above can be obtained in one line of code by chaining the opperations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[True, True, 'a value']"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pipe = r.pipeline()\n",
+    "pipe.set(\"a\", \"a value\").set(\"b\", \"b value\").get(\"a\").execute()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Performance comparison\n",
+    "\n",
+    "Using pipelines can improve performance, for more informations, see [Redis documentation about pipelining](https://redis.io/docs/manual/pipelining/). Here is a simple comparison test of performance between basic and pipelined commands (we simply increment a value and measure the time taken by both method)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datetime import datetime\n",
+    "\n",
+    "incr_value = 100000"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Without pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r.set(\"incr_key\", \"0\")\n",
+    "\n",
+    "start = datetime.now()\n",
+    "\n",
+    "for _ in range(incr_value):\n",
+    "    r.incr(\"incr_key\")\n",
+    "res_without_pipeline = r.get(\"incr_key\")\n",
+    "\n",
+    "time_without_pipeline = (datetime.now() - start).total_seconds()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Without pipeline\n",
+      "================\n",
+      "Time taken:  21.759733\n",
+      "Increment value:  100000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Without pipeline\")\n",
+    "print(\"================\")\n",
+    "print(\"Time taken: \", time_without_pipeline)\n",
+    "print(\"Increment value: \", res_without_pipeline)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### With pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r.set(\"incr_key\", \"0\")\n",
+    "\n",
+    "start = datetime.now()\n",
+    "\n",
+    "pipe = r.pipeline()\n",
+    "for _ in range(incr_value):\n",
+    "    pipe.incr(\"incr_key\")\n",
+    "pipe.get(\"incr_key\")\n",
+    "res_with_pipeline = pipe.execute()[-1]\n",
+    "\n",
+    "time_with_pipeline = (datetime.now() - start).total_seconds()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "With pipeline\n",
+      "=============\n",
+      "Time taken:  2.357863\n",
+      "Increment value:  100000\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"With pipeline\")\n",
+    "print(\"=============\")\n",
+    "print(\"Time taken: \", time_with_pipeline)\n",
+    "print(\"Increment value: \", res_with_pipeline)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using pipelines provides the same result in much less time."
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "84048e2f8e89effc8610b2fb270e4858ef00e9403d223856d62b05266db287ca"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.9.2 ('.venv': venv)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.2"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}