diff --git a/01-data-model/data-model.ipynb b/01-data-model/data-model.ipynb index f525899..5b30397 100644 --- a/01-data-model/data-model.ipynb +++ b/01-data-model/data-model.ipynb @@ -482,7 +482,7 @@ " self.y = y\n", "\n", " def __repr__(self):\n", - " return 'Vector(%r, %r)' % (self.x, self.y)\n", + " return f'Vector({self.x!r}, {self.y!r})'\n", "\n", " def __abs__(self):\n", " return math.hypot(self.x, self.y)\n", diff --git a/02-array-seq/array-seq.ipynb b/02-array-seq/array-seq.ipynb index 032d811..afdbf6b 100644 --- a/02-array-seq/array-seq.ipynb +++ b/02-array-seq/array-seq.ipynb @@ -9,12 +9,14 @@ "**Sections with code snippets in this chapter:**\n", "\n", "* [List Comprehensions and Generator Expressions](#List-Comprehensions-and-Generator-Expressions)\n", + "* [Tuples Are Not Just Immutable Lists](#Tuples-Are-Not-Just-Immutable-Lists)\n", + "* [Unpacking sequences and iterables](#Unpacking-sequences-and-iterables)\n", + "* [Pattern Matching with Sequences](#Pattern-Matching-with-Sequences)\n", "* [Slicing](#Slicing)\n", - "* [Building Lists of Lists](#Building-Lists-of-Lists)\n", + "* [Using + and * with Sequences](#Using-+-and-*-with-Sequences)\n", "* [Augmented Assignment with Sequences](#Augmented-Assignment-with-Sequences)\n", "* [list.sort and the sorted Built-In Function](#list.sort-and-the-sorted-Built-In-Function)\n", - "* [Managing Ordered Sequences with bisect](#Managing-Ordered-Sequences-with-bisect)\n", - "* [Arrays](#Arrays)\n", + "* [When a List Is Not the Answer](#When-a-List-Is-Not-the-Answer)\n", "* [Memory Views](#Memory-Views)\n", "* [NumPy and SciPy](#NumPy-and-SciPy)\n", "* [Deques and Other Queues](#Deques-and-Other-Queues)\n", @@ -42,9 +44,7 @@ "outputs": [ { "data": { - "text/plain": [ - "[36, 162, 163, 165, 8364, 164]" - ] + "text/plain": "[36, 162, 163, 165, 8364, 164]" }, "execution_count": 1, "metadata": {}, @@ -65,7 +65,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-2. Build a list of Unicode codepoints from a string, take 2" + "#### Example 2-2. Build a list of Unicode codepoints from a string, using a listcomp" ] }, { @@ -75,9 +75,7 @@ "outputs": [ { "data": { - "text/plain": [ - "[36, 162, 163, 165, 8364, 164]" - ] + "text/plain": "[36, 162, 163, 165, 8364, 164]" }, "execution_count": 2, "metadata": {}, @@ -106,9 +104,7 @@ "outputs": [ { "data": { - "text/plain": [ - "'ABC'" - ] + "text/plain": "'ABC'" }, "execution_count": 3, "metadata": {}, @@ -128,9 +124,7 @@ "outputs": [ { "data": { - "text/plain": [ - "[65, 66, 67]" - ] + "text/plain": "[65, 66, 67]" }, "execution_count": 4, "metadata": {}, @@ -141,6 +135,30 @@ "codes" ] }, + { + "cell_type": "code", + "execution_count": 5, + "outputs": [ + { + "data": { + "text/plain": "67" + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "codes = [last := ord(c) for c in x]\n", + "last" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, { "cell_type": "markdown", "metadata": {}, @@ -150,214 +168,958 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "[162, 163, 165, 8364, 164]" + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "symbols = '$¢£¥€¤'\n", + "beyond_ascii = [ord(s) for s in symbols if ord(s) > 127]\n", + "beyond_ascii" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "[162, 163, 165, 8364, 164]" + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "beyond_ascii = list(filter(lambda c: c > 127, map(ord, symbols)))\n", + "beyond_ascii" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Example 2-4. Cartesian product using a list comprehension" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "[('black', 'S'),\n ('black', 'M'),\n ('black', 'L'),\n ('white', 'S'),\n ('white', 'M'),\n ('white', 'L')]" + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "colors = ['black', 'white']\n", + "sizes = ['S', 'M', 'L']\n", + "tshirts = [(color, size) for color in colors for size in sizes]\n", + "tshirts" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('black', 'S')\n", + "('black', 'M')\n", + "('black', 'L')\n", + "('white', 'S')\n", + "('white', 'M')\n", + "('white', 'L')\n" + ] + } + ], + "source": [ + "for color in colors:\n", + " for size in sizes:\n", + " print((color, size))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "[('black', 'S'),\n ('black', 'M'),\n ('black', 'L'),\n ('white', 'S'),\n ('white', 'M'),\n ('white', 'L')]" + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "shirts = [(color, size) for size in sizes\n", + " for color in colors]\n", + "tshirts" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Example 2-5. Initializing a tuple and an array from a generator expression" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "(36, 162, 163, 165, 8364, 164)" + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "symbols = '$¢£¥€¤'\n", + "tuple(ord(symbol) for symbol in symbols)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": "array('I', [36, 162, 163, 165, 8364, 164])" + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import array\n", + "\n", + "array.array('I', (ord(symbol) for symbol in symbols))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Example 2-6. Cartesian product in a generator expression" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "black S\n", + "black M\n", + "black L\n", + "white S\n", + "white M\n", + "white L\n" + ] + } + ], + "source": [ + "colors = ['black', 'white']\n", + "sizes = ['S', 'M', 'L']\n", + "\n", + "for tshirt in ('%s %s' % (c, s) for c in colors for s in sizes):\n", + " print(tshirt)" + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Tuples Are Not Just Immutable Lists" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + }, + "execution_count": 73 + }, + { + "cell_type": "markdown", + "source": [ + "#### Example 2-7. Tuples used as records" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 14, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "BRA/CE342567\n", + "ESP/XDA205856\n", + "USA/31195855\n" + ] + } + ], + "source": [ + "lax_coordinates = (33.9425, -118.408056)\n", + "city, year, pop, chg, area = ('Tokyo', 2003, 32_450, 0.66, 8014)\n", + "traveler_ids = [('USA', '31195855'), ('BRA', 'CE342567'), ('ESP', 'XDA205856')]\n", + "\n", + "for passport in sorted(traveler_ids):\n", + " print('%s/%s' % passport)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 15, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "USA\n", + "BRA\n", + "ESP\n" + ] + } + ], + "source": [ + "for country, _ in traveler_ids:\n", + " print(country)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "### Tuples as Immutable Lists" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 16, + "outputs": [ + { + "data": { + "text/plain": "True" + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a = (10, 'alpha', [1, 2])\n", + "b = (10, 'alpha', [1, 2])\n", + "a == b" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 17, + "outputs": [ + { + "data": { + "text/plain": "False" + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b[-1].append(99)\n", + "a == b" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 18, + "outputs": [ + { + "data": { + "text/plain": "(10, 'alpha', [1, 2, 99])" + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 19, + "outputs": [ + { + "data": { + "text/plain": "True" + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def fixed(o):\n", + " try:\n", + " hash(o)\n", + " except TypeError:\n", + " return False\n", + " return True\n", + "\n", + "\n", + "tf = (10, 'alpha', (1, 2)) # Contains no mutable items\n", + "tm = (10, 'alpha', [1, 2]) # Contains a mutable item (list)\n", + "fixed(tf)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 20, + "outputs": [ + { + "data": { + "text/plain": "False" + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fixed(tm)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## Unpacking sequences and iterables" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 21, + "outputs": [ + { + "data": { + "text/plain": "33.9425" + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lax_coordinates = (33.9425, -118.408056)\n", + "latitude, longitude = lax_coordinates # unpacking\n", + "latitude" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 22, + "outputs": [ + { + "data": { + "text/plain": "-118.408056" + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "longitude" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 23, + "outputs": [ + { + "data": { + "text/plain": "(2, 4)" + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "divmod(20, 8)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 24, + "outputs": [ + { + "data": { + "text/plain": "(2, 4)" + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "t = (20, 8)\n", + "divmod(*t)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 25, + "outputs": [ + { + "data": { + "text/plain": "(2, 4)" + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "quotient, remainder = divmod(*t)\n", + "quotient, remainder" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 26, + "outputs": [ + { + "data": { + "text/plain": "'id_rsa.pub'" + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "_, filename = os.path.split('/home/luciano/.ssh/id_rsa.pub')\n", + "filename" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "### Using * to grab excess items" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 27, + "outputs": [ + { + "data": { + "text/plain": "(0, 1, [2, 3, 4])" + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a, b, *rest = range(5)\n", + "a, b, rest" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 28, + "outputs": [ + { + "data": { + "text/plain": "(0, 1, [2])" + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a, b, *rest = range(3)\n", + "a, b, rest" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 29, "outputs": [ { "data": { - "text/plain": [ - "[162, 163, 165, 8364, 164]" - ] + "text/plain": "(0, 1, [])" }, - "execution_count": 5, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "symbols = '$¢£¥€¤'\n", - "beyond_ascii = [ord(s) for s in symbols if ord(s) > 127]\n", - "beyond_ascii" - ] + "a, b, *rest = range(2)\n", + "a, b, rest" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 30, "outputs": [ { "data": { - "text/plain": [ - "[162, 163, 165, 8364, 164]" - ] + "text/plain": "(0, [1, 2], 3, 4)" }, - "execution_count": 6, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "beyond_ascii = list(filter(lambda c: c > 127, map(ord, symbols)))\n", - "beyond_ascii" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Example 2-4. Cartesian product using a list comprehension" - ] + "a, *body, c, d = range(5)\n", + "a, body, c, d" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 31, "outputs": [ { "data": { - "text/plain": [ - "[('black', 'S'),\n", - " ('black', 'M'),\n", - " ('black', 'L'),\n", - " ('white', 'S'),\n", - " ('white', 'M'),\n", - " ('white', 'L')]" - ] + "text/plain": "([0, 1], 2, 3, 4)" }, - "execution_count": 7, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "colors = ['black', 'white']\n", - "sizes = ['S', 'M', 'L']\n", - "tshirts = [(color, size) for color in colors for size in sizes]\n", - "tshirts" - ] + "*head, b, c, d = range(5)\n", + "head, b, c, d" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "### Unpacking with * in function calls and sequence literals" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, + "execution_count": 32, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "('black', 'S')\n", - "('black', 'M')\n", - "('black', 'L')\n", - "('white', 'S')\n", - "('white', 'M')\n", - "('white', 'L')\n" - ] + "data": { + "text/plain": "(1, 2, 3, 4, (5, 6))" + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "for color in colors:\n", - " for size in sizes:\n", - " print((color, size))" - ] + "def fun(a, b, c, d, *rest):\n", + " return a, b, c, d, rest\n", + "\n", + "\n", + "fun(*[1, 2], 3, *range(4, 7))" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 33, "outputs": [ { "data": { - "text/plain": [ - "[('black', 'S'),\n", - " ('black', 'M'),\n", - " ('black', 'L'),\n", - " ('white', 'S'),\n", - " ('white', 'M'),\n", - " ('white', 'L')]" - ] + "text/plain": "(0, 1, 2, 3, 4)" }, - "execution_count": 9, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "shirts = [(color, size) for size in sizes\n", - " for color in colors]\n", - "tshirts" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Example 2-5. Initializing a tuple and an array from a generator expression" - ] + "*range(4), 4" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 10, - "metadata": {}, + "execution_count": 34, "outputs": [ { "data": { - "text/plain": [ - "(36, 162, 163, 165, 8364, 164)" - ] + "text/plain": "[0, 1, 2, 3, 4]" }, - "execution_count": 10, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "symbols = '$¢£¥€¤'\n", - "tuple(ord(symbol) for symbol in symbols)" - ] + "[*range(4), 4]" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, + "execution_count": 35, "outputs": [ { "data": { - "text/plain": [ - "array('I', [36, 162, 163, 165, 8364, 164])" - ] + "text/plain": "{0, 1, 2, 3, 4, 5, 6, 7}" }, - "execution_count": 11, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import array\n", - "array.array('I', (ord(symbol) for symbol in symbols))" - ] + "{*range(4), 4, *(5, 6, 7)}" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "markdown", - "metadata": {}, "source": [ - "#### Example 2-6. Cartesian product in a generator expression" - ] + "### Nested unpacking\n", + "#### Example 2-8. Unpacking nested tuples to access the longitude\n", + "\n", + "[02-array-seq/metro_lat_lon.py](02-array-seq/metro_lat_lon.py)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "## Pattern Matching with Sequences\n", + "#### Example 2-9. Method from an imaginary Robot class" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } }, { "cell_type": "code", - "execution_count": 12, - "metadata": {}, + "execution_count": 36, + "outputs": [], + "source": [ + "# def handle_command(self, message):\n", + "# match message:\n", + "# case ['BEEPER', frequency, times]:\n", + "# self.beep(times, frequency)\n", + "# case ['NECK', angle]:\n", + "# self.rotate_neck(angle)\n", + "# case ['LED', ident, intensity]:\n", + "# self.leds[ident].set_brightness(ident, intensity)\n", + "# case ['LED', ident, red, green, blue]:\n", + "# self.leds[ident].set_color(ident, red, green, blue)\n", + "# case _:\n", + "# raise InvalidCommand(message)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "#### Example 2-10. Destructuring nested tuples—requires Python ≥ 3.10.