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This commit is contained in:
Kellen Blumberg 2023-02-07 12:14:58 -08:00
commit 15c01854ef
45 changed files with 3469 additions and 10510 deletions
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1
.gitignore vendored
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@ -7,3 +7,4 @@
*.txt
secrets.json
*.dcf
.dcf

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apps/flow/.gitignore vendored Normal file
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.DS_Store

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apps/flow/flowscored/.gitignore vendored Normal file
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.DS_Store

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apps/optimism/optimistic_score_prototype/data.RData
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apps/optimism/optimistic_score_prototype/rsconnect/science.flipsidecrypto.xyz/angela/.gitignore vendored Normal file
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optimistic_score_prototype.dcf

11
apps/optimism/optimistic_score_prototype/server.R
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@ -20,6 +20,11 @@ function(input, output, session) {
updateActionButton(session = session, inputId = "connect",
label = paste0("connected as ", substr(input$eth_address, 1, 7), "..."),
icon = character(0))
tmp <- data.table(address = input$eth_address,
time = Sys.time(),
score = userScore())
write.csv(tmp, file = paste0("/rstudio-data/optimistic-data/", input$eth_address, "_", Sys.time(), ".csv"), row.names = FALSE)
} else {
updateActionButton(session = session, inputId = "connect",
@ -119,6 +124,7 @@ function(input, output, session) {
})
userScore <- reactive({
if(nrow(thisAddyData()) > 0) {
thisAddyData()$total_score
@ -127,10 +133,13 @@ function(input, output, session) {
}
})
output$tx_handler <- renderUI({
TransactionHandler(
"tx_button",
chainId = 420,
chainId = 10,
label = "Attest Your Score On Chain",
contract_address = "0xD870A73a32d0b8C34CcF1E6098E9A26977CB605b",
contract_abi = abi,

32
apps/optimism/optimistic_score_prototype/ui.R
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@ -3,22 +3,28 @@ fluidPage(
tags$link(rel = "stylesheet", type = "text/css", href = "shiny.css"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Roboto+Mono"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Open+Sans"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Rubik")
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Rubik"),
tags$script(src = "rudderstack.js")
),
# background: linear-gradient(90deg, rgba(255,196,202,0.19511554621848737) 0%, rgba(255,255,255,0) 100%); color: #919EAB;
fluidRow(class = "titlebar",
column(9, img(src = "app_logo.svg", height = "44px", style = "margin-left: 13px; margin-top: 13px; margin-bottom: 13px;")),
column(3, style = "text-align: right;", actionButton("connect", icon = icon("wallet"), label = " Connect Wallet")),
bsModal(id = "connectpop", title = "", trigger = "connect",
WalletHandler("eth_address", chainId = 420))
WalletHandler("eth_address", chainId = 10),
br(),
a("How to connect MetaMask to Optimism",
href = "https://help.optimism.io/hc/en-us/articles/6223777057179-How-do-I-use-Optimism-with-MetaMask-",
target = "_blank", style = "font-style: italic;"))
),
fluidRow(class = "wrapper",
fluidRow(class = "scoreholder",
fluidRow(class = "description", div("Score up to 5 points by doing things that contribute to the Optimism Network. Then click 'Attest Your Score On Chain' to use the ",
a("AttestationStation", href = "https://community.optimism.io/docs/governance/attestation-station/", target = "_blank"),
a("AttestationStation",
href = "https://community.optimism.io/docs/governance/attestation-station/",
onclick = "rudderstack.track('optimist-click-attestation-station')",
target = "_blank"),
" to get your score onchain.")),
br(),
fluidRow(class = "scorebox",
@ -61,15 +67,23 @@ fluidPage(
div(class = "LINKS", "FAQ:"),
div(class = "links",
a(href = "https://community.optimism.io/docs/governance/attestation-station/",
"What is Attestation Station?", target = "_blank")),
"What is Attestation Station?",
onclick = "rudderstack.track('optimist-click-attestation-station')",
target = "_blank")),
div(class = "links",
a(href = "https://github.com/FlipsideCrypto/user_metrics/tree/main/apps/optimism/optimistic_score_prototype",
"Can I have this code?", target = "_blank")),
"Can I have this code?",
onclick = "rudderstack.track('optimist-click-github')",
target = "_blank")),
div(class = "links",
a(href = "https://app.flipsidecrypto.com/dashboard/optimist-score-queries-data-Jp7kIN",
"Can I have this data?", target = "_blank")),
"Can I have this data?",
onclick = "rudderstack.track('optimist-click-velocity')",
target = "_blank")),
div(class = "links",
a(href = "https://flipsidecrypto.xyz/", "What is Flipside?", target = "_blank"))
a(href = "https://flipsidecrypto.xyz/", "What is Flipside?",
onclick = "rudderstack.track('optimist-click-flipsidexyz')",
target = "_blank"))
)

2
apps/optimism/optimistic_score_prototype/update_data.R
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@ -38,7 +38,7 @@ op.metrics.w[, delegation_score := ifelse(n_delegations > 0, 1, 0)]
op.metrics.w[, nft_score := ifelse(n_trades > 0, 1, 0)]
op.metrics.w[, dex_score := ifelse(n_swaps > 0, 1, 0)]
op.metrics.w[, total_score := airdrop_score + cex_score + delegation_score + nft_score + dex_score]
op.metrics.w[, total_score := airdrop_score + 1 + delegation_score + nft_score + dex_score]
op.metrics.w <- op.metrics.w[total_score > 0]

