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chore: ch2 note - tuple attribution & copy/ deepcopy
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‎02-array-seq/array-seq.ipynb‎

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@@ -490,9 +490,45 @@
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"#### Example 2-7. Tuples used as records"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`tuple` 只能接一個引數，並且**可以排序**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"TypeError: tuple expected at most 1 argument, got 2\n",
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"AttributeError: 'tuple' object has no attribute 'sort'\n",
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"[-118.408056, 33.9425]\n"
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]
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}
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],
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"source": [
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"try:\n",
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" lax_coordinates = tuple(33.9425, -118.408056)\n",
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"except TypeError: \n",
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" print(\"TypeError: tuple expected at most 1 argument, got 2\")\n",
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"\n",
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"lax_coordinates = tuple((33.9425, -118.408056))\n",
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"try:\n",
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" lax_coordinates.sort()\n",
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"except AttributeError:\n",
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" print(\"AttributeError: 'tuple' object has no attribute 'sort'\")\n",
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"print(sorted(lax_coordinates))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -504,6 +540,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<class 'tuple'>\n",
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"BRA/CE342567\n",
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"ESP/XDA205856\n",
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"USA/31195855\n"
@@ -512,6 +549,8 @@
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],
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"source": [
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"lax_coordinates = (33.9425, -118.408056)\n",
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"print(type(lax_coordinates))\n",
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"\n",
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"city, year, pop, chg, area = ('Tokyo', 2003, 32_450, 0.66, 8014)\n",
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"traveler_ids = [('USA', '31195855'), ('BRA', 'CE342567'), ('ESP', 'XDA205856')]\n",
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"\n",
@@ -521,7 +560,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 2,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -558,7 +597,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 7,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -572,7 +611,7 @@
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"True"
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]
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},
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"execution_count": 16,
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -585,7 +624,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 8,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -599,7 +638,7 @@
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"False"
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]
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},
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"execution_count": 17,
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -611,7 +650,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 9,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -625,7 +664,7 @@
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"(10, 'alpha', [1, 2, 99])"
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]
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},
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"execution_count": 18,
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -636,7 +675,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 10,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -650,7 +689,7 @@
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"True"
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]
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},
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"execution_count": 19,
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -671,7 +710,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 11,
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"metadata": {
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"collapsed": false,
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"pycharm": {
@@ -685,7 +724,7 @@
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"False"
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]
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},
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"execution_count": 20,
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -694,6 +733,81 @@
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"fixed(tm)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`tuple` 可以相加串接"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(10, 'alpha', (1, 2), 10, 'alpha', [1, 2])"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tf + tm"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`tuple` **不能使用** `tuple.copy()`\n",
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"- `copy.copy()`（淺拷貝, shallow copy）\n",
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" - 只複製最外層的容器物件，裡面的巢狀物件（例如 list 裡的 list）只是參考（reference）。\n",
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" - 也就是說，內層的資料仍指向原本的記憶體位置，兩者共享。 \n",
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"- `copy.deepcopy()`（深拷貝, deep copy）\n",
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" - 遞迴地複製所有巢狀物件。\n",
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" - 原物件與拷貝物件完全獨立，改其中一個不會影響另一個。\n",
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"\n",
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"| 功能 | `copy.copy()`（淺拷貝） | `copy.deepcopy()`（深拷貝） |\n",
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"| -------- | ------------------ | ---------------------- |\n",
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"| 複製外層 | ✅ | ✅ |\n",
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"| 複製內層巢狀物件 | ❌（參照原物件） | ✅（新建物件） |\n",
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"| 速度與效能 | 較快 | 較慢（因為遞迴複製） |\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"'tuple' object has no attribute 'copy'\n",
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"tf_copy = (10, 'alpha', (1, 2))\n",
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"tf_deepcopy = (10, 'alpha', (1, 2))\n"
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]
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}
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],
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"source": [
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"try:\n",
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" tf_copy = tf.copy()\n",
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"except AttributeError: \n",
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" print(\"'tuple' object has no attribute 'copy'\")\n",
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"\n",
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"from copy import copy, deepcopy\n",
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"\n",
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"tf_copy = copy(tf)\n",
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"print(f\"tf_copy = {tf_copy}\")\n",
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"tf_deepcopy = deepcopy(tf)\n",
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"print(f\"tf_deepcopy = {tf_deepcopy}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {

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