\n", + "[02-array-seq/match_lat_lon.py](02-array-seq/match_lat_lon.py)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 37, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "black S\n", - "black M\n", - "black L\n", - "white S\n", - "white M\n", - "white L\n" + " | latitude | longitude\n", + "Mexico City | 19.4333 | -99.1333\n", + "New York-Newark | 40.8086 | -74.0204\n", + "São Paulo | -23.5478 | -46.6358\n" ] } ], "source": [ - "colors = ['black', 'white']\n", - "sizes = ['S', 'M', 'L']\n", + "metro_areas = [\n", + " ('Tokyo', 'JP', 36.933, (35.689722, 139.691667)),\n", + " ('Delhi NCR', 'IN', 21.935, (28.613889, 77.208889)),\n", + " ('Mexico City', 'MX', 20.142, (19.433333, -99.133333)),\n", + " ('New York-Newark', 'US', 20.104, (40.808611, -74.020386)),\n", + " ('São Paulo', 'BR', 19.649, (-23.547778, -46.635833)),\n", + "]\n", "\n", - "for tshirt in ('%s %s' % (c, s) for c in colors for s in sizes):\n", - " print(tshirt)" - ] + "def main():\n", + " print(f'{\"\":15} | {\"latitude\":>9} | {\"longitude\":>9}')\n", + " for record in metro_areas:\n", + " match record:\n", + " case [name, _, _, (lat, lon)] if lon <= 0:\n", + " print(f'{name:15} | {lat:9.4f} | {lon:9.4f}')\n", + "main()" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "### Pattern Matching Sequences in an Interpreter\n", + "#### Example 2-11. Matching patterns without match/case.\n", + "[02-array-seq/lispy/py3.9/lis.py](02-array-seq/lispy/py3.9/lis.py)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "markdown", + "source": [ + "#### Example 2-12. Pattern matching with match/case—requires Python ≥ 3.10.\n", + "[02-array-seq/lispy/py3.10/lis.py](02-array-seq/lispy/py3.10/lis.py)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + } }, { "cell_type": "markdown", @@ -375,16 +1137,14 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 38, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[10, 20]" - ] + "text/plain": "[10, 20]" }, - "execution_count": 13, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -397,16 +1157,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 39, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[30, 40, 50, 60]" - ] + "text/plain": "[30, 40, 50, 60]" }, - "execution_count": 14, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -417,16 +1175,14 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[10, 20, 30]" - ] + "text/plain": "[10, 20, 30]" }, - "execution_count": 15, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -437,16 +1193,14 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 41, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[40, 50, 60]" - ] + "text/plain": "[40, 50, 60]" }, - "execution_count": 16, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -464,16 +1218,14 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 42, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "'bye'" - ] + "text/plain": "'bye'" }, - "execution_count": 17, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -485,16 +1237,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 43, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "'elcycib'" - ] + "text/plain": "'elcycib'" }, - "execution_count": 18, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } @@ -505,16 +1255,14 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "'eccb'" - ] + "text/plain": "'eccb'" }, - "execution_count": 19, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -527,12 +1275,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-9. Line items from a flat-file invoice" + "#### Example 2-13. Line items from a flat-file invoice" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -577,16 +1325,14 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 46, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]" - ] + "text/plain": "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]" }, - "execution_count": 21, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" } @@ -598,16 +1344,14 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 47, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, 1, 20, 30, 5, 6, 7, 8, 9]" - ] + "text/plain": "[0, 1, 20, 30, 5, 6, 7, 8, 9]" }, - "execution_count": 22, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } @@ -619,16 +1363,14 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 48, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, 1, 20, 30, 5, 8, 9]" - ] + "text/plain": "[0, 1, 20, 30, 5, 8, 9]" }, - "execution_count": 23, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" } @@ -640,16 +1382,14 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 49, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, 1, 20, 11, 5, 22, 9]" - ] + "text/plain": "[0, 1, 20, 11, 5, 22, 9]" }, - "execution_count": 24, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } @@ -668,7 +1408,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -688,16 +1428,14 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 51, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, 1, 100, 22, 9]" - ] + "text/plain": "[0, 1, 100, 22, 9]" }, - "execution_count": 26, + "execution_count": 51, "metadata": {}, "output_type": "execute_result" } @@ -711,21 +1449,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Using + and * with Sequences" + "## Using + and * with Sequences" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 52, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3]" - ] + "text/plain": "[1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3]" }, - "execution_count": 27, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } @@ -737,16 +1473,14 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 53, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "'abcdabcdabcdabcdabcd'" - ] + "text/plain": "'abcdabcdabcdabcdabcd'" }, - "execution_count": 28, + "execution_count": 53, "metadata": {}, "output_type": "execute_result" } @@ -766,21 +1500,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-10. A list with three lists of length 3 can represent a tic-tac-toe board" + "#### Example 2-14. A list with three lists of length 3 can represent a tic-tac-toe board" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 54, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" - ] + "text/plain": "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" }, - "execution_count": 29, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } @@ -792,16 +1524,14 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 55, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', '_'], ['_', '_', 