267
apps/optimism/optimistic_score_prototype/update_data_optimist_score_prototoype.Rmd Normal file
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@ -0,0 +1,267 @@
---
title: "Update Optimist Score Prototype Data"
author: "Angeal"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Run Updates
Hello I am running this at `r Sys.time()`
```{r update}
library(fasttime)
library(gridExtra)
library(ggplot2)
library(data.table)
library(reshape2)
library(dplyr)
library(dbplyr)
library(dplyr)
library(odbc)
library(RJSONIO)
library(magrittr)
library(RJSONIO)
library(xts)
library(quantmod)
library(fTrading)
library(curl)
library(stringr)
library(aws.s3)
library(RPostgres)
source("/home/data-science/data_science/util/util_functions.R")
airdrop.claims <- QuerySnowflake("
SELECT
event_inputs:recipient::string as user_address,
count(distinct(tx_hash)) AS n_claims,
sum(event_inputs:amount::numeric / pow(10,18)) as token_volume
from optimism.core.fact_event_logs
WHERE
block_timestamp > '2022-05-30'
AND
origin_function_signature = '0x2e7ba6ef' -- claim
AND
contract_address = lower('0xFeDFAF1A10335448b7FA0268F56D2B44DBD357de') -- distr contract
AND
user_address NOT IN (
SELECT address
FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS
WHERE blockchain = 'optimism')
GROUP BY user_address
")
cex.activity <- QuerySnowflake("
WITH wdraws AS (SELECT
to_address AS user_address,
tt.contract_address AS token_contract,
symbol AS token_symbol,
count(tt.tx_hash) AS n_withdrawals,
sum(raw_amount) / pow(10, decimals) AS wdraw_token_volume,
sum(raw_amount) / pow(10, decimals) * price AS wdraw_usd_volume
FROM
optimism.core.fact_token_transfers tt
JOIN optimism.core.FACT_HOURLY_TOKEN_PRICES pp
ON date_trunc('hour', tt.block_timestamp) = pp.hour
AND tt.contract_address = pp.token_address
WHERE
from_address IN
(SELECT address
FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS
WHERE blockchain = 'optimism' AND label_type = 'cex' AND label_subtype = 'hot_wallet')
AND
to_address NOT IN (
SELECT address
FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS
WHERE blockchain != 'optimism')
GROUP BY user_address, token_contract, token_symbol, decimals, price),
deps AS (
SELECT
from_address AS user_address,
tt.contract_address AS token_contract,
symbol AS token_symbol,
count(tt.tx_hash) AS n_deposits,
sum(raw_amount) / pow(10, decimals) AS dep_token_volume,
sum(raw_amount) / pow(10, decimals) * price AS dep_usd_volume
FROM
optimism.core.fact_token_transfers tt
JOIN optimism.core.FACT_HOURLY_TOKEN_PRICES pp
ON date_trunc('hour', tt.block_timestamp) = pp.hour
AND tt.contract_address = pp.token_address
WHERE
to_address IN
(SELECT address
FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS
WHERE blockchain = 'optimism' AND label_type = 'cex' AND label_subtype = 'deposit_wallet')
AND
from_address NOT IN (
SELECT address
FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS
WHERE blockchain != 'optimism')
GROUP BY user_address, token_contract, token_symbol, decimals, price
)
SELECT
COALESCE(ds.user_address, ws.user_address) AS user_address,
'tbd' AS exchange_name,
COALESCE(ds.token_contract, ws.token_contract) AS token_contract,
SPLIT_PART(COALESCE(ds.token_contract, ws.token_contract), '.', 2) AS token_symbol,
COALESCE(n_deposits, 0) AS n_deposits,
COALESCE(n_withdrawals, 0) AS n_withdrawals,
COALESCE(dep_token_volume, 0) AS dep_token_volume,
COALESCE(dep_usd_volume, 0) AS dep_usd_volume,
COALESCE(wdraw_token_volume, 0) AS wdraw_token_volume,
COALESCE(wdraw_usd_volume, 0) AS wdraw_usd_volume
FROM deps ds
FULL OUTER JOIN wdraws ws ON ds.user_address = ws.user_address
AND ds.token_contract = ws.token_contract
")
chain.stakes <- QuerySnowflake("
WITH format_delegations AS (
select
*,
(raw_new_balance - raw_previous_balance) / pow(10, 18) AS net_delegation
FROM optimism.core.fact_delegations
WHERE
delegation_type != 'Re-Delegation'
)
SELECT
delegator AS user_address,
'0x4200000000000000000000000000000000000042' AS token_contract,
'OP' AS token_symbol,
count(distinct(tx_hash)) AS n_stakes,
0 AS n_unstakes,
sum(net_delegation) AS stake_token_volume,
0 AS stake_usd_volume,
0 AS unstake_token_volume,
0 AS unstake_usd_volume
FROM format_delegations
WHERE
delegator NOT IN (SELECT address FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS where blockchain = 'optimism')
GROUP BY
delegator
")
nft.trades <- QuerySnowflake("
WITH sells AS (
SELECT
seller_address AS user_address,
platform_name AS marketplace,
nft_address AS nf_token_contract,
count(distinct(tokenid)) AS n_nfts_sold,
currency_symbol AS sell_symbol,
currency_address AS currency,
count(tx_hash) AS n_sells,
sum(price) AS token_sell_volume,
sum(price_usd) AS sell_usd_volume
FROM
optimism.core.ez_nft_sales ns
WHERE
user_address NOT IN (SELECT address FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS where blockchain = 'optimism')
GROUP BY
seller_address, marketplace, nf_token_contract, sell_symbol, currency
),
buys AS (
SELECT
buyer_address AS user_address,
platform_name AS marketplace,
nft_address AS nf_token_contract,
count(distinct(tokenid)) AS n_nfts_bought,
currency_symbol AS buy_symbol,
currency_address AS currency,
count(tx_hash) AS n_buys,
sum(price) AS token_buy_volume,
sum(price_usd) AS buy_usd_volume
FROM
optimism.core.ez_nft_sales ns
WHERE
user_address NOT IN (SELECT address FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS where blockchain = 'optimism')
GROUP BY
buyer_address, marketplace, nf_token_contract, buy_symbol, currency
)
SELECT
COALESCE(sells.user_address, buys.user_address) AS user_address,
COALESCE(sells.marketplace, buys.marketplace) AS marketplace,
COALESCE(sells.nf_token_contract, buys.nf_token_contract) AS nf_token_contract,
COALESCE(buys.n_nfts_bought, 0) AS n_nfts_bought,
COALESCE(sells.n_nfts_sold, 0) AS n_nfts_sold,
SPLIT_PART(COALESCE(sells.nf_token_contract, buys.nf_token_contract), '.', 2) AS nft_project,
COALESCE(sells.currency, buys.currency) AS token_contract,
COALESCE(sells.sell_symbol, buys.buy_symbol) AS token_symbol,
COALESCE(n_buys, 0) AS n_buys,
COALESCE(token_buy_volume, 0) AS buy_token_volume,
COALESCE(buy_usd_volume, 0) AS buy_usd_volume,
COALESCE(n_sells, 0) AS n_sells,
COALESCE(token_sell_volume, 0) AS sell_token_volume,
COALESCE(sell_usd_volume, 0) AS sell_usd_volume
FROM sells
FULL OUTER JOIN buys ON sells.user_address = buys.user_address
AND sells.marketplace = buys.marketplace
AND sells.nf_token_contract = buys.nf_token_contract
AND sells.currency = buys.currency
")
dex.swaps <- QuerySnowflake("
WITH swaps AS (
SELECT
tx_hash,
ORIGIN_FROM_ADDRESS AS user_address
FROM
OPTIMISM.CORE.FACT_EVENT_LOGS
WHERE
(lower(event_name) LIKE '%swap%'
OR
tx_hash IN (select tx_hash FROM OPTIMISM.VELODROME.EZ_SWAPS WHERE block_timestamp > current_date - 180) )
AND
ORIGIN_FROM_ADDRESS NOT IN (SELECT address FROM FLIPSIDE_PROD_DB.CROSSCHAIN.ADDRESS_LABELS where blockchain = 'optimism')
)
SELECT
user_address,
count(distinct(tx_hash)) AS n_swaps
FROM
swaps
GROUP BY
user_address
")
op.metrics.w <- MergeDataFrames(
list(airdrop.claims[, list(user_address, airdrop_tokens_claimed = token_volume)],
cex.activity[, list(net_cex_wdraw = sum(wdraw_usd_volume) - sum(dep_usd_volume)), by = user_address],
chain.stakes[, list(user_address, n_delegations = n_stakes)],
nft.trades[, list(n_trades = sum(n_buys + n_sells)), by = user_address],
dex.swaps),
by = "user_address", all = TRUE
)
ReplaceValues(op.metrics.w)
op.metrics.w[, airdrop_score := ifelse(airdrop_tokens_claimed > 0, 1, 0)]
op.metrics.w[, cex_score := ifelse(net_cex_wdraw >= 0, 1, 0)]
op.metrics.w[, delegation_score := ifelse(n_delegations > 0, 1, 0)]
op.metrics.w[, nft_score := ifelse(n_trades > 0, 1, 0)]
op.metrics.w[, dex_score := ifelse(n_swaps > 0, 1, 0)]
op.metrics.w[, total_score := airdrop_score + 1 + delegation_score + nft_score + dex_score]
op.metrics.w <- op.metrics.w[total_score > 0]
save(op.metrics.w, file = "/rstudio-data/optimist_score_prototype_data.RData")
print(file.info("/rstudio-data/optimist_score_prototype_data.RData"))
```
Done updating at `r Sys.time()`
The end. Byeeeee.

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apps/optimism/optimistic_score_prototype/www/rudderstack.js Normal file
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@ -0,0 +1,3 @@
!function(){var e=window.rudderanalytics=window.rudderanalytics||[];e.methods=["load","page","track","identify","alias","group","ready","reset","getAnonymousId","setAnonymousId"],e.factory=function(t){return function(){var r=Array.prototype.slice.call(arguments);return r.unshift(t),e.push(r),e}};for(var t=0;t<e.methods.length;t++){var r=e.methods[t];e[r]=e.factory(r)}e.loadJS=function(e,t){var r=document.createElement("script");r.type="text/javascript",r.async=!0,r.src="https://cdn.rudderlabs.com/v1.1/rudder-analytics.min.js";var a=document.getElementsByTagName("script")[0];a.parentNode.insertBefore(r,a)},e.loadJS(),
e.load('29a6Pl6fLlx4iYiOdfxRt0IBad9','https://flipsidecrworumuyiulf.dataplane.rudderstack.com'),
e.page()}();

54
apps/optimism/optimistic_score_prototype/www/shiny.css
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@ -1,5 +1,5 @@
body {
background: white;
background: url('Background_03.png');
font-family: 'Open Sans', sans-serif;
font-size: 16px;
font-weight: 400;
@ -7,7 +7,11 @@ body {
}
a, a:hover, a:visited, a:active {
color: red;
color: #F60001;
}
a:hover {
color: #F6000195;
}
.container-fluid {
@ -34,10 +38,18 @@ a, a:hover, a:visited, a:active {
color: #F60001;
font-size: 1.02em;
padding: 8px;
background: linear-gradient(white, white) padding-box,
linear-gradient(to right, #F60001, #F60001) border-box;
border-radius: 4px;
border: 3px solid transparent;
border: 3px solid #F60001;
}
#connect:hover {
background-color: #F60001;
color: white;
}
#connect:visited {
background-color: transparent;
color: #F60001;
}
.walletpart {
@ -63,9 +75,9 @@ a, a:hover, a:visited, a:active {
line-height: 50px;
width: 20%;
background-color: white;
border: 2px red solid;
border: 2px #F60001 solid;
border-radius: 4px 0 0 4px;
color: red;
color: #F60001;
text-align: center;
font-family: Rubik;
font-weight: 600;
@ -77,9 +89,9 @@ a, a:hover, a:visited, a:active {
height: 50px;
line-height: 50px;
width: 80%;
background-color: red;
background-color: #F60001;
border-radius: 0 4px 4px 0;
border: 2px red solid;
border: 2px #F60001 solid;
color: white;
text-align: left;
padding-left: 10px;
@ -87,7 +99,7 @@ a, a:hover, a:visited, a:active {
.scoreholder {
border: 2px solid red;
border: 2px solid #F60001;
border-radius: 17px;
padding: 10px 30px 0 37px;
max-width: 630px;
@ -120,7 +132,7 @@ a, a:hover, a:visited, a:active {
}
.scorecircle {
background-color: red;
background-color: #F60001;
color: white;
font-family: Rubik;
font-size: 4em;
@ -138,9 +150,9 @@ a, a:hover, a:visited, a:active {
}
button {
border: 1px red solid;
border: 1px #F60001 solid;
padding: 5px;
color: red;
color: #F60001;
background-color: white;
margin: 10px;
border-radius: 4px;
@ -158,6 +170,8 @@ button {
border: 3px solid transparent;
}
.scorecolumns {
padding-left: 30px;
padding-right: 30px;
@ -179,7 +193,7 @@ button {
border: 1px solid #F60001;
}
.modal-title {
color: red;
color: #F60001;
font-weight: bold;
border: none;
}
@ -194,9 +208,19 @@ button {
.links {
color: red;
color: #F60001;
font-size: 0.95em;
text-align: center;
}
#tx_button > button:disabled {
background-color: #F6000197;
cursor: not-allowed;
}
#tx_button > button:hover:enabled {
background-color: #CF0018
}

