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Query multiple PSE symbols with parallelization #342

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3123504
Merge enzoampil/fastquant to ajdajd/fastquant
ajdajd Oct 25, 2020
e9d96d9
Merge pull request #5 from enzoampil/master
ajdajd Feb 3, 2021
c63ac51
Implement get_pse_data_multiple
ajdajd Feb 4, 2021
d8d0353
Add demo notebook for get_pse_data_multiple
ajdajd Feb 4, 2021
ad65d62
Update example notebook
ajdajd Feb 4, 2021
7adb58d
Add demo notebook
ajdajd Feb 11, 2021
d957f92
Add type checking for symbols
ajdajd Feb 11, 2021
86fb42f
Update demo notebook
ajdajd Feb 11, 2021
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378 changes: 378 additions & 0 deletions examples/get_pse_data_multiple_demo.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"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": "3.8.5"
},
"colab": {
"name": "get_pse_data_multiple_demo.ipynb",
"provenance": [],
"toc_visible": true
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "h-tZ3KhfPQW6"
},
"source": [
"*This notebook was run with Google Colab.*"
]
},
{
"cell_type": "code",
"metadata": {
"id": "FcVD1bJrL_RG"
},
"source": [
"from fastquant import get_pse_data, get_pse_data_multiple\r\n",
"from datetime import datetime"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "obCQra9qL_RL"
},
"source": [
"# Define variables"
]
},
{
"cell_type": "code",
"metadata": {
"id": "vqnwvVoAL_RL"
},
"source": [
"# Define a list of stock symbols\n",
"psei = [\n",
" \"AEV\",\n",
" \"AP\",\n",
" \"AGI\",\n",
" \"AC\",\n",
" \"ALI\",\n",
" \"BPI\",\n",
" \"BDO\",\n",
" \"BLOOM\",\n",
" \"DMC\",\n",
" \"EMP\",\n",
" \"FGEN\",\n",
" \"GLO\",\n",
" \"GTCAP\",\n",
" \"ICT\",\n",
" \"JGS\",\n",
" \"JFC\",\n",
" \"LTG\",\n",
" \"MER\",\n",
" \"MEG\",\n",
" \"MPI\",\n",
" \"MBT\",\n",
" \"TEL\",\n",
" \"PGOLD\",\n",
" \"RLC\",\n",
" \"RRHI\",\n",
" \"SMC\",\n",
" \"SECB\",\n",
" \"SM\",\n",
" \"SMPH\",\n",
" \"URC\",\n",
"]\n",
"\n",
"# Define start and stop dates\n",
"start_date = \"2021-01-01\"\n",
"end_date = datetime.utcnow().strftime(\"%Y-%m-%d\")"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "nqLGsSenL_RM"
},
"source": [
"# Method 1: Without parallelization"
]
},
{
"cell_type": "code",
"metadata": {
"id": "AOLREYbCL_RM",
"outputId": "c27f80a7-2ff2-4bd4-89f9-c5925bb3898b",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"%%time\n",
"\n",
"for symbol in psei:\n",
" get_pse_data(symbol, start_date, end_date)"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"193it [00:24, 7.72it/s]\n",
"193it [00:24, 8.54it/s]\n",
"193it [00:25, 8.02it/s]\n",
"193it [00:26, 8.21it/s]\n",
"193it [00:25, 8.83it/s]\n",
"193it [00:25, 8.30it/s]\n",
"193it [00:24, 8.73it/s]\n",
"193it [00:26, 8.22it/s]\n",
"193it [00:24, 5.93it/s]\n",
"193it [00:25, 6.94it/s]\n",
"193it [00:29, 9.29it/s]\n",
"193it [00:26, 8.26it/s]\n",
"193it [00:26, 8.53it/s]\n",
"193it [00:26, 7.34it/s]\n",
"193it [00:26, 7.40it/s]\n",
"193it [00:26, 6.06it/s]\n",
"193it [00:27, 9.16it/s]\n",
"193it [00:23, 8.38it/s]\n",
"193it [00:24, 9.32it/s]\n",
"193it [00:24, 7.80it/s]\n",
"193it [00:25, 7.72it/s]\n",
"193it [00:31, 6.21it/s]\n",
"193it [00:25, 9.26it/s]\n",
"193it [00:24, 7.66it/s]\n",
"193it [00:25, 6.85it/s]\n",
"193it [00:25, 7.69it/s]\n",
"193it [00:26, 6.93it/s]\n",
"193it [00:23, 9.43it/s]\n",
"193it [00:26, 8.46it/s]\n",
"193it [00:27, 8.13it/s]"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"CPU times: user 49 s, sys: 4.33 s, total: 53.3 s\n",
"Wall time: 13min 14s\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3_nL-bnRL_RN"
},
"source": [
"# Method 2: With parallelization"
]
},
{
"cell_type": "code",
"metadata": {
"id": "WtCjazDsL_RN",
"outputId": "2dfbca92-ec17-411c-a15d-c64ddc5b45a4",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"%%time\n",
"\n",
"data = get_pse_data_multiple(\n",
" psei, n_jobs=-1, start_date=start_date, end_date=end_date\n",
")"
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"[Parallel(n_jobs=-1)]: Using backend LokyBackend with 2 concurrent workers.\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"CPU times: user 110 ms, sys: 44.4 ms, total: 155 ms\n",
"Wall time: 8min 34s\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"[Parallel(n_jobs=-1)]: Done 30 out of 30 | elapsed: 8.6min finished\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "iDkkY5qSL_RO"
},
"source": [
"## Accessing individual stock data"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ciFsQ4J1L_RO",
"outputId": "20f4b574-697a-47c7-af2a-f89322941d3a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 235
}
},
"source": [
"data[\"JFC\"].head()"
],
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>value</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>dt</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-01-04</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>194.4</td>\n",
" <td>NaN</td>\n",
" <td>625440.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-05</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>194.9</td>\n",
" <td>NaN</td>\n",
" <td>513300.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-06</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>194.4</td>\n",
" <td>NaN</td>\n",
" <td>565340.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-07</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>192.6</td>\n",
" <td>NaN</td>\n",
" <td>802590.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-08</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>192.5</td>\n",
" <td>NaN</td>\n",
" <td>720470.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" open high low close value volume\n",
"dt \n",
"2021-01-04 NaN NaN NaN 194.4 NaN 625440.0\n",
"2021-01-05 NaN NaN NaN 194.9 NaN 513300.0\n",
"2021-01-06 NaN NaN NaN 194.4 NaN 565340.0\n",
"2021-01-07 NaN NaN NaN 192.6 NaN 802590.0\n",
"2021-01-08 NaN NaN NaN 192.5 NaN 720470.0"
]
},
"metadata": {
"tags": []
},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "9LT0bBAJPEVN"
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}
1 change: 1 addition & 0 deletions python/fastquant/data/__init__.py
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Expand Up @@ -9,6 +9,7 @@
get_stock_table,
# Combines get_phisix_data and get_pse_data_cache
get_pse_data,
get_pse_data_multiple,
# Gets data from PHISIX
get_phisix_data,
# Gets data from PSE Data Cache
Expand Down
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