From 1a50f7e6def174c2ba8ad804ac0c31ebd62e9271 Mon Sep 17 00:00:00 2001 From: flashlan Date: Wed, 21 Jun 2023 23:44:22 -0300 Subject: [PATCH] init Kdb+ Functions --- compareDBs.ipynb | 98 ++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 95 insertions(+), 3 deletions(-) diff --git a/compareDBs.ipynb b/compareDBs.ipynb index 6a00a33..6d2d5a0 100644 --- a/compareDBs.ipynb +++ b/compareDBs.ipynb @@ -80,9 +80,9 @@ "from influxdb_client import InfluxDBClient\n", "from influxdb_client.client.write_api import SYNCHRONOUS\n", "from minio import Minio\n", - "from monary import Monary\n", "from pymongo import MongoClient\n", "from pytz import timezone\n", + "from qpython import qconnection\n", "from sqlalchemy import create_engine\n", "\n", "load_dotenv()" @@ -1368,6 +1368,7 @@ "cell_type": "markdown", "id": "50d1fc58-89a7-4507-aff0-6e943656cfe0", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ @@ -1506,6 +1507,7 @@ "cell_type": "markdown", "id": "97405e42-61dc-42c7-8220-237a312c0ec7", "metadata": { + "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ @@ -1755,8 +1757,98 @@ "metadata": {}, "outputs": [], "source": [ - "np.bool = np.bool_\n", - "from qpython import qconnection" + "# numpy version boolean fix\n", + "np.bool = np.bool_" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bbd217e3-695f-4fa6-ae42-83db1dde8311", + "metadata": {}, + "outputs": [], + "source": [ + "# functions\n", + "\n", + "\n", + "def kdbConnect():\n", + " q = qconnection.QConnection(host=\"localhost\", port=5001)\n", + " q.open()\n", + " return q\n", + "\n", + "\n", + "def kdbLoadCsv(file=\"out.csv\"):\n", + " data = pd.read_csv(file)\n", + " return data\n", + "\n", + "\n", + "def kdbWrite():\n", + " q = kdbConnect()\n", + " data = kdbLoadCsv()\n", + " q.sendSync(\"{t::x}\", data)\n", + " q.sendSync(\"`:/home/sandman/q/tab1 set t\")\n", + " q.close()\n", + " return 0\n", + "\n", + "\n", + "def kdbRead():\n", + " q = kdbConnect()\n", + " df2 = q.sendSync(\"tab2: get `:/home/sandman/q/tab1\")\n", + " df2 = q.sendSync(\"tab2\")\n", + " df = pd.DataFrame(q(\"t\")) # , pandas=True))\n", + " df3 = q.sendSync(\"select from t\")\n", + " # ver todos esses loads\n", + " q.close()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dc239236-bb47-4bcb-8e50-ac900852cd47", + "metadata": {}, + "outputs": [], + "source": [ + "# load" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "67f0c26e-44fb-40b0-a147-5d97bfbbded2", + "metadata": {}, + "outputs": [], + "source": [ + "# write" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dcb200be-ffc9-4bcc-8554-5740fb420ab5", + "metadata": {}, + "outputs": [], + "source": [ + "# print write time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d4ce0203-b0c7-440b-a3ca-d7b2a7682474", + "metadata": {}, + "outputs": [], + "source": [ + "# read" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1a16fd76-2158-40fe-9285-c53791f8ed51", + "metadata": {}, + "outputs": [], + "source": [ + "# print read time" ] }, {