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apps/solana/solarscored/.gitignore vendored Normal file
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solarscored_data.RData

69
apps/solana/solarscored/edit_svg.R Normal file
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@ -0,0 +1,69 @@
library(stringr)
setwd("~/user_metrics/apps/solana/solarscored")
# read in the svg text
svg.text <- readLines("wheelpart.svg")
# split into parts on the layer opening tag
split.at.1 <- "Layer_"
sgv.text.split <- strsplit(svg.text, split = split.at.1, fixed = TRUE)[[1]]
# grab the layer with the slices
# you have to know which one it is
# we're looking for layer 1
center.slices <- sgv.text.split[which(substr(sgv.text.split, 1, 1) == "1")]
center.slices <- '<g id="Layer_1"><path class="cls-7" d="M421.63,216.81c51.13,0,99.47,23.28,131.35,63.25l-47.29,37.71c-20.4-25.58-51.34-40.48-84.06-40.48v-60.48Z"/><path class="cls-9" d="M552.98,280.07c31.88,39.97,43.82,92.29,32.44,142.13l-58.96-13.46c7.28-31.9-.36-65.38-20.76-90.96l47.29-37.71Z"/><path class="cls-17" d="M585.42,422.19c-11.38,49.84-44.83,91.8-90.9,113.98l-26.24-54.49c29.48-14.2,50.89-41.05,58.17-72.95l58.96,13.46Z"/><path class="cls-5" d="M494.52,536.17c-46.06,22.18-99.72,22.18-145.78,0l26.24-54.49c29.48,14.2,63.82,14.2,93.3,0l26.24,54.49Z"/><path class="cls-11" d="M348.74,536.17c-46.06-22.18-79.52-64.13-90.9-113.98l58.96-13.46c7.28,31.9,28.69,58.75,58.17,72.95l-26.24,54.49Z"/><path class="cls-13" d="M257.84,422.19c-11.38-49.84,.56-102.16,32.44-142.13l47.29,37.71c-20.4,25.58-28.04,59.06-20.76,90.96l-58.96,13.46Z"/><path class="cls-15" d="M290.28,280.07c31.88-39.97,80.22-63.25,131.35-63.25v60.48c-32.72,0-63.66,14.9-84.06,40.48l-47.29-37.71Z"/><path class="cls-7" d="M421.63,156.33c69.53,0,135.28,31.66,178.63,86.03l-47.29,37.71c-31.88-39.97-80.22-63.25-131.35-63.25v-60.48Z"/><path class="cls-9" d="M600.27,242.36c43.35,54.36,59.59,125.51,44.12,193.3l-58.96-13.46c11.38-49.84-.56-102.16-32.44-142.13l47.29-37.71Z"/><path class="cls-17" d="M644.38,435.65c-15.47,67.79-60.97,124.84-123.62,155.01l-26.24-54.49c46.06-22.18,79.52-64.13,90.9-113.98l58.96,13.46Z"/><path class="cls-5" d="M520.77,590.66c-62.65,30.17-135.62,30.17-198.27,0l26.24-54.49c46.06,22.18,99.72,22.18,145.78,0l26.24,54.49Z"/><path class="cls-11" d="M322.5,590.66c-62.65-30.17-108.15-87.22-123.62-155.01l58.96-13.46c11.38,49.84,44.83,91.8,90.9,113.98l-26.24,54.49Z"/><path class="cls-13" d="M198.88,435.65c-15.47-67.79,.77-138.93,44.12-193.3l47.29,37.71c-31.88,39.97-43.82,92.29-32.44,142.13l-58.96,13.46Z"/><path class="cls-15" d="M243,242.36c43.35-54.36,109.1-86.03,178.63-86.03v60.48c-51.13,0-99.47,23.28-131.35,63.25l-47.29-37.71Z"/><path class="cls-7" d="M421.63,95.85c87.94,0,171.09,40.04,225.92,108.8l-47.29,37.71c-43.35-54.36-109.1-86.03-178.63-86.03v-60.48Z"/><path class="cls-9" d="M647.55,204.65c54.83,68.75,75.37,158.73,55.8,244.46l-58.96-13.46c15.47-67.79-.77-138.93-44.12-193.3l47.29-37.71Z"/><path class="cls-17" d="M703.35,449.11c-19.57,85.73-77.11,157.89-156.34,196.04l-26.24-54.49c62.65-30.17,108.15-87.22,123.62-155.01l58.96,13.46Z"/><path class="cls-5" d="M547.01,645.16c-79.23,38.15-171.52,38.15-250.75,0l26.24-54.49c62.65,30.17,135.62,30.17,198.27,0l26.24,54.49Z"/><path class="cls-11" d="M296.26,645.16c-79.23-38.15-136.77-110.31-156.34-196.04l58.96-13.46c15.47,67.79,60.97,124.84,123.62,155.01l-26.24,54.49Z"/><path class="cls-13" d="M139.92,449.11c-19.57-85.73,.97-175.71,55.8-244.46l47.29,37.71c-43.35,54.36-59.59,125.51-44.12,193.3l-58.96,13.46Z"/><path class="cls-15" d="M195.71,204.65c54.83-68.75,137.98-108.8,225.92-108.8v60.48c-69.53,0-135.28,31.66-178.63,86.03l-47.29-37.71Z"/></g>'
split.at.2 <- "path"
block.orders <- c("nfts", "governance", "variety", "staking", "longevity", "bridging", "activity")
wheel.colors <- c("#30CFCF", "#A682EE", "#23D1BA", "#9764E8", "#3EAFE0", "#8880E5", "#26D994")
editing <- str_split(center.slices, "path")[[1]]
intro.bit <- editing[1]
editing <- editing[2:22]
# insert class name to each slice shape
edited <- sapply(1:21, function(i) {
#class name:
cat.name <- block.orders[ifelse(i %% 7 == 0, 7, i %% 7)]
class.name <- paste0(cat.name, ceiling((i)/7))
str_replace( editing[i], "cls-(.*?) ", paste0(class.name, "\" "))
})
edited.slices <- paste(c(intro.bit, edited), collapse = split.at.2)
# add this to the top section with the css
new.header <- str_replace(string = sgv.text.split[1],
pattern = "<style>.",
replacement = paste0("<style>",
paste(".", paste0(rep(block.orders, each = 3), 1:3), "{fill:",
rep(wheel.colors, each = 3),
";opacity:%s;}", sep = "", collapse = ""),
".")
)
edited.svg <- paste(c(new.header,
sgv.text.split[which(substr(sgv.text.split, 1, 1) == "3")],
edited.slices,
sgv.text.split[which(substr(sgv.text.split, 1, 1) == "2")],
sgv.text.split[which(substr(sgv.text.split, 1, 1) == "5")]),
collapse = split.at.1)
writeLines(edited.svg, con = "wheel.svg")
# 1 slices
# 2 text
# 3 border
# 5 icon
substr(sgv.text.split, 1, 1)