'X'], ['_', '_', '_']]" - ] + "text/plain": "[['_', '_', '_'], ['_', '_', 'X'], ['_', '_', '_']]" }, - "execution_count": 30, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } @@ -815,21 +1545,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-11. A list with three references to the same list is useless" + "#### Example 2-15. A list with three references to the same list is useless" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 56, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" - ] + "text/plain": "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" }, - "execution_count": 31, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -841,16 +1569,14 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 57, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', 'O'], ['_', '_', 'O'], ['_', '_', 'O']]" - ] + "text/plain": "[['_', '_', 'O'], ['_', '_', 'O'], ['_', '_', 'O']]" }, - "execution_count": 32, + "execution_count": 57, "metadata": {}, "output_type": "execute_result" } @@ -869,16 +1595,14 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 58, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" - ] + "text/plain": "[['_', '_', '_'], ['_', '_', '_'], ['_', '_', '_']]" }, - "execution_count": 33, + "execution_count": 58, "metadata": {}, "output_type": "execute_result" } @@ -893,16 +1617,14 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 59, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[['_', '_', '_'], ['_', '_', '_'], ['X', '_', '_']]" - ] + "text/plain": "[['_', '_', '_'], ['_', '_', '_'], ['X', '_', '_']]" }, - "execution_count": 34, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" } @@ -921,7 +1643,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 60, "metadata": {}, "outputs": [], "source": [ @@ -931,16 +1653,14 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 61, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "4414271936" - ] + "text/plain": "140694277263808" }, - "execution_count": 36, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -952,16 +1672,14 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 62, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[1, 2, 3, 1, 2, 3]" - ] + "text/plain": "[1, 2, 3, 1, 2, 3]" }, - "execution_count": 37, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } @@ -973,16 +1691,14 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 63, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "True" - ] + "text/plain": "True" }, - "execution_count": 38, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } @@ -993,7 +1709,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ @@ -1003,16 +1719,14 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 65, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "4414275328" - ] + "text/plain": "140694329335488" }, - "execution_count": 40, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } @@ -1024,35 +1738,34 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 66, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "False" - ] + "text/plain": "False" }, - "execution_count": 41, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t *= 2\n", - "id(t) == idt # new tuple" + "id(t) == idt # new tuple" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### A += Assignment Puzzler" + "### A += Assignment Puzzler\n", + "#### Example 2-16. A riddle" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -1071,18 +1784,28 @@ " print(repr(e))" ] }, + { + "cell_type": "markdown", + "source": [ + "#### Example 2-17. The unexpected result: item t2 is changed and an exception is raised" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 68, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "(1, 2, [30, 40, 50, 60])" - ] + "text/plain": "(1, 2, [30, 40, 50, 60])" }, - "execution_count": 43, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } @@ -1095,12 +1818,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-14. Bytecode for the expression s[a] += b" + "#### Example 2-18. Bytecode for the expression s[a] += b" ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 69, "metadata": {}, "outputs": [ { @@ -1135,16 +1858,14 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 70, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['apple', 'banana', 'grape', 'raspberry']" - ] + "text/plain": "['apple', 'banana', 'grape', 'raspberry']" }, - "execution_count": 45, + "execution_count": 70, "metadata": {}, "output_type": "execute_result" } @@ -1156,16 +1877,14 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 71, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['grape', 'raspberry', 'apple', 'banana']" - ] + "text/plain": "['grape', 'raspberry', 'apple', 'banana']" }, - "execution_count": 46, + "execution_count": 71, "metadata": {}, "output_type": "execute_result" } @@ -1176,16 +1895,14 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 72, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['raspberry', 'grape', 'banana', 'apple']" - ] + "text/plain": "['raspberry', 'grape', 'banana', 'apple']" }, - "execution_count": 47, + "execution_count": 72, "metadata": {}, "output_type": "execute_result" } @@ -1196,16 +1913,14 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 73, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['grape', 'apple', 'banana', 'raspberry']" - ] + "text/plain": "['grape', 'apple', 'banana', 'raspberry']" }, - "execution_count": 48, + "execution_count": 73, "metadata": {}, "output_type": "execute_result" } @@ -1216,16 +1931,14 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 74, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['raspberry', 'banana', 'grape', 'apple']" - ] + "text/plain": "['raspberry', 'banana', 'grape', 'apple']" }, - "execution_count": 49, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" } @@ -1236,16 +1949,14 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 75, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['grape', 'raspberry', 'apple', 'banana']" - ] + "text/plain": "['grape', 'raspberry', 'apple', 'banana']" }, - "execution_count": 50, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" } @@ -1256,16 +1967,14 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 76, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['apple', 'banana', 'grape', 'raspberry']" - ] + "text/plain": "['apple', 'banana', 'grape', 'raspberry']" }, - "execution_count": 51, + "execution_count": 76, "metadata": {}, "output_type": "execute_result" } @@ -1279,322 +1988,231 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Managing Ordered Sequences with bisect" + "## When a List Is Not the Answer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-15. bisect finds insertion points for items in a sorted sequence" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEMO: bisect_right\n", - "haystack -> 1 4 5 6 8 12 15 20 21 23 23 26 29 30\n", - "31 @ 14 | | | | | | | | | | | | | |31\n", - "30 @ 14 | | | | | | | | | | | | | |30\n", - "29 @ 13 | | | | | | | | | | | | |29\n", - "23 @ 11 | | | | | | | | | | |23\n", - "22 @ 9 | | | | | | | | |22\n", - "10 @ 5 | | | | |10\n", - " 8 @ 5 | | | | |8 \n", - " 5 @ 3 | | |5 \n", - " 2 @ 1 |2 \n", - " 1 @ 1 |1 \n", - " 0 @ 0 0 \n" - ] - } - ], - "source": [ - "# BEGIN BISECT_DEMO\n", - "import bisect\n", - "import sys\n", - "\n", - "HAYSTACK = [1, 4, 5, 6, 8, 12, 15, 20, 21, 23, 23, 26, 29, 30]\n", - "NEEDLES = [0, 1, 2, 5, 8, 10, 22, 23, 29, 30, 31]\n", - "\n", - "ROW_FMT = '{0:2d} @ {1:2d} {2}{0:<2d}'\n", - "\n", - "def demo(haystack, needles, bisect_fn):\n", - " print('DEMO:', bisect_fn.