mirror of
https://github.com/FlipsideCrypto/sdk.git
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291 lines
9.0 KiB
Plaintext
291 lines
9.0 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Intro to Flipside API/SDK: Getting Started\n",
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"\n",
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"<em>install Flipside with pip</em><br/>\n",
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"`pip install flipside`"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Import the package"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from flipside import Flipside"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Run your first query<br/>\n",
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"<em>Remember to copy/paste your API Key from https://flipsidecrypto.xyz/api-keys below.</em>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"YOUR_API_KEY = os.environ.get(\"FLIPSIDE_API_KEY\")\n",
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"\n",
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"# Invoke the ShroomDK class to create an instance of the SDK\n",
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"sdk = Flipside(YOUR_API_KEY)\n",
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"\n",
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"# Run a query\n",
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"xMETRIC_contract_address = '0x15848C9672e99be386807b9101f83A16EB017bb5'\n",
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"\n",
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"query_result_set = sdk.query(f\"\"\"\n",
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" SELECT count(distinct to_address) as recipient_count\n",
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" FROM polygon.core.fact_token_transfers\n",
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" WHERE block_timestamp > '2022-07-10T00:00:00'\n",
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" AND contract_address = lower('{xMETRIC_contract_address}')\n",
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" AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
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"\"\"\")\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Query Result Set\n",
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"\n",
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"```python\n",
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"class QueryResultSet(BaseModel):\n",
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" query_id: Union[str, None] = Field(None, description=\"The server id of the query\")\n",
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" status: str = Field(False, description=\"The status of the query (`PENDING`, `FINISHED`, `ERROR`)\")\n",
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" columns: Union[List[str], None] = Field(None, description=\"The names of the columns in the result set\")\n",
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" column_types: Union[List[str], None] = Field(None, description=\"The type of the columns in the result set\")\n",
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" rows: Union[List[Any], None] = Field(None, description=\"The results of the query\")\n",
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" run_stats: Union[QueryRunStats, None] = Field(\n",
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" None,\n",
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" description=\"Summary stats on the query run (i.e. the number of rows returned, the elapsed time, etc)\",\n",
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" )\n",
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" records: Union[List[Any], None] = Field(None, description=\"The results of the query transformed as an array of objects\")\n",
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" error: Any\n",
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"\n",
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"```"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"## Explore the result set object\n",
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"\n",
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"records = query_result_set.records\n",
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"\n",
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"print(records[0])\n",
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"\n",
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"print(f\"There are {records[0]['recipient_count']} unique recipients of xMETRIC tokens.\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### xMETRIC Leaderboard\n",
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"Retrieve the balance of every xMETRIC holder"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "sql"
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}
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},
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"outputs": [],
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"source": [
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"WITH sent_tokens AS (\n",
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" SELECT \n",
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" to_address as Participant,\n",
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" sum(raw_amount/pow(10,18)) as xMETRIC\n",
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" FROM polygon.core.fact_token_transfers\n",
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" WHERE\n",
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" block_timestamp::date > '2022-07-10'::date \n",
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" AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
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" AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
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" GROUP BY 1\n",
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"),\n",
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"burnt_tokens AS (\n",
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" SELECT\n",
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" to_address as Participant,\n",
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" sum(raw_amount/pow(10,18)) as xMETRIC\n",
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" FROM polygon.core.fact_token_transfers\n",
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" WHERE\n",
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" block_timestamp::date > '2022-07-10'::date \n",
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" AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
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" AND to_address = lower('0x0000000000000000000000000000000000000000')\n",
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" GROUP BY 1\n",
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")\n",
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"SELECT\n",
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" sent_tokens.Participant as \"participant_addr\",\n",
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" coalesce(sent_tokens.xmetric,0) - coalesce(burnt_tokens.xMETRIC,0) as \"balance\"\n",
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"FROM sent_tokens \n",
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"LEFT JOIN burnt_tokens ON sent_tokens.Participant = burnt_tokens.Participant\n",
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"ORDER BY 2 DESC"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load the sql query from a file\n",
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"leaderboard_sql_query = open(\"./sql/xmetric_leaderboard.sql\", 'r').read()\n",
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"\n",
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"# Run the query with pagination\n",
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"\n",
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"page_number = 1\n",
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"page_size = 10\n",
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"\n",
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"leaderboard_result_set = sdk.query(\n",
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" leaderboard_sql_query, \n",
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" page_size=page_size,\n",
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" page_number=page_number)\n",
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"\n",
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"for record in leaderboard_result_set.records:\n",
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" print(record)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Plot the xMETRIC LeaderBoard Results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"full_leaderboard_result_set = sdk.query(leaderboard_sql_query)\n",
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"\n",
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"import pandas as pd\n",
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"import plotly.express as px\n",
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"\n",
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"df = pd.DataFrame(full_leaderboard_result_set.records)\n",
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"\n",
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"fig = px.histogram(df, x=\"balance\", marginal=\"box\", hover_data=df.columns, nbins=200)\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Cross Chain xMETRIC User Exploration"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "sql"
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}
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},
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"outputs": [],
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"source": [
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"WITH xmetric_holders AS (\n",
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" SELECT to_address as holder_addr\n",
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" FROM polygon.core.fact_token_transfers\n",
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" WHERE block_timestamp > '2022-07-10T00:00:00'\n",
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" AND contract_address = lower('0x15848C9672e99be386807b9101f83A16EB017bb5')\n",
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" AND to_address != lower('0x4b8923746a1D9943bbd408F477572762801efE4d')\n",
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")\n",
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"SELECT\n",
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" token_name,\n",
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" symbol,\n",
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" count(distinct user_address) as num_holders,\n",
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" median(usd_value_now) as median_usd_holdings\n",
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"FROM ethereum.core.ez_current_balances\n",
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"INNER JOIN xmetric_holders \n",
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" ON ethereum.core.ez_current_balances.user_address = xmetric_holders.holder_addr\n",
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"WHERE ethereum.core.ez_current_balances.usd_value_now > 0\n",
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"GROUP BY 1, 2\n",
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"ORDER BY 3 DESC\n",
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"LIMIT 25"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load the sql query from a file\n",
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"xmetric_eth_holdings_sql_query = open(\"./sql/xmetric_eth_holdings.sql\", 'r').read()\n",
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"\n",
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"# Run the query\n",
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"xmetric_eth_holdings_results = sdk.query(xmetric_eth_holdings_sql_query)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Plot the results\n",
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"df = pd.DataFrame(xmetric_eth_holdings_results.records)\n",
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"\n",
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"fig = px.bar(df, x=\"token_name\", y=\"num_holders\", hover_data=df.columns)\n",
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"\n",
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"fig.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.10.1 64-bit",
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"language": "python",
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"codemirror_mode": {
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"name": "ipython",
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"file_extension": ".py",
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"nbconvert_exporter": "python",
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