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/* | ||
Copyright (c) 2019-2026, Hossein Moein | ||
All rights reserved. | ||
Redistribution and use in source and binary forms, with or without | ||
modification, are permitted provided that the following conditions are met: | ||
* Redistributions of source code must retain the above copyright | ||
notice, this list of conditions and the following disclaimer. | ||
* Redistributions in binary form must reproduce the above copyright | ||
notice, this list of conditions and the following disclaimer in the | ||
documentation and/or other materials provided with the distribution. | ||
* Neither the name of Hossein Moein and/or the DataFrame nor the | ||
names of its contributors may be used to endorse or promote products | ||
derived from this software without specific prior written permission. | ||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | ||
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
DISCLAIMED. IN NO EVENT SHALL Hossein Moein BE LIABLE FOR ANY | ||
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
*/ | ||
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#include <DataFrame/DataFrame.h> | ||
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#include <chrono> | ||
#include <cstdint> | ||
#include <cstdlib> | ||
#include <ctime> | ||
#include <iostream> | ||
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using namespace hmdf; | ||
using namespace std::chrono; | ||
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// A DataFrame with long type index | ||
// | ||
using MyDataFrame = StdDataFrame<long>; | ||
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// ----------------------------------------------------------------------------- | ||
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int main(int, char *[]) { | ||
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/* | ||
std::ofstream stream; | ||
stream.open("Large_File.csv"); | ||
stream << "INDEX:200000000:<long>,COL1:200000000:<uint>,COL2:200000000:<int>,COL3:200000000:<int>,COL4:200000000:<int>,COL5:200000000:<ulong>,COL6:200000000:<int>,COL7:200000000:<ulong>\n"; | ||
std::srand(std::time(nullptr)); | ||
for (std::size_t i = 0; i < 200000000; ++i) { | ||
stream << i << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << ',' | ||
<< std::rand() << '\n'; | ||
} | ||
stream.close(); | ||
*/ | ||
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MyDataFrame df; | ||
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const auto start = std::chrono::high_resolution_clock::now(); | ||
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try { | ||
df.read("Large_File.csv", io_format::csv2); | ||
} | ||
catch (const DataFrameError &ex) { | ||
std::cout << ex.what() << std::endl; | ||
} | ||
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const auto end = std::chrono::high_resolution_clock::now(); | ||
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std::cout << "Column Length: " | ||
<< df.get_column<int>("COL6").size() << '\n'; | ||
std::cout | ||
<< "Reading Took: " | ||
<< double(duration_cast<microseconds>(end - start).count()) / 1000000.0 | ||
<< " seconds\n"; | ||
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return (0); | ||
} | ||
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// ----------------------------------------------------------------------------- | ||
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// Local Variables: | ||
// mode:C++ | ||
// tab-width:4 | ||
// c-basic-offset:4 | ||
// End: |
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import datetime | ||
import pandas as pd | ||
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# ------------------------------------------------------------------------------ | ||
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start = datetime.datetime.now() | ||
df = df = pd.read_csv("Large_File.csv") | ||
end = datetime.datetime.now() | ||
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print(f"Column Length: {len(df['COL6:200000000:<int>'])}") | ||
print(f"Reading Took: {(end - start).seconds}.{(end - start).microseconds}") | ||
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# ------------------------------------------------------------------------------ | ||
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# Local Variables: | ||
# mode:Python | ||
# tab-width:4 | ||
# c-basic-offset:4 | ||
# End: | ||
|
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import datetime | ||
import polars as pl | ||
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# ------------------------------------------------------------------------------ | ||
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start = datetime.datetime.now() | ||
df = pl.read_csv("Large_File.csv") | ||
end = datetime.datetime.now() | ||
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print(f"Column Length: {df.select(pl.count()).item()}") | ||
print(f"Reading Took: {(end - start).seconds}.{(end - start).microseconds}") | ||
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# ------------------------------------------------------------------------------ | ||
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# Local Variables: | ||
# mode:Python | ||
# tab-width:4 | ||
# c-basic-offset:4 | ||
# End: |
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