__name__) # <1>\n", - " print('haystack ->', ' '.join('%2d' % n for n in haystack))\n", - " for needle in reversed(needles):\n", - " position = bisect_fn(haystack, needle) # <2>\n", - " offset = position * ' |' # <3>\n", - " print(ROW_FMT.format(needle, position, offset)) # <4>\n", - "\n", - "demo(HAYSTACK, NEEDLES, bisect.bisect) # <5>\n", - "# END BISECT_DEMO" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DEMO: bisect_left\n", - "haystack -> 1 4 5 6 8 12 15 20 21 23 23 26 29 30\n", - "31 @ 14 | | | | | | | | | | | | | |31\n", - "30 @ 13 | | | | | | | | | | | | |30\n", - "29 @ 12 | | | | | | | | | | | |29\n", - "23 @ 9 | | | | | | | | |23\n", - "22 @ 9 | | | | | | | | |22\n", - "10 @ 5 | | | | |10\n", - " 8 @ 4 | | | |8 \n", - " 5 @ 2 | |5 \n", - " 2 @ 1 |2 \n", - " 1 @ 0 1 \n", - " 0 @ 0 0 \n" - ] - } - ], - "source": [ - "demo(HAYSTACK, NEEDLES, bisect.bisect_left)" + "### Arrays" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-16. Given a test score, grade returns the corresponding letter grade" + "#### Example 2-19. Creating, saving, and loading a large array of floats" ] }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 77, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['F', 'D', 'D', 'C', 'C', 'B', 'B', 'A', 'A']" - ] + "text/plain": "0.8190492979077034" }, - "execution_count": 54, + "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):\n", - " i = bisect.bisect(breakpoints, score)\n", - " return grades[i]\n", + "from array import array\n", + "from random import random, seed\n", + "seed(10) # Use seed to make the output consistent\n", "\n", - "[grade(score) for score in [55, 60, 65, 70, 75, 80, 85, 90, 95]]" + "floats = array('d', (random() for i in range(10 ** 7)))\n", + "floats[-1]" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 78, "metadata": {}, + "outputs": [], "source": [ - "#### Example 2-17. bisect_left maps a score of 60 to grade F, not D as in Example 2-16." + "with open('floats.bin', 'wb') as fp:\n", + " floats.tofile(fp)" ] }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 79, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "['F', 'F', 'D', 'D', 'C', 'C', 'B', 'B', 'A']" - ] + "text/plain": "0.8190492979077034" }, - "execution_count": 55, + "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "def grade(score, breakpoints=[60, 70, 80, 90], grades='FDCBA'):\n", - " i = bisect.bisect_left(breakpoints, score)\n", - " return grades[i]\n", + "floats2 = array('d')\n", "\n", - "[grade(score) for score in [55, 60, 65, 70, 75, 80, 85, 90, 95]]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Example 2-18. Insort keeps a sorted sequence always sorted" + "with open('floats.bin', 'rb') as fp:\n", + " floats2.fromfile(fp, 10 ** 7)\n", + "\n", + "floats2[-1]" ] }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 80, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "insert 10 -> [10]\n", - "insert 0 -> [0, 10]\n", - "insert 6 -> [0, 6, 10]\n", - "insert 8 -> [0, 6, 8, 10]\n", - "insert 7 -> [0, 6, 7, 8, 10]\n", - "insert 2 -> [0, 2, 6, 7, 8, 10]\n", - "insert 10 -> [0, 2, 6, 7, 8, 10, 10]\n" - ] + "data": { + "text/plain": "True" + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "import bisect\n", - "import random\n", - "\n", - "SIZE = 7\n", - "\n", - "random.seed(1729)\n", - "\n", - "my_list = []\n", - "\n", - "for i in range(SIZE):\n", - " new_item = random.randrange(SIZE*2)\n", - " bisect.insort(my_list, new_item)\n", - " print(f'insert {new_item:2d} -> {my_list}')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## When a List Is Not the Answer" + "floats2 == floats" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Arrays" + "### Memory Views" ] }, { "cell_type": "markdown", - "metadata": {}, "source": [ - "#### Example 2-19. Creating, saving, and loading a large array of floats" - ] + "#### Example 2-20. Handling 6 bytes memory of as 1×6, 2×3, and 3×2 views" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } }, { "cell_type": "code", - "execution_count": 57, - "metadata": {}, + "execution_count": 81, "outputs": [ { "data": { - "text/plain": [ - "0.5963321947530882" - ] + "text/plain": "[0, 1, 2, 3, 4, 5]" }, - "execution_count": 57, + "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from array import array\n", - "from random import random\n", - "\n", - "floats = array('d', (random() for i in range(10**7)))\n", - "floats[-1]" - ] + "octets = array('B', range(6))\n", + "m1 = memoryview(octets)\n", + "m1.tolist()" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [], + "execution_count": 82, + "outputs": [ + { + "data": { + "text/plain": "[[0, 1, 2], [3, 4, 5]]" + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "with open('floats.bin', 'wb') as fp:\n", - " floats.tofile(fp)" - ] + "m2 = m1.cast('B', [2, 3])\n", + "m2.tolist()" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 59, - "metadata": {}, + "execution_count": 83, "outputs": [ { "data": { - "text/plain": [ - "0.5963321947530882" - ] + "text/plain": "[[0, 1], [2, 3], [4, 5]]" }, - "execution_count": 59, + "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "floats2 = array('d')\n", - "\n", - "with open('floats.bin', 'rb') as fp:\n", - " floats2.fromfile(fp, 10**7)\n", - "\n", - "floats2[-1]" - ] + "m3 = m1.cast('B', [3, 2])\n", + "m3.tolist()" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "code", - "execution_count": 60, - "metadata": {}, + "execution_count": 84, "outputs": [ { "data": { - "text/plain": [ - "True" - ] + "text/plain": "array('B', [0, 1, 2, 33, 22, 5])" }, - "execution_count": 60, + "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "floats2 == floats" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Memory Views" - ] + "m2[1,1] = 22\n", + "m3[1,1] = 33\n", + "octets" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-20. Changing the value of an array item by poking one of its bytes" + "#### Example 2-21. Changing the value of an 16-bit integer array item by poking one of its bytes" ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 85, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "5" - ] + "text/plain": "5" }, - "execution_count": 61, + "execution_count": 85, "metadata": {}, "output_type": "execute_result" } @@ -1607,16 +2225,14 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 86, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "-2" - ] + "text/plain": "-2" }, - "execution_count": 62, + "execution_count": 