145
apps/solana/solarscored/global.R
View File

@ -1,144 +1,41 @@
# lunatics
setwd('/Users/kellen/git/user_metrics/apps/solana/solarscored')
library(shiny)
library(data.table)
library(stringr)
library(shinyWidgets)
library(reactable)
library(plotly)
library(shinyjs)
library(capture)
library(shinyBS)
library(dplyr)
library(solAttestR)
# library(terraConnectr)
library(shinycssloaders)
#install.packages("~/user_metrics/apps/solana/solAttestR_0.0.0.9000.tar.gz", repos = NULL, type="source")
#install.packages("~/user_metrics/apps/optimism/opAttestR_0.0.0.9000.tar.gz", repos = NULL, type="source")
wheel.colors <- c("#30CFCF", "#A682EE", "#23D1BA", "#9764E8", "#3EAFE0", "#8880E5", "#26D994")
svgdata <- readLines("wheel.svg")
#not used:
#library(stringr)
#library(showtext)
#library(htmltools)
rating.max <- 420
#load("data.RData")
file.location <- ifelse(Sys.info()[["user"]] == "rstudio-connect",
"/rstudio-data/solarscored_data.RData",
"solarscored_data.RData")
user <- Sys.info()[['user']]
isRstudio <- user == 'rstudio-connect'
baseDir <- ifelse(isRstudio, '/rstudio-data/solarscored_data.RData', './')
file.location <- paste0(baseDir, 'solarscored_data.RData')
load(file.location)
# print(exists("score.criteria"))
score_criteria <- read.csv('./score_criteria.csv') %>% as.data.table()
score_criteria <- read.csv(
paste0(baseDir, 'score_criteria.csv')
) %>% as.data.table()
bar.plot.colors <- c("#14F195", "#B2FBDC")
round_any <- function(x, accuracy, f=round){f(x/ accuracy) * accuracy}
# setnames(df2, c("user_address", "longevity", "activity", "governor", "bridgor", "staker", "explorer", "nfts",
# "longevity1", "longevity2", "longevity3", "activity1", "activity2", "activity3", "governance1", "governance2", "governance3",
# "bridging1", "bridging2", "bridging3", "staking1", "staking2", "staking3",
# "diversification1", "diversification2", "diversification3", "nfts1", "nfts2", "nfts3", "total_score"))
RemoveNAs <- function(table = dt,
na.to = 0) {
for (j in seq_len(ncol(table)))
set(table,which(is.na(table[[j]])),j,na.to)
}
base.style <- rep("20%", times = 21)
Rescale <- function(x, newrange, oldrange = NULL) {
if(is.null(oldrange)){
if (is.numeric(x) && is.numeric(newrange)) {
xna <- is.na(x)
if (all(xna))
return(x)
if (any(xna))
xrange <- range(x[!xna])
else xrange <- range(x)
if (xrange[1] == xrange[2])
return(x)
mfac <- (newrange[2] - newrange[1])/(xrange[2] - xrange[1])
return(newrange[1] + (x - xrange[1]) * mfac)
} else {
warning("Only numeric objects can be rescaled")
return(x)
}
} else if(!is.null(oldrange)){
if (is.numeric(x) && is.numeric(newrange)) {
xna <- is.na(x)
if (all(xna))
return(x)
mfac <- (newrange[2] - newrange[1])/(oldrange[2] - oldrange[1])
new.vals <- newrange[1] + (x - oldrange[1]) * mfac
if(length(new.vals[ new.vals > max(newrange)]))
new.vals[ new.vals > max(newrange)] <- max(newrange)
if(length(new.vals[ new.vals < min(newrange)]))
new.vals[ new.vals < min(newrange)] <- min(newrange)
return(new.vals)
} else {
warning("Only numeric objects can be rescaled")
return(x)
}
}
}
categories <- c("nfts", "governance", "variety", "staking", "longevity", "bridge", "activity")
MergeDataFrames <- function(list.of.data.frames,
by=NULL,
all=NULL){
if(is.null(by)) stop("You need to explicitly define your 'by' statement")
if(is.null(all)) {
all <- FALSE
message("MergeDataFrames: only complete rows will be returned. Use all=TRUE to return all rows.")
}
Reduce(
function(...)
merge(...,
by=by,
all=all),
list.of.data.frames)
}
empty.df <- data.table(total_score=0,longevity=0,longevity_value=0,activity=0,activity_value=0,governance=0,governance_value=0,bridge=0,bridge_value=0,staking=0,staking_value=0,variety=0,variety_value=0,nfts=0,nft_value=0)
# theme_univ3_small <- function(base_size = 12,
# bgcolor.dark = "white",
# bgcolor.light = "white",
# text.color = "white",
# title.color = "#white",
# lines.color = "#EDEDF3") {
# half_line <- base_size/2
# theme(text = element_text(family = 'roboto-mono',
# face = "plain",
# colour = text.color, size = base_size,
# lineheight = 0.9, hjust = 0.5,
# vjust = 0.5, angle = 0,
# margin = margin(), debug = FALSE),
#
# plot.background = element_rect(color = NA, fill = "black"),
# plot.title = element_text(size = rel(1.2),
# color = title.color,
# margin = margin(b = half_line/2)),
#
# strip.background = element_rect(fill = bgcolor.dark, colour = NA),
# strip.text = element_text(colour = text.color, size = rel(0.8)),
# strip.text.x = element_text(margin = margin(t = half_line/2,
# b = half_line/2)),
# strip.text.y = element_text(angle = -90,
# margin = margin(l = half_line/2,
# r = half_line/2)),
#
# axis.line = element_blank(),
# axis.ticks.x = element_blank(),
# axis.ticks.y = element_blank(),
#
# axis.text = element_text(color = text.color, size = base_size - 2),
#
# panel.background = element_rect(fill = "transparent", colour = NA),
# panel.border = element_blank(),
# panel.grid.major.x = element_blank(),
# panel.grid.major.y = element_blank(),
# panel.grid.minor.x = element_blank(),
# panel.grid.minor.y = element_blank(),
#
# legend.background = element_rect(colour = NA, fill = "transparent"),
# legend.key = element_rect(colour = NA, fill = "transparent"),
#
# axis.title.x=element_blank(),
# axis.text.x=element_blank(),
# axis.title.y=element_blank(),
# axis.text.y=element_blank())
# }

3
apps/solana/solarscored/score_criteria.csv
View File

@ -17,6 +17,3 @@ Staker,Stakooooor,staker_3,3,1000+ SOL currently staked onto Solana,
Explorer,Exploror,explorer_1,1,1+ unique programs interacted with,
Explorer,Explorooor,explorer_2,2,10+ unique programs interacted with,
Explorer,Explorooooor,explorer_3,3,25+ unique programs interacted with,
NFTs,NFT Enjoyooor,nfts_1,1,"1+ $SOL on NFTs (buys, sells, mints, last 180 days)",
NFTs,Sharp,nfts_2,2,"100+ $SOL on NFTs (buys, sells, mints, last 180 days)",
NFTs,NFT Whale,nfts_3,3,"1k+ $SOL on NFTs (buys, sells, mints, last 180 days)",
1 category score_name metric_name points score_description velocity_query
17 Explorer Exploror explorer_1 1 1+ unique programs interacted with
18 Explorer Explorooor explorer_2 2 10+ unique programs interacted with
19 Explorer Explorooooor explorer_3 3 25+ unique programs interacted with
NFTs NFT Enjoyooor nfts_1 1 1+ $SOL on NFTs (buys, sells, mints, last 180 days)
NFTs Sharp nfts_2 2 100+ $SOL on NFTs (buys, sells, mints, last 180 days)
NFTs NFT Whale nfts_3 3 1k+ $SOL on NFTs (buys, sells, mints, last 180 days)

