added examples

examples/example_iris.ipynb

@@ -0,0 +1,190 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Hack to make the module importable\n",
+    "import sys\n",
+    "sys.path.append(r'./../')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "import neo4j\n",
+    "import pandas as pd\n",
+    "\n",
+    "from rel2graph.relational_modules.pandas import PandasDataFrameIterator\n",
+    "from rel2graph import IteratorIterator\n",
+    "from rel2graph import Converter\n",
+    "from rel2graph.utils import load_file\n",
+    "from rel2graph import register_attribute_postprocessor, Attribute\n",
+    "\n",
+    "import rel2graph.common_modules.types # For FLOAT, INT, etc. wrappers\n",
+    "# This is required because the pandas dataframe iterator will convert all values \n",
+    "# to int64 which is not supported by neo4j"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Configure Logging\n",
+    "import logging\n",
+    "\n",
+    "#logging.basicConfig(level=logging.WARNING)\n",
+    "logger = logging.getLogger(\"rel2graph\")\n",
+    "logger.setLevel(logging.INFO)\n",
+    "log_formatter = logging.Formatter(\"%(asctime)s [%(threadName)s]::[%(levelname)s]::%(filename)s: %(message)s\")\n",
+    "console_handler = logging.StreamHandler()\n",
+    "console_handler.setFormatter(log_formatter)\n",
+    "logger.addHandler(console_handler)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')\n",
+    "iris"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = {\n",
+    "  \"ID\": [1,2,2,3,4,4],\n",
+    "  \"FirstName\": [\"Julian\", \"Fritz\",  \"Fritz\", \"Hans\", \"Rudolfo\", \"Rudolfo\"],\n",
+    "  \"LastName\": [\"Minder\", \"Generic\", \"SomeGuy\", \"Müller\", \"Muster\", \"Muster\"],\n",
+    "  \"FavoriteFlower\": [\"virginica\", \"setosa\", \"setosa\", \"versicolor\", \"setosa\", \"setosa\"]\n",
+    "}\n",
+    "people = pd.DataFrame(data)\n",
+    "people"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "schema = \"\"\"\n",
+    "ENTITY(\"Flower\"):\n",
+    "    NODE(\"Flower\") flower:\n",
+    "        - sepal_length = FLOAT(Flower.sepal_length)\n",
+    "        - petal_length = FLOAT(Flower.petal_width)\n",
+    "        - sepal_width = FLOAT(Flower.sepal_width)\n",
+    "        - petal_width = FLOAT(Flower.petal_width)\n",
+    "    NODE(\"Species\", \"BioEntity\") species:\n",
+    "        + Name = Flower.species\n",
+    "    RELATIONSHIP(flower, \"is\", species):\n",
+    "    \n",
+    "ENTITY(\"Person\"):\n",
+    "    NODE(\"Person\") person:\n",
+    "        + ID = INT(Person.ID)\n",
+    "        - FirstName = Person.FirstName\n",
+    "        - LastName = Person.LastName\n",
+    "\n",
+    "    RELATIONSHIP(person, \"likes\", MATCH(\"Species\", Name=Person.FavoriteFlower)):\n",
+    "        - Since = \"4ever\"\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "uri = \"bolt://localhost:7687\"\n",
+    "auth = neo4j.basic_auth(\"neo4j\", \"password\") # CHANGE TO YOUR CREDENTIALS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Delete all nodes and relationships\n",
+    "driver = neo4j.GraphDatabase().driver(uri, auth=auth)\n",
+    "with driver.session() as session:\n",
+    "    session.run(\"MATCH (n) DETACH DELETE n\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iterator = IteratorIterator([PandasDataFrameIterator(people, \"Person\"), PandasDataFrameIterator(iris, \"Flower\")])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter = Converter(schema, iterator, uri, auth, num_workers=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from tqdm.notebook import tqdm\n",
+    "converter(progress_bar=tqdm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "b412206d49013109e888184d145344cd80b977ea9059b5a051a9ff53a4d07d7f"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}