86, "metadata": {}, "output_type": "execute_result" } @@ -1627,16 +2243,14 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 87, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[254, 255, 255, 255, 0, 0, 1, 0, 2, 0]" - ] + "text/plain": "[254, 255, 255, 255, 0, 0, 1, 0, 2, 0]" }, - "execution_count": 63, + "execution_count": 87, "metadata": {}, "output_type": "execute_result" } @@ -1648,16 +2262,14 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 88, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array('h', [-2, -1, 1024, 1, 2])" - ] + "text/plain": "array('h', [-2, -1, 1024, 1, 2])" }, - "execution_count": 64, + "execution_count": 88, "metadata": {}, "output_type": "execute_result" } @@ -1671,50 +2283,47 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### NumPy and SciPy" + "### NumPy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-21. Basic operations with rows and columns in a numpy.ndarray" + "#### Example 2-22. Basic operations with rows and columns in a numpy.ndarray" ] }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 89, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])" - ] + "text/plain": "array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])" }, - "execution_count": 65, + "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", + "\n", "a = np.arange(12)\n", "a" ] }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 90, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "numpy.ndarray" - ] + "text/plain": "numpy.ndarray" }, - "execution_count": 66, + "execution_count": 90, "metadata": {}, "output_type": "execute_result" } @@ -1725,16 +2334,14 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 91, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "(12,)" - ] + "text/plain": "(12,)" }, - "execution_count": 67, + "execution_count": 91, "metadata": {}, "output_type": "execute_result" } @@ -1745,18 +2352,14 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 92, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[ 0, 1, 2, 3],\n", - " [ 4, 5, 6, 7],\n", - " [ 8, 9, 10, 11]])" - ] + "text/plain": "array([[ 0, 1, 2, 3],\n [ 4, 5, 6, 7],\n [ 8, 9, 10, 11]])" }, - "execution_count": 68, + "execution_count": 92, "metadata": {}, "output_type": "execute_result" } @@ -1768,16 +2371,14 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 93, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([ 8, 9, 10, 11])" - ] + "text/plain": "array([ 8, 9, 10, 11])" }, - "execution_count": 69, + "execution_count": 93, "metadata": {}, "output_type": "execute_result" } @@ -1788,16 +2389,14 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 94, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "9" - ] + "text/plain": "9" }, - "execution_count": 70, + "execution_count": 94, "metadata": {}, "output_type": "execute_result" } @@ -1808,16 +2407,14 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 95, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([1, 5, 9])" - ] + "text/plain": "array([1, 5, 9])" }, - "execution_count": 71, + "execution_count": 95, "metadata": {}, "output_type": "execute_result" } @@ -1828,25 +2425,20 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 96, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([[ 0, 4, 8],\n", - " [ 1, 5, 9],\n", - " [ 2, 6, 10],\n", - " [ 3, 7, 11]])" - ] + "text/plain": "array([[ 0, 4, 8],\n [ 1, 5, 9],\n [ 2, 6, 10],\n [ 3, 7, 11]])" }, - "execution_count": 72, + "execution_count": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "a.transpose()\n" + "a.transpose()" ] }, { @@ -1858,7 +2450,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 97, "metadata": {}, "outputs": [], "source": [ @@ -1869,7 +2461,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 98, "metadata": {}, "outputs": [], "source": [ @@ -1878,16 +2470,14 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 99, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([0.29150425, 0.33893554, 0.08112756])" - ] + "text/plain": "array([0.06078257, 0.61741189, 0.84349987])" }, - "execution_count": 75, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" } @@ -1898,16 +2488,14 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 100, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "array([0.14575213, 0.16946777, 0.04056378])" - ] + "text/plain": "array([0.03039128, 0.30870594, 0.42174994])" }, - "execution_count": 76, + "execution_count": 100, "metadata": {}, "output_type": "execute_result" } @@ -1919,16 +2507,14 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 101, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "True" - ] + "text/plain": "True" }, - "execution_count": 77, + "execution_count": 101, "metadata": {}, "output_type": "execute_result" } @@ -1943,7 +2529,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 102, "metadata": {}, "outputs": [], "source": [ @@ -1954,16 +2540,14 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 103, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "memmap([0.29150425, 0.33893554, 0.08112756])" - ] + "text/plain": "memmap([0.06078257, 0.61741189, 0.84349987])" }, - "execution_count": 79, + "execution_count": 103, "metadata": {}, "output_type": "execute_result" } @@ -1983,21 +2567,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Example 2-22. Working with a deque" + "#### Example 2-23. Working with a deque" ] }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 104, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" - ] + "text/plain": "deque([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])" }, - "execution_count": 80, + "execution_count": 104, "metadata": {}, "output_type": "execute_result" } @@ -2011,16 +2593,14 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 105, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([7, 8, 9, 0, 1, 2, 3, 4, 5, 6])" - ] + "text/plain": "deque([7, 8, 9, 0, 1, 2, 3, 4, 5, 6])" }, - "execution_count": 81, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -2032,16 +2612,14 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 106, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])" - ] + "text/plain": "deque([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])" }, - "execution_count": 82, + "execution_count": 106, "metadata": {}, "output_type": "execute_result" } @@ -2053,16 +2631,14 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 107, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([-1, 1, 2, 3, 4, 5, 6, 7, 8, 9])" - ] + "text/plain": "deque([-1, 1, 2, 3, 4, 5, 6, 7, 8, 9])" }, - "execution_count": 83, + "execution_count": 107, "metadata": {}, "output_type": "execute_result" } @@ -2074,16 +2650,14 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 108, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([3, 4, 5, 6, 7, 8, 9, 11, 22, 33])" - ] + "text/plain": "deque([3, 4, 5, 6, 7, 8, 9, 11, 22, 33])" }, - "execution_count": 84, + "execution_count": 108, "metadata": {}, "output_type": "execute_result" } @@ -2095,16 +2669,14 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 109, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "deque([40, 30, 20, 10, 3, 4, 5, 6, 7, 8])" - ] + "text/plain": "deque([40, 30, 20, 10, 3, 4, 5, 6, 7, 8])" }, - "execution_count": 85, + "execution_count": 109, "metadata": {}, "output_type": "execute_result" } @@ -2130,7 +2702,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 110, "metadata": {}, "outputs": [], "source": [ @@ -2139,7 +2711,7 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 111, "metadata": {}, "outputs": [ { @@ -2166,16 +2738,14 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 112, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, '1', 5, 6, '9', 14, 19, '23', 28, '28']" - ] + "text/plain": "[0, '1', 5, 6, '9', 14, 19, '23', 28, '28']" }, - "execution_count": 88, + "execution_count": 112, "metadata": {}, "output_type": "execute_result" } @@ -2188,16 +2758,14 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 113, "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "[0, '1', 14, 19, '23', 28, '28', 5, 6, '9']" - ] + "text/plain": "[0, '1', 14, 19, '23', 28, '28', 5, 6, '9']" }, - "execution_count": 89, + "execution_count": 113, "metadata": {}, "output_type": "execute_result" } @@ -2208,7 +2776,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 113, "metadata": {}, "outputs": [], "source": [] @@ -2235,4 +2803,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/02-array-seq/test.sh b/02-array-seq/test.sh index 4747320..906717d 100755 --- a/02-array-seq/test.sh +++ b/02-array-seq/test.sh @@ -1,4 +1,4 @@ #!/bin/bash python3 -m doctest bisect_demo.py -python3 -m doctest metro_lat_long.py +python3 -m doctest metro_lat_lon.py pytest -q --nbval diff --git a/06-obj-ref/README.rst b/06-obj-ref/README.rst index deac2fa..0d705e6 100644 --- a/06-obj-ref/README.rst +++ b/06-obj-ref/README.rst @@ -1,4 +1,4 @@ -Sample code for Chapter 8 - "Object references, mutability and recycling" +Sample code for Chapter 6 - "Object references, mutability and recycling" From the book "Fluent Python" by Luciano Ramalho (O'Reilly, 2015) http://shop.oreilly.com/product/0636920032519.do diff --git a/08-def-type-hints/callable/variance.py b/08-def-type-hints/callable/variance.py new file mode 100644 index 0000000..fcddbde --- /dev/null +++ b/08-def-type-hints/callable/variance.py @@ -0,0 +1,22 @@ +from collections.abc import Callable + +def update( # <1> + probe: Callable[[], float], # <2> + display: Callable[[float], None] # <3> + ) -> None: + temperature = probe() + # imagine lots of control code here + display(temperature) + +def probe_ok() -> int: # <4> + return 42 + +def display_wrong(temperature: int) -> None: # <5> + print(hex(temperature)) + +update(probe_ok, display_wrong) # type error # <6> + +def display_ok(temperature: complex) -> None: # <7> + print(temperature) + +update(probe_ok, display_ok) # OK # <8> diff --git a/08-def-type-hints/coordinates/requirements.txt b/08-def-type-hints/coordinates/requirements.txt index fb11094..7b7b424 100644 --- a/08-def-type-hints/coordinates/requirements.txt +++ b/08-def-type-hints/coordinates/requirements.txt @@ -1,2 +1,2 @@ geolib==1.0.7 -future==0.18.2 +future==0.18.3 diff --git a/17-it-generator/columnize_iter.py b/17-it-generator/columnize_iter.py index cee0f13..4362bc1 100644 --- a/17-it-generator/columnize_iter.py +++ b/17-it-generator/columnize_iter.py @@ -6,8 +6,8 @@ def columnize( ) -> Iterator[tuple[str, ...]]: # <1> if num_columns == 0: num_columns = round(len(sequence) ** 0.5) - num_rows, reminder = divmod(len(sequence), num_columns) - num_rows += bool(reminder) + num_rows, remainder = divmod(len(sequence), num_columns) + num_rows += bool(remainder) return (tuple(sequence[i::num_rows]) for i in range(num_rows)) # <2> # end::COLUMNIZE[] diff --git a/20-executors/getflags/flags2_asyncio.py b/20-executors/getflags/flags2_asyncio.py index 4f1849a..b697840 100755 --- a/20-executors/getflags/flags2_asyncio.py +++ b/20-executors/getflags/flags2_asyncio.py @@ -79,6 +79,8 @@ async def supervisor(cc_list: list[str], error = exc # <10> except KeyboardInterrupt: break + else: + error = None if error: status = DownloadStatus.ERROR # <11> diff --git a/20-executors/getflags/requirements.txt b/20-executors/getflags/requirements.txt index b8bb630..9b1faeb 100644 --- a/20-executors/getflags/requirements.txt +++ b/20-executors/getflags/requirements.txt @@ -1,10 +1,10 @@ anyio==3.3.2 -certifi==2021.5.30 +certifi==2024.7.4 charset-normalizer==2.0.6 -h11==0.12.0 +h11==0.16.0 httpcore==0.13.7 httpx==1.0.0b0 -idna==3.2 +idna==3.7 rfc3986==1.5.0 sniffio==1.2.0 -tqdm==4.62.3 +tqdm==4.66.3 diff --git a/21-async/mojifinder/requirements.txt b/21-async/mojifinder/requirements.txt index 1f7c3d6..6831fee 100644 --- a/21-async/mojifinder/requirements.txt +++ b/21-async/mojifinder/requirements.txt @@ -1,7 +1,7 @@ click==7.1.2 fastapi==0.65.2 -h11==0.12.0 -pydantic==1.8.2 -starlette==0.13.6 +h11==0.16.0 +pydantic==1.10.13 +starlette==0.40.0 typing-extensions==3.7.4.3 uvicorn==0.13.4 diff --git a/README.md b/README.md index 96273ac..234c8da 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,7 @@ # Fluent Python 2e example code -Example code for the book **Fluent Python, 2nd edition** by Luciano Ramalho (O'Reilly, 2021). +Example code for the book **Fluent Python, Second Edition** by Luciano Ramalho (O'Reilly, 2022). -> **BEWARE**: This is a work in progress! -> -> * Code here may change and disappear without warning. -> -> * Major reorganizations may happen at any time. -> -> * No promises. No guarantees. Use at own risk. ## Table of Contents @@ -16,37 +9,37 @@ All chapters are undergoing review and updates, including significant rewrites i New chapters in **Fluent Python 2e** are marked with 🆕. -🚨 This table of contents is subject to change at any time until the book goes to the printer. +> 🚨  This table of contents is subject to change at any time until the book goes to the printer.
+Latest change: Old **Part I—Prologue** merged into new **Part I—Data Structures**; parts renumbered accordingly; chapter numbers unchanged. Part / Chapter #|Title|Directory|1st ed. Chapter # ---:|---|---|:---: -**I – Prologue**| +**I – Data Structures**| 1|The Python Data Model|[01-data-model](01-data-model)|1 -**II – Data Structures**| 2|An Array of Sequences|[02-array-seq](02-array-seq)|2 3|Dictionaries and Sets|[03-dict-set](03-dict-set)|3 4|Unicode Text versus Bytes|[04-text-byte](04-text-byte)|4 5|Data Class Builders|[05-data-classes](05-data-classes)|🆕 6|Object References, Mutability, and Recycling|[06-obj-ref](06-obj-ref)|8 -**III – Functions as Objects**| +**II – Functions as Objects**| 7|Funcions as First-Class Objects|[07-1class-func](07-1class-func)|5 -8|Type Hints in Function Definitions|[08-def-type-hints](08-def-type-hints)|🆕 -9|Function Decorators and Closures|[09-closure-deco](09-closure-deco)|7 +8|Type Hints in Functions|[08-def-type-hints](08-def-type-hints)|🆕 +9|Decorators and Closures|[09-closure-deco](09-closure-deco)|7 10|Design Patterns with