863
apps/solana/solarscored/scratch.sql
View File

@ -1,863 +0,0 @@
CASE WHEN marketplace in ('yawww', 'solanart', 'hadeswap', 'solport', 'coral cube') THEN '0% Marketplace'
WHEN marketplace in ('opensea', 'magic eden v1', 'solana monkey business marketplace', 'magic eden v1') THEN 'Royalty Marketplace' END marketplace_type,
SELECT (post.value - pre.value) * POWER (10, -9) AS dff
, COALESCE(dff, 0) / s.sales_amount AS pct_m
, a.value:pubkey::string AS pubkey
, s.*
FROM solana.core.fact_nft_sales s
LEFT JOIN solana.core.fact_transactions t
ON t.tx_id = s.tx_id
LEFT JOIN TABLE(FLATTEN(account_keys)) a
ON a.value:pubkey::string = 'Fz7HjwoXiDZNRxXMfLAAJLbArqjCTVWrG4wekit2VpSd'
LEFT JOIN TABLE(FLATTEN(t.pre_balances)) pre
ON pre.index = a.index
LEFT JOIN TABLE(FLATTEN(t.post_balances)) post
ON post.index = a.index
WHERE s.block_timestamp >= '2022-11-01'
AND t.block_timestamp >= '2022-11-01'
AND s.marketplace = 'solanart'
AND s.succeeded
ORDER BY pct_m ASC
-- LIMIT 100
-- solanart
-- 39fEpihLATXPJCQuSiXLUSiCbGchGYjeL39eyXh3KbyT
SELECT CONCAT('https://solana.fm/tx/', s.tx_id) AS sfm_link
, l.label
, s.*
FROM solana.core.fact_nft_sales s
JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= '2022-05-01'
AND s.block_timestamp <= '2022-05-02'
AND s.marketplace = 'solanart'
AND s.succeeded
LIMIT 100
SELECT s.*
FROM solana.core.fact_nft_sales s
LEFT JOIN solana.core.fact_transfers t
ON t.tx_id = s.tx_id
WHERE s.block_timestamp >= '2022-07-01'
AND s.block_timestamp <= '2022-08-01'
AND t.tx_id IS NULL
AND s.marketplace = 'yawww'
LIMIT 100
-- solanart
WITH b0 AS (
SELECT s.tx_id
, s.sales_amount
, s.mint
, SUM(CASE WHEN tx_to = '39fEpihLATXPJCQuSiXLUSiCbGchGYjeL39eyXh3KbyT' THEN t.amount ELSE 0 END) AS m_amt
, SUM(CASE WHEN tx_to = '39fEpihLATXPJCQuSiXLUSiCbGchGYjeL39eyXh3KbyT' OR amount > sales_amount * 0.5 THEN 0 ELSE amount END) AS r_amt
FROM solana.core.fact_nft_sales s
JOIN solana.core.fact_transfers t
ON t.tx_id = s.tx_id
AND t.mint = 'So11111111111111111111111111111111111111112'
WHERE s.block_timestamp >= '2022-11-01'
AND s.block_timestamp <= '2022-11-05'
AND t.block_timestamp >= '2022-11-01'
AND t.block_timestamp <= '2022-11-05'
AND s.marketplace = 'solanart'
AND s.succeeded
GROUP BY 1, 2, 3
)
SELECT CONCAT('https://solana.fm/tx/', tx_id) AS sfm_link
, CONCAT('https://solscan.io/token/', mint) AS mint_link
, tx_id
, sales_amount
, m_amt
, r_amt
, ROUND(m_amt / sales_amount, 5) AS m_pct
, ROUND(r_amt / sales_amount, 5) AS r_pct
FROM b0
https://solana.fm/tx/5uoq1G9wBzuei7WS8MxN7XZwVoD3KuHTJzTZGphpvXmG42tTL5nXuJB43W7BanSLP7zRzc5R6TQNZmMNQ74L4vES
Updates
Dashboard on royalties and thread
Version 0.1 of SolarScored is out
Working on Business Intelligence Report
Problems Encountered
Priorities
Concerns
Excitements
SELECT *
FROM solana.core.fact_transfers
WHERE t.block_timestamp >= '2022-05-01'
AND t.block_timestamp <= '2022-05-05'
AND tx_id = '5uoq1G9wBzuei7WS8MxN7XZwVoD3KuHTJzTZGphpvXmG42tTL5nXuJB43W7BanSLP7zRzc5R6TQNZmMNQ74L4vES'
WITH prices AS (
SELECT date_trunc('week', recorded_hour)::date AS date
, AVG(close) AS price
FROM crosschain.core.fact_hourly_prices
WHERE id = 'solana'
AND close IS NOT NULL
GROUP BY 1
), amount AS (
SELECT date_trunc('week', block_timestamp)::date AS date
, SUM(amount) AS sol_volume
FROM solana.core.fact_transfers t
WHERE mint = 'So11111111111111111111111111111111111111111'
AND NOT tx_to IN (
'F8Vyqk3unwxkXukZFQeYyGmFfTG3CAX4v24iyrjEYBJV'
, '9BVcYqEQxyccuwznvxXqDkSJFavvTyheiTYk231T1A8S'
, '3uTzTX5GBSfbW7eM9R9k95H7Txe32Qw3Z25MtyD2dzwC'
, '5Xm6nU1Bi6UewCrhJQFk1CAV97ZJaRiFw4tFNhUbXy3u'
)
AND NOT tx_from IN (
'F8Vyqk3unwxkXukZFQeYyGmFfTG3CAX4v24iyrjEYBJV'
, '9BVcYqEQxyccuwznvxXqDkSJFavvTyheiTYk231T1A8S'
, '3uTzTX5GBSfbW7eM9R9k95H7Txe32Qw3Z25MtyD2dzwC'
, '5Xm6nU1Bi6UewCrhJQFk1CAV97ZJaRiFw4tFNhUbXy3u'
)
GROUP BY 1
)
SELECT a.date
, a.sol_volume
, (a.sol_volume * p.price) AS usd_volume
FROM amount a
JOIN prices p ON p.date = a.date
SELECT *
FROM solana.core.fact_swaps
WHERE block_timestamp >= '2022-11-08'
AND tx_id = '66DAgKyZ4qccKdtb4hdLkDpGbppGym4jPxTfqxS8DKLbBw5atrWN6QS2mLrrHPSrUmbUcsWKgYQs3wye2yowpr1i'
SELECT *
FROM solana.core.fact_transfers
WHERE block_timestamp >= CURRENT_DATE - 90
AND mint = 'So11111111111111111111111111111111111111111'
-- AND tx_to = 'F8Vyqk3unwxkXukZFQeYyGmFfTG3CAX4v24iyrjEYBJV'
ORDER BY amount DESC
LIMIT 100
WITH nft_sales AS (
SELECT block_timestamp::date AS date
, 'NFT Sale' AS tx_type
, SUM(sales_amount) AS sol_volume
FROM solana.core.fact_nft_sales s
WHERE block_timestamp >= '2022-01-01'
GROUP BY 1, 2
), swaps AS (
SELECT block_timestamp::date AS date
, 'Token Swap' AS tx_type
, SUM(CASE WHEN swap_from_mint = 'So11111111111111111111111111111111111111112' THEN swap_from_amount ELSE swap_to_amount END) AS sol_volume
FROM solana.core.fact_swaps
WHERE block_timestamp >= '2022-01-01'
GROUP BY 1, 2
), prices AS (
SELECT recorded_hour::date AS date
, AVG(close) AS price
FROM crosschain.core.fact_hourly_prices
WHERE id = 'solana'
GROUP BY 1
)
SELECT date_trunc('week', COALESCE(n.date, w.date)) AS week
, SUM( COALESCE(n.sol_volume, 0) ) AS nft_volume_sol
, SUM( COALESCE(s.sol_volume, 0) ) AS swap_volume_sol
, SUM( COALESCE(n.sol_volume, 0) + COALESCE(s.sol_volume, 0) ) AS tot_volume_sol
, SUM( price * COALESCE(n.sol_volume, 0) ) AS nft_volume_usd
, SUM( price * COALESCE(s.sol_volume, 0) ) AS swap_volume_usd
, SUM( price * (COALESCE(n.sol_volume, 0) + COALESCE(s.sol_volume, 0)) ) AS tot_volume_usd
FROM nft_sales n
FULL OUTER JOIN swaps s
ON s.date = n.date
LEFT JOIN prices p
ON p.date = COALESCE(n.date, s.date)
GROUP BY 1
SELECT s.*
, a.value:pubkey::string AS pubkey
, (post.value - pre.value) * POWER (10, -9) AS dff
FROM solana.core.fact_nft_sales s
JOIN solana.core.fact_transactions t
ON t.tx_id = s.tx_id
LEFT JOIN TABLE(FLATTEN(account_keys)) a
ON a.value:pubkey::string = 'Fz7HjwoXiDZNRxXMfLAAJLbArqjCTVWrG4wekit2VpSd'
LEFT JOIN TABLE(FLATTEN(t.pre_balances)) pre
ON pre.index = a.index
LEFT JOIN TABLE(FLATTEN(t.post_balances)) post
ON post.index = a.index
WHERE s.block_timestamp >= '2022-11-01'
AND t.block_timestamp >= '2022-11-01'
AND s.marketplace = 'yawww'
WITH buys AS (
SELECT purchaser AS user_address
, SUM(sales_amount) AS buy_volume
FROM solana.core.fact_nft_sales
WHERE block_timestamp >= CURRENT_DATE - 180
AND succeeded
GROUP BY 1
), sells AS (
SELECT seller AS user_address
, SUM(sales_amount) AS sell_volume
FROM solana.core.fact_nft_sales
WHERE block_timestamp >= CURRENT_DATE - 180
AND succeeded
GROUP BY 1
), mints AS (
SELECT purchaser AS user_address
, SUM(mint_price) AS mint_volume
FROM solana.core.fact_nft_sales
WHERE block_timestamp >= CURRENT_DATE - 180
AND succeeded
AND mint_currency = 'So11111111111111111111111111111111111111111'
AND mint_price <= 15
GROUP BY 1
)
