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{ | |
"cells": [ | |
{ | |
"attachments": {}, | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"Decimals show up with a large precision because ... computers. 🙈 If you're interested in the background, watch [this video](https://www.youtube.com/watch?v=8afbTaA-gOQ)." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('1.5500000000000000444089209850062616169452667236328125')" | |
] | |
}, | |
"execution_count": 1, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"import decimal\n", | |
"decimal.Decimal(1.55)" | |
] | |
}, | |
{ | |
"attachments": {}, | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"Adding two Decimals will give you a result with high precision." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('3.100000000000000088817841970')" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"decimal.Decimal(1.55) + decimal.Decimal(1.55)" | |
] | |
}, | |
{ | |
"attachments": {}, | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"However you can set a global (or local) precision in the decimal context:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"context = decimal.getcontext()\n", | |
"context.prec = 5\n", | |
"\n", | |
"decimal.setcontext(context)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"Which does not have effect on the display of the number. That display is just the value in memory." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('1.5500000000000000444089209850062616169452667236328125')" | |
] | |
}, | |
"execution_count": 4, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"decimal.Decimal(1.55)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"But it does have impact on caluclations with decimals. They will honor the new precision." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('3.1000')" | |
] | |
}, | |
"execution_count": 5, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"decimal.Decimal(1.55) + decimal.Decimal(1.55)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('0.52632')" | |
] | |
}, | |
"execution_count": 6, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"\n", | |
"decimal.Decimal(1.23456789) / decimal.Decimal(2.34567890)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"Quantize Operations work too" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Decimal('1.24')" | |
] | |
}, | |
"execution_count": 7, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"decimal.Decimal(1.23456789).quantize(decimal.Decimal(\"0.01\"), rounding=decimal.ROUND_UP)" | |
] | |
}, | |
{ | |
"attachments": {}, | |
"cell_type": "markdown", | |
"metadata": { | |
"collapsed": false | |
}, | |
"source": [ | |
"But their exponent length must not exceed the context precision." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"ename": "InvalidOperation", | |
"evalue": "[<class 'decimal.InvalidOperation'>]", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mInvalidOperation\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn [8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m decimal\u001b[39m.\u001b[39;49mDecimal(\u001b[39m1.23456789\u001b[39;49m)\u001b[39m.\u001b[39;49mquantize(decimal\u001b[39m.\u001b[39;49mDecimal(\u001b[39m\"\u001b[39;49m\u001b[39m0.00001\u001b[39;49m\u001b[39m\"\u001b[39;49m), rounding\u001b[39m=\u001b[39;49mdecimal\u001b[39m.\u001b[39;49mROUND_UP)\n", | |
"\u001b[0;31mInvalidOperation\u001b[0m: [<class 'decimal.InvalidOperation'>]" | |
] | |
} | |
], | |
"source": [ | |
"decimal.Decimal(1.23456789).quantize(decimal.Decimal(\"0.00001\"), rounding=decimal.ROUND_UP)" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.11.0" | |
}, | |
"vscode": { | |
"interpreter": { | |
"hash": "bbd4ab6cee4fbadc42120d79571a0419777e4c09f1fba222b628301c5d986467" | |
} | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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