First-Class Functions|[10-dp-1class-func](10-dp-1class-func)|6 -**IV – Object-Oriented Idioms**| +**III – Object-Oriented Idioms**| 11|A Pythonic Object|[11-pythonic-obj](11-pythonic-obj)|9 -12|Sequence Hacking, Hashing, and Slicing|[12-seq-hacking](12-seq-hacking)|10 +12|Special Methods for Sequences|[12-seq-hacking](12-seq-hacking)|10 13|Interfaces, Protocols, and ABCs|[13-protocl-abc](13-protocol-abc)|11 -14|Inheritance: For Good or For Worse|[14-inheritance](14-inheritance)|12 +14|Inheritance: For Better or For Worse|[14-inheritance](14-inheritance)|12 15|More About Type Hints|[15-more-types](15-more-types)|🆕 -16|Operator Overloading: Doing It Right|[16-op-overloading](16-op-overloading)|13 -**V – Control Flow**| +16|Operator Overloading|[16-op-overloading](16-op-overloading)|13 +**IV – Control Flow**| 17|Iterators, Generators, and Classic Coroutines|[17-it-generator](17-it-generator)|14 -18|Context Managers and else Blocks|[18-with-match](18-with-match)|15 +18|with, match, and else Blocks|[18-with-match](18-with-match)|15 19|Concurrency Models in Python|[19-concurrency](19-concurrency)|🆕 20|Concurrent Executors|[20-executors](20-executors)|17 21|Asynchronous Programming|[21-async](21-async)|18 -**VI – Metaprogramming**| +**V – Metaprogramming**| 22|Dynamic Attributes and Properties|[22-dyn-attr-prop](22-dyn-attr-prop)|19 23|Attribute Descriptors|[23-descriptor](23-descriptor)|20 24|Class Metaprogramming|[24-class-metaprog](24-class-metaprog)|21 diff --git a/links/FPY.LI.htaccess b/links/FPY.LI.htaccess index 6e324d0..5607fa4 100644 --- a/links/FPY.LI.htaccess +++ b/links/FPY.LI.htaccess @@ -1,3 +1,6 @@ +# to recreate or update this file: +# $ cat custom.htaccess short.htaccess > FPY.LI.htaccess + ErrorDocument 404 /404.html # main resources @@ -35,6 +38,9 @@ RedirectTemp /typecoro https://docs.python.org/3.10/library/typing.html#typing.C RedirectTemp /typing https://docs.python.org/3/library/typing.html RedirectTemp /weakref https://www.fluentpython.com/extra/weak-references/ +# URL added during QA of the Second Edition +RedirectTemp /bdfl https://www.artima.com/weblogs/viewpost.jsp?thread=235725 + # Python Enhancement Proposals RedirectTemp /pep218 https://www.python.org/dev/peps/pep-0218/ RedirectTemp /pep227 https://www.python.org/dev/peps/pep-0227/ @@ -149,7 +155,7 @@ RedirectTemp /a-18 https://www.python.org/doc/essays/ RedirectTemp /1-1 http://hugunin.net/story_of_jython.html RedirectTemp /1-2 https://www.oreilly.com/library/view/jython-essentials/9781449397364/ RedirectTemp /1-3 https://docs.python.org/3/reference/lexical_analysis.html#reserved-classes-of-identifiers -RedirectTemp /1-4 https://docs.python.org/2/library/string.html#format-string-syntax +RedirectTemp /1-4 https://docs.python.org/3.10/library/string.html#format-string-syntax RedirectTemp /1-5 https://stackoverflow.com/questions/1436703/what-is-the-difference-between-str-and-repr RedirectTemp /1-6 https://docs.python.org/3/library/stdtypes.html#truth RedirectTemp /1-7 https://docs.python.org/3/tutorial/controlflow.html#unpacking-argument-lists @@ -1067,3 +1073,17 @@ RedirectTemp /24-27 https://docs.python.org/3/library/functools.html#functools.t RedirectTemp /24-28 https://www.python.org/download/releases/2.2.3/descrintro/ RedirectTemp /24-29 https://github.com/lihaoyi/macropy RedirectTemp /24-30 https://people.eecs.berkeley.edu/~bh/ss-toc2.html +# content of short.htaccess file created and managed by short.py + +# appended: 2025-05-23 15:12:13 +RedirectTemp /22 https://pythonfluente.com/2/#pattern_matching_case_study_sec +RedirectTemp /23 https://pythonfluente.com/2/#how_slicing_works +RedirectTemp /24 https://pythonfluente.com/2/#sliceable_sequence +RedirectTemp /25 https://pythonfluente.com/2/#virtual_subclass_sec +RedirectTemp /26 https://pythonfluente.com/2/#environment_class_ex +RedirectTemp /27 https://pythonfluente.com/2/#subclass_builtin_woes +RedirectTemp /28 https://pythonfluente.com/2/#slots_section +RedirectTemp /29 https://pythonfluente.com/2/#typeddict_sec +RedirectTemp /2a https://pythonfluente.com/2/#problems_annot_runtime_sec +RedirectTemp /2b https://pythonfluente.com/2/#legacy_deprecated_typing_box +RedirectTemp /2c https://pythonfluente.com/2/#positional_pattern_implement_sec diff --git a/links/README.md b/links/README.md index 09c808a..65749b2 100644 --- a/links/README.md +++ b/links/README.md @@ -1,37 +1,6 @@ -# Short links for URLs in the book +This file is deployed as `.htaccess` to the FPY.LI domain +to map short URLs in Fluent Python to the original URLs. -## Problem: link rot +To update it, I use tools in this other repo: -_Fluent Python, Second Edition_ has more than 1000 links to external resources. -Inevitably, some of those links will rot as time passes. -But I can't change the URLs in the print book... - -## Solution: indirection - -I replaced almost all URLs in the book with shortened versions that go through the `fpy.li` site which I control. -The site has an `.htaccess` file with *temporary* redirects. - -When I find out a link is stale, I can thange the redirect in `.htaccess` to a new target, -so the link in the book is back in service through the updated redirect. - -## Help wanted - -Please report broken links as bugs in the [`FPY.LI.htaccess`](FPY.LI.htaccess) file. -Also, feel free to send pull requests with fixes to that file. -When I accept a PR, I will redeploy it to `fpy.li/.htaccess`. - -## Details - -Almost all URLs in the book are replaced with shortened versions like -[`http://fpy.li/1-3`](http://fpy.li/1-3)—for chapter 1, link #3. - -There are also custom short URLs like -[`https://fpy.li/code`](https://fpy.li/code) which redirects to the example code repository. -I used custom short URLs for URLs with 3 or more mentions, or links to PEPs. - -Exceptions: - -- URLs with `oreilly` in them are unchanged; -- `fluentpython.com` URL (with no path) is unchanged; - -The `FPY.LI.htaccess` is deployed at the root folder in `http://fpy.li`. +https://github.com/pythonfluente/pythonfluente2e diff --git a/links/custom.htaccess b/links/custom.htaccess deleted file mode 100644 index a13b9f8..0000000 --- a/links/custom.htaccess +++ /dev/null @@ -1,113 +0,0 @@ -ErrorDocument 404 /404.html - -# main resources -RedirectTemp /book https://www.oreilly.com/library/view/fluent-python-2nd/9781492056348/ -RedirectTemp /code https://github.com/fluentpython/example-code-2e -RedirectTemp /home https://www.fluentpython.com/ - -# URLs mentioned at least three times -RedirectTemp /bisect https://www.fluentpython.com/extra/ordered-sequences-with-bisect/ -RedirectTemp /cardxvi https://www.python.org/dev/peps/pep-0484/#the-numeric-tower -RedirectTemp /collec https://docs.python.org/3/library/collections.html -RedirectTemp /dask https://dask.org/ -RedirectTemp /dtmodel https://docs.python.org/3/reference/datamodel.html -RedirectTemp /descr101 https://www.python.org/download/releases/2.2.3/descrintro/ -RedirectTemp /descrhow 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