SELECT COALESCE(b.user_address, s.user_address, m.user_address) AS user_address
, COALESCE(b.buy_volume, 0) + COALESCE(s.sell_volume, 0) + COALESCE(s.mint_volume, 0) AS volume
FROM buys b
FULL OUTER JOIN sells s
ON s.user_address = b.user_address
FULL OUTER JOIN mints m
ON m.user_address = COALESCE(b.user_address, s.user_address)
SELECT *
FROM solana.core.fact_nft_mints
WHERE block_timestamp >= CURRENT_DATE - 2
AND succeeded
LIMIT 11
SELECT CONCAT('https://solana.fm/tx/', e.tx_id) AS sfm_link
, ARRAY_SIZE(e.inner_instruction:instructions)
, e.tx_id
, e.block_id
, e.block_timestamp::date AS date
, e.inner_instruction:instructions[0]:parsed:info:mint::string AS mint
, s.sales_amount
, CASE WHEN e.inner_instruction:instructions[0]:parsed:info:lamports > 0 THEN 0 WHEN inner_instruction:instructions[3]:parsed:info:lamports > 0 THEN 3 ELSE 5 END AS ind
, COALESCE(e.inner_instruction:instructions[ind]:parsed:info:lamports * POWER(10, -9), 0) AS price_0
, COALESCE(e.inner_instruction:instructions[ind + 1]:parsed:info:lamports * POWER(10, -9), 0) AS yawww_fee
, COALESCE(e.inner_instruction:instructions[ind + 2]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(e.inner_instruction:instructions[ind + 3]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(e.inner_instruction:instructions[ind + 4]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(e.inner_instruction:instructions[ind + 5]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(e.inner_instruction:instructions[ind + 6]:parsed:info:lamports * POWER(10, -9), 0) AS collection_royalty
, price_0 + yawww_fee + collection_royalty AS price
, CASE WHEN price = 0 THEN 0 ELSE yawww_fee / price END AS pct_m
, CASE WHEN price = 0 THEN 0 ELSE collection_royalty / price END AS pct_r
, CASE
WHEN mint = '2ZkSXXKvdxCCkHYkhfL3xmGvioMQoERCMPVzxmRjVF2K' THEN 'Liberty Square'
WHEN mint = '3TmpAxD2Z4zPfFVR7uNQMFw4tj7sNSwc2MzSFyjoV2Np' THEN 'Heroes Of Astron'
WHEN mint = '9XX3iGGCVaqivVkgVk8ci6SF3zMRbKnxp1fQhJFXmsam' THEN 'The Resurrected'
WHEN mint = 'Afw1QQLzHAFEUWJCriRunLzz3PL4v1ZDQvs1izk29Wvi' THEN 'Heroes Of Astron'
ELSE INITCAP(l.label) END AS collection
, e.inner_instruction
, t.inner_instruction
, e.instruction
FROM solana.core.fact_events e
JOIN solana.core.fact_nft_sales s
ON s.tx_id = e.tx_id
JOIN solana.core.fact_transactions t
ON t.tx_id = e.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = inner_instruction:instructions[0]:parsed:info:mint::string
WHERE e.block_timestamp >= '2022-06-04 13:49:14'
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
AND e.succeeded
AND mint IS NOT NULL
AND price < 1000
AND ROUND(pct_m, 5) = 0.0
-- AND pct_r > 0
ORDER BY pct_r DESC, e.block_timestamp DESC, e.tx_id
LIMIT 100
SELECT *
FROM solana.core.fact_transfers
WHERE block_timestamp >= '2022-12-06'
AND tx_id = '5trNueei7P3ukTaHBQSZBirhfbxgetF9D53DMvFHZRfNH8JwKdnjVjTV2zrG56idwvYbtquGieXSHRKSEzV4EZgz'
WITH prices AS (
SELECT date_trunc('week', recorded_hour)::date AS date
, AVG(close) AS price
FROM crosschain.core.fact_hourly_prices
WHERE id = 'solana'
GROUP BY 1
), amount (
SELECT date_trunc('week', block_timestamp) AS date
, SUM(amount) AS sol_amount
FROM solana.core.fact_transfers t
WHERE mint = 'So11111111111111111111111111111111111111112'
GROUP BY 1
)
SELECT p.date
, a.sol_volume
, (a.sol_amount * p.price) AS usd_volume
FROM amount a
LEFT JOIN prices p ON p.date = a.date
SELECT date
FROM solana.core.fact_transfers t
LIMIT 100
SELECT CONCAT('https://solana.fm/tx/', e.tx_id) AS sfm_link
, ARRAY_SIZE(inner_instruction:instructions)
, e.tx_id
, e.block_id
, e.block_timestamp::date AS date
, inner_instruction:instructions[0]:parsed:info:mint::string AS mint
, COALESCE(inner_instruction:instructions[ind]:parsed:info:lamports * POWER(10, -9), 0) AS price_0
, COALESCE(inner_instruction:instructions[ind + 1]:parsed:info:lamports * POWER(10, -9), 0) AS yawww_fee
, COALESCE(inner_instruction:instructions[ind + 2]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(inner_instruction:instructions[ind + 3]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(inner_instruction:instructions[ind + 4]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(inner_instruction:instructions[ind + 5]:parsed:info:lamports * POWER(10, -9), 0)
+ COALESCE(inner_instruction:instructions[ind + 6]:parsed:info:lamports * POWER(10, -9), 0) AS collection_royalty
, price_0 + yawww_fee + collection_royalty AS price
, CASE WHEN price = 0 THEN 0 ELSE yawww_fee / price END AS pct_m
, CASE WHEN price = 0 THEN 0 ELSE collection_royalty / price END AS pct_r
, CASE
WHEN mint = '2ZkSXXKvdxCCkHYkhfL3xmGvioMQoERCMPVzxmRjVF2K' THEN 'Liberty Square'
WHEN mint = '3TmpAxD2Z4zPfFVR7uNQMFw4tj7sNSwc2MzSFyjoV2Np' THEN 'Heroes Of Astron'
WHEN mint = '9XX3iGGCVaqivVkgVk8ci6SF3zMRbKnxp1fQhJFXmsam' THEN 'The Resurrected'
WHEN mint = 'Afw1QQLzHAFEUWJCriRunLzz3PL4v1ZDQvs1izk29Wvi' THEN 'Heroes Of Astron'
ELSE INITCAP(l.label) END AS collection
, inner_instruction
, instruction
FROM solana.core.fact_events e
JOIN solana.core.fact_nft_sales s
ON s.tx_id = e.tx_id
LEFT JOIN solana.core.dim_labels l ON l.address = inner_instruction:instructions[0]:parsed:info:mint::string
WHERE e.block_timestamp >= '2022-06-04 13:49:14'
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
AND e.succeeded
AND mint IS NOT NULL
AND price < 1000
AND ROUND(pct_m, 5) = 0.0
//AND pct_r > 0
ORDER BY pct_r DESC, e.block_timestamp DESC, e.tx_id
LIMIT 100
SELECT MAX(ARRAY_SIZE(inner_instruction:instructions))
FROM solana.core.fact_events e
LEFT JOIN solana.core.dim_labels l ON l.address = inner_instruction:instructions[0]:parsed:info:mint::string
WHERE e.block_timestamp >= '2022-07-04 13:49:14'
AND inner_instruction:instructions[0]:parsed:info:mint::string IS NOT NULL
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
SELECT date_trunc('month', e.block_timestamp)::date AS date
, SUM(COALESCE(inner_instruction:instructions[5]:parsed:info:lamports * POWER(10, -9), 0)) AS price_0
, SUM(COALESCE(inner_instruction:instructions[6]:parsed:info:lamports * POWER(10, -9), 0)) AS yawww_fee
, SUM(COALESCE(inner_instruction:instructions[7]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[8]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[9]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[10]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[11]:parsed:info:lamports * POWER(10, -9), 0)) AS collection_royalty
, price_0 + yawww_fee + collection_royalty AS price
, yawww_fee / price AS pct_m
, collection_royalty / price AS pct_r
FROM solana.core.fact_events e
WHERE e.block_timestamp >= '2022-07-04 13:49:14'
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
AND price < 1000
GROUP BY 1
WITH b0 AS (
SELECT date_trunc('month', e.block_timestamp)::date AS date
