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serge-sans-pailleserge-sans-paille
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Make all nbval notebook Python3 notebooks
Toward 2020!
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4 files changed

+100
-54
lines changed

4 files changed

+100
-54
lines changed

‎pythran/tests/notebooks/capsule.ipynb

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@@ -209,21 +209,21 @@
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"display_name": "Python 3",
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"language": "python",
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"name": "python2"
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.14+"
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,

‎pythran/tests/notebooks/export.ipynb

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@@ -358,14 +358,60 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It also works correctly for ndarray of different dimension and dtype:"
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"It works fine for scalars of differents size / sign"
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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": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%pythran\n",
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"#pythran export dtype(complex64)\n",
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"#pythran export dtype(complex128)\n",
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"#pythran export dtype(complex256)\n",
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"import numpy as np\n",
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"def dtype(x): return x.real, x.imag"
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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": 20,
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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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"(1.5, -1.5) <class 'numpy.float32'>\n",
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"(1.5, -1.5) <class 'float'>\n",
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"(1.5, -1.5) <class 'numpy.float128'>\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"x64 = dtype(np.complex64(1.5 + -1.5j))\n",
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"print(x64, type(x64[0]))\n",
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"x128 = dtype(np.complex128(1.5 + -1.5j))\n",
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"print(x128, type(x128[0]))\n",
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"x256 = dtype(np.complex256(1.5 + -1.5j))\n",
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"print(x256, type(x256[0]))"
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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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"It also works correctly for ndarray of different dimension and dtype:"
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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": 21,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%pythran\n",
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"#pythran export array(int8[])\n",
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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": 22,
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"metadata": {},
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"outputs": [
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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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"It is however ambiguous to use numpy's dtype of different size/sign as scalar across overloads"
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"It is however ambiguous to use numpy's dtype that actually have the same sign and size (in that case on a 64bit machine)"
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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": 21,
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"execution_count": 23,
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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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"Ambiguous overloads\n",
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"\tambiguous(float64)\n",
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"\tambiguous(float32).\n"
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"\tambiguous(int64)\n",
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"\tambiguous(int).\n"
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]
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}
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],
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"source": [
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"code = '''\n",
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"#pythran export ambiguous(float32)\n",
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"#pythran export ambiguous(float64)\n",
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"#pythran export ambiguous(int)\n",
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"#pythran export ambiguous(int64)\n",
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"def ambiguous(x): return x\n",
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"'''\n",
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"try:\n",
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"metadata": {},
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"outputs": [
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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": 26,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"outputs": [
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{
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"(1, '1')"
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]
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},
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"execution_count": 25,
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"execution_count": 27,
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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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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {},
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"outputs": [
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{
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"'stuff that matter'"
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]
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},
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"execution_count": 27,
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"execution_count": 29,
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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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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"execution_count": 31,
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"metadata": {},
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"outputs": [
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{
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"'<capsule object \"corp(int, float)\" at 0x...'"
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]
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},
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"execution_count": 29,
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"execution_count": 31,
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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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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"metadata": {},
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {},
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"outputs": [
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{
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"4"
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]
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},
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"execution_count": 32,
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"execution_count": 34,
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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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"cell_type": "code",
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},
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"cell_type": "code",
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},
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{
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},
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"cell_type": "code",
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},
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"metadata": {},
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"outputs": [
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{
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"((5, 1), (1, 5))"
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]
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},
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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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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"display_name": "Python 3",
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"language": "python",
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"name": "python2"
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.14+"
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,

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