, COALESCE(inner_instruction:instructions[5]:parsed:info:lamports * POWER(10, -9), 0) AS price_0
, COALESCE(inner_instruction:instructions[6]:parsed:info:lamports * POWER(10, -9), 0) AS yawww_fee
, COALESCE(inner_instruction:instructions[7]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[8]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[9]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[10]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[11]:parsed:info:lamports * POWER(10, -9), 0) AS collection_royalty
, price_0 + yawww_fee + collection_royalty AS price
, ROUND(yawww_fee / price, 4) AS pct_m
, ROUND(collection_royalty / price, 4) AS pct_r
FROM solana.core.fact_events e
WHERE e.block_timestamp >= '2022-06-01'
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
)
SELECT date
, pct_m
, COUNT(1) AS n
FROM b0
GROUP BY 1, 2
SELECT date_trunc('month', block_timestamp)::date AS date
, COUNT(1) AS n
FROM solana.core.fact_nft_sales
WHERE marketplace = 'yawww'
GROUP BY 1
SELECT date_trunc('month', e.block_timestamp)::date AS date
, SUM(COALESCE(inner_instruction:instructions[5]:parsed:info:lamports * POWER(10, -9), 0)) AS price_0
, SUM(COALESCE(inner_instruction:instructions[6]:parsed:info:lamports * POWER(10, -9), 0)) AS yawww_fee
, SUM(COALESCE(inner_instruction:instructions[7]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[8]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[9]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[10]:parsed:info:lamports * POWER(10, -9), 0) + COALESCE(inner_instruction:instructions[11]:parsed:info:lamports * POWER(10, -9), 0)) AS collection_royalty
, price_0 + yawww_fee + collection_royalty AS price
, yawww_fee / price AS pct_m
, collection_royalty / price AS pct_r
FROM solana.core.fact_events e
WHERE e.block_timestamp >= '2022-07-04 13:49:14'
AND instruction:programId = '5SKmrbAxnHV2sgqyDXkGrLrokZYtWWVEEk5Soed7VLVN'
AND price < 1000
GROUP BY 1
SELECT s.marketplace
-- , t.tx_to
, s.tx_id
, l.label
, CONCAT('https://solana.fm/tx/', s.tx_id) AS sfm_link
, ARRAY_SIZE(tr.instructions) AS as_in
, ARRAY_SIZE(tr.instructions[0]:instructions) AS as_in0
, *
FROM solana.core.fact_nft_sales s
-- JOIN solana.core.fact_transfers t
-- ON t.tx_id = s.tx_id
-- AND t.tx_to = '5z1vT6R1HcgvzDpto63rrhgVF4CjA4Sho6DbN58Pwzw3'
JOIN solana.core.dim_labels l
ON l.address = s.mint
AND l.label = 'grimzdao'
WHERE s.block_timestamp >= '2022-10-01'
-- AND t.block_timestamp >= '2022-10-01'
AND s.marketplace ILIKE '%yaw%'
hayleyngreenfield@gmail.com
Is there anything you think I could / should do in these areas to make sure he's productive (or future people are productive)
There was space for me to help grow Ben's skillset.
Should we do more BI stuff?
We're enjoying it (sustainable)
Right incentives (making money)
'
SELECT CONCAT('https://solana.fm/tx/', tx_id) AS sfm_link
, *
FROM solana.core.fact_nft_sales s
JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= CURRENT_DATE - 3
AND marketplace = 'hadeswap'
AND l.label = 'Okay Bears'
LIMIT 100
SELECT l.label
, s.tx_id
, *
FROM solana.core.fact_nft_sales s
JOIN solana.core.fact_transfers t
ON t.tx_id = s.tx_id
AND t.tx_to = '5z1vT6R1HcgvzDpto63rrhgVF4CjA4Sho6DbN58Pwzw3'
JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= CURRENT_DATE - 90
AND t.block_timestamp >= CURRENT_DATE - 90
AND s.tx_id IN (
'5JpNhDGvqTjs7efXr5H2DbZPyQjN7yXHpaUDr8d3ba4BnMXZj8p2hzekJKG872UfDLcS9WugExyBtRkFsNYQhhmY',
'3EgBVWgqjA5fGDGLgEC4fmbrg2LrPP37MqdHyj8yyaYTuBnsLCdetorwyssvCf9yLq74YJ2U4juZ3pp7Wb93SRjc',
'4qeihebwmvB8ot37DdXUYe3aavqyyNcRTqJM4VoPDLtX7PUJjf8UH2AAXbjjBFQ2QW1CXQCXivPucGwRCMzghNUn',
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'45SczJ13kx96N8me7er3Xmgx5BA8VHA42yELckhjgDPsjcVkYDRGeHDSuQUNzjVstgc3ShwgjocDJvqC3JKFc1UR',
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'45Fzc4fJCDqzJH2WLUV2U3YJf87At7Z3YgsyvevvKJ9cuwVXTVETaAr3hCk6ZKdC3hc4CWmYaC8ZUBzzWFQ3Q8kw',
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'3MhactaRa7XAuyYve7EjQk62MXNcfre25ENgWM9XPjNAdYj9JASPRCyNzhVMsxTdSBGQX97pnEYoLKEAb8xjwD6D',
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'tuMpRaXBWc92ygcqgfgjSZjwvxpgm247AWtFxwg6d3iRPmGHPjSpB8wojefiMHHA4TeyQtFizJcUczpoVsFgcNU',
'3Eg3g1JB18EsZn3iCHpZAm5QiTSjCn6BDdeZbCqiZ5AmMwohNdENrewySDeYNDyLMfGAvox6wuDno21ghgNJ4pR',
'4MYzNmhSxQhZ9vu1n4H9cFfyuqQHTqNNo3ExNkh6x5XQTR5EprzNRNKwsgHvzznRrMeGdv5yWSoZJGvM4dL2eZiB',
'2KEYGUHXEh5N3MhajtbkfDtf9pq26Wqi2QcJMS4gjWEpw5KEc2pPKUuDkj3ef4yfTNK7VJQfLhG16tuyEGA8vZ5G',
'fALSk5BGE3m3QpGwr9Fch2uqweRSLm6PrsJqoHKGnHmrCh28sdTNvSHVBW86NihT2joYkvjxrxH1gq9Qd1sFtEQ',
'3nqyc1fPzQ1CvHhj1t8rGFqjVV9vh5ehBUrJdrGrUg3t8xa1ifNR5pE2vf66oqQgzHDTRpNw45a95vt49WdbyQUF'
)
'Bring back thread competition (open it up the whole company)
Bring back NFT Deal Score
SELECT marketplace
, SUM(sales_amount) AS amt
FROM solana.core.fact_nft_sales s
WHERE block_timestamp >= '2022-08-01'
AND sales_amount < 1000
GROUP BY 1
ORDER BY 2 DESC
SELECT CONCAT('https://solana.fm/tx/', tx_id) AS sfm_link
, l.label
, s.*
FROM solana.core.fact_nft_sales s
JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE block_timestamp >= CURRENT_DATE - 7
AND marketplace = 'hadeswap'
LIMIT 100
WITH tx AS (
SELECT DISTINCT s.tx_id
, block_timestamp::date AS date
, COALESCE(m.token_name, 'Other') AS token_name
, s.mint
, sales_amount
, purchaser
FROM solana.core.fact_nft_sales s
JOIN solana.core.dim_nft_metadata m ON m.mint = s.mint
WHERE block_timestamp >= '2022-01-01'
AND block_timestamp <= '2022-01-02'
AND m.token_name = 'Okay Bears'
AND marketplace LIKE 'magic eden v1'
AND succeeded
AND sales_amount > 0
), base AS (
SELECT t.tx_id
, SUM(CASE WHEN tx_to = 'rFqFJ9g7TGBD8Ed7TPDnvGKZ5pWLPDyxLcvcH2eRCtt' AND t.mint = 'So11111111111111111111111111111111111111112' THEN amount ELSE 0 END) AS m_amt
, SUM(CASE WHEN tx_to <> 'rFqFJ9g7TGBD8Ed7TPDnvGKZ5pWLPDyxLcvcH2eRCtt' AND t.mint = 'So11111111111111111111111111111111111111112' AND amount < (sales_amount * 0.5) THEN amount ELSE 0 END) AS r_amt
FROM solana.core.fact_transfers t
JOIN tx ON tx.tx_id = t.tx_id
WHERE block_timestamp >= '2022-01-01'
GROUP BY 1
), b0 AS (
SELECT tx.tx_id
, date
, mint
, token_name
, sales_amount
-- , s_amt
, m_amt
, r_amt
, ROUND(sales_amount - COALESCE(r_amt, 0) - COALESCE(m_amt, 0),4) AS s_amt
-- , ROUND(sales_amount - COALESCE(s_amt, 0) - COALESCE(m_amt, 0),4) AS r_amt_calc
, s_amt / sales_amount AS s_pct
, m_amt / sales_amount AS m_pct
, r_amt / sales_amount AS r_pct
FROM tx
JOIN base b ON b.tx_id = tx.tx_id
)
, b1 AS (
SELECT token_name
, date_trunc('month', date) AS month
, SUM(sales_amount) AS sales_amount
, SUM(s_amt) AS s_amt
, SUM(m_amt) AS m_amt
, SUM(r_amt) AS r_amt
, MEDIAN(s_pct) AS s_pct
, MEDIAN(m_pct) AS m_pct
, MEDIAN(r_pct) AS r_pct
, 100 * AVG(CASE WHEN b0.r_amt = 0 THEN 1.0 ELSE 0.0 END) AS pct_no_royalty
FROM b0
GROUP BY 1, 2
)
SELECT *
, 100 * (r_amt / sales_amount) AS royalty_pct
FROM b1
SELECT CONCAT('https://solscan.io/tx/', tx_id) AS sol_link
, *
FROM solana.core.fact_nft_mints
WHERE mint_currency = 'So11111111111111111111111111111111111111111'
AND mint_price <= 15
ORDER BY mint_price DESC
LIMIT 100
--
WITH tx AS (
SELECT DISTINCT s.tx_id
, block_timestamp::date AS date
, COALESCE(m.token_name, 'Other') AS token_name
, s.mint
, sales_amount
, purchaser
FROM solana.core.fact_nft_sales s
JOIN solana.core.dim_nft_metadata m ON m.mint = s.mint
WHERE block_timestamp >= '2022-01-01'
-- AND m.token_name = 'Okay Bears'
AND marketplace = 'magic eden v2'
AND succeeded
AND sales_amount > 0
), mint AS (
SELECT date_trunc('month', block_timestamp)::date AS month
, SUM(mint_price) AS mint_volume
FROM solana.core.fact_nft_mints m
WHERE month >= '2022-01-01'
AND mint_currency = 'So11111111111111111111111111111111111111111'
AND mint_price <= 15
GROUP BY 1
)
, base AS (
SELECT t.tx_id
, SUM(CASE WHEN tx_to = 'rFqFJ9g7TGBD8Ed7TPDnvGKZ5pWLPDyxLcvcH2eRCtt' AND t.mint = 'So11111111111111111111111111111111111111112' THEN amount ELSE 0 END) AS m_amt
, SUM(CASE WHEN tx_to <> 'rFqFJ9g7TGBD8Ed7TPDnvGKZ5pWLPDyxLcvcH2eRCtt' AND t.mint = 'So11111111111111111111111111111111111111112' AND amount < (sales_amount * 0.5) THEN amount ELSE 0 END) AS r_amt
FROM solana.core.fact_transfers t
JOIN tx ON tx.tx_id = t.tx_id
WHERE block_timestamp >= '2022-01-01'
GROUP BY 1
), b0 AS (
SELECT tx.tx_id
, date
, mint
, token_name
, sales_amount
-- , s_amt
, m_amt
, r_amt
, ROUND(sales_amount - COALESCE(r_amt, 0) - COALESCE(m_amt, 0),4) AS s_amt
-- , ROUND(sales_amount - COALESCE(s_amt, 0) - COALESCE(m_amt, 0),4) AS r_amt_calc
, s_amt / sales_amount AS s_pct
, m_amt / sales_amount AS m_pct
, r_amt / sales_amount AS r_pct
FROM tx
JOIN base b ON b.tx_id = tx.tx_id
)
, b1 AS (
SELECT date_trunc('month', date) AS month
, SUM(sales_amount) AS sales_amount
, SUM(s_amt) AS s_amt
, SUM(m_amt) AS m_amt
, SUM(r_amt) AS r_amt
, MEDIAN(s_pct) AS s_pct
, MEDIAN(m_pct) AS m_pct
, MEDIAN(r_pct) AS r_pct
, 100 * AVG(CASE WHEN b0.r_amt = 0 THEN 1.0 ELSE 0.0 END) AS pct_no_royalty
FROM b0
GROUP BY 1
)
SELECT b1.*
, 100 * (r_amt / sales_amount) AS royalty_pct
, m.mint_volume
FROM b1
JOIN mint m ON m.month = b1.month
-- explorer
WITH signers AS (
SELECT tx_id
, signers[0]::string AS user_address
FROM solana.core.fact_transactions
WHERE block_timestamp >= CURRENT_DATE - 90
GROUP BY 1, 2
)
SELECT user_address
, COUNT(DISTINCT COALESCE(l.label, e.program_id)) AS n_unique_programs
FROM solana.core.fact_events e
JOIN signers s ON s.tx_id = e.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = e.program_id
WHERE e.block_timestamp >= CURRENT_DATE - 90
GROUP BY 1
-- Staker - How much SOL have they staked?
WITH b0 AS (
SELECT *
, ROW_NUMBER() OVER (PARTITION BY stake_authority ORDER BY block_timestamp DESC) AS rn
FROM solana.core.ez_staking_lp_actions
)
SELECT stake_authority AS user_address
, post_tx_staked_balance * POWER(10, -9) AS staked_sol
FROM b0
WHERE rn = 1
-- Bridgor - How many times are they bridging assets onto Solana (from a bridge or CEX)?
WITH tx AS (
SELECT DISTINCT tx_id
FROM solana.core.fact_events e
JOIN solana.core.dim_labels l
ON l.address = e.program_id
AND l.label_subtype = 'bridge'
WHERE e.block_timestamp >= CURRENT_DATE - 2
)
SELECT CASE WHEN tx.tx_id IS NULL THEN label_type ELSE 'bridge' END AS clean_label
, COUNT(1) AS n
FROM solana.core.fact_transfers t
LEFT JOIN tx ON tx.tx_id = t.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = t.tx_from
AND (l.label_type = 'cex' OR l.label_subtype = 'bridge' )
WHERE t.block_timestamp >= CURRENT_DATE - 2
AND (tx.tx_id IS NOT NULL OR l.label_type IS NOT NULL)
GROUP BY 1
ORDER BY 2 DESC
WITH tx AS (
SELECT DISTINCT tx_id
FROM solana.core.fact_events e
JOIN solana.core.dim_labels l
ON l.address = e.program_id
AND l.label_subtype = 'bridge'
WHERE e.block_timestamp >= CURRENT_DATE - 90
)
SELECT tx_to
, COUNT(1) AS n_bridge
, SUM(CASE WHEN mint = 'So11111111111111111111111111111111111111112' THEN amount ELSE 0 END) AS sol_bridge_amt
FROM solana.core.fact_transfers t
LEFT JOIN tx ON tx.tx_id = t.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = t.tx_from
AND (l.label_type = 'cex' OR l.label_subtype = 'bridge' )
WHERE t.block_timestamp >= CURRENT_DATE - 90
AND (tx.tx_id IS NOT NULL OR l.label_type IS NOT NULL)
GROUP BY 1
ORDER BY 3 DESC
SELECT *
FROM solana.core.dim_labels
WHERE label_type = 'nft'
AND label_subtype = 'nf_token_contract'
LIMIT 100
SELECT *
FROM solana.core.fact_nft_sales s
JOIN solana.core.fact_transactions t
ON t.tx_id = s.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= CURRENT_DATE - 1
AND t.block_timestamp >= CURRENT_DATE - 1
AND l.label IS NULL
ORDER BY s.sales_amount DESC
LIMIT 100
SELECT *
FROM solana.core.fact_nft_sales s
JOIN solana.core.fact_transactions t
ON t.tx_id = s.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= CURRENT_DATE - 1
AND t.block_timestamp >= CURRENT_DATE - 1
AND l.label IS NULL
ORDER BY s.sales_amount DESC
LIMIT 100
SELECT *
FROM solana.core.fact_nft_sales s
WHERE s.block_timestamp >= '2022-11-30'
AND s.block_timestamp <= '2022-12-01'
ORDER BY s.sales_amount DESC
LIMIT 100
SELECT g.total_score
, s.result_url
, *
FROM bi_analytics.bronze.hevo_grades g
JOIN bi_analytics.bronze.hevo_submissions s ON s.id = g.submission_id
JOIN bi_analytics.bronze.hevo_claims c ON c.id = s.claim_id
JOIN bi_analytics.bronze.hevo_bounties b ON b.id = c.bounty_id
-- JOIN bi_analytics.bronze.hevo_campaigns ca ON ca.id = b.campaign_id
WHERE b.created_at >= '2022-10-01'
AND intended_payment_currency = 'RUNE'
ORDER BY b.created_at DESC, g.total_score DESC
SELECT s.*
FROM solana.core.fact_nft_sales s
LEFT JOIN solana.core.dim_labels l
ON l.address = s.mint
WHERE s.block_timestamp >= '2022-08-01'
AND l.address IS NULL
AND sales_amount < 1000
ORDER BY COALESCE(sales_amount, 0) DESC
LIMIT 100
SELECT ca.title
, ca.project_name
, ca.end_date::date AS date
, g.total_score
, *
FROM bi_analytics.bronze.hevo_grades g
JOIN bi_analytics.bronze.hevo_submissions s ON s.id = g.submission_id
JOIN bi_analytics.bronze.hevo_claims c ON c.id = s.claim_id
JOIN bi_analytics.bronze.hevo_bounties b ON b.id = c.bounty_id
-- JOIN bi_analytics.bronze.hevo_campaigns ca ON ca.id = b.campaign_id
WHERE ca.project_name ILIKE '%THOR%'
AND ca.end_date >= '2022-10-01'
ORDER BY ca.end_date, ca.title, g.total_score DESC
SELECT *
FROM bi_analytics.bronze.hevo_bounty_collections
LIMIT 100
SELECT project_name
, COUNT(1) AS n
FROM bi_analytics.bronze.hevo_campaigns ca
GROUP BY 1
ORDER BY 2 DESC
SELECT *
FROM bi_analytics.bronze.hevo_campaigns ca
WHERE project_name = 'THORChain'
ORDER BY ca.end_date, ca.title DESC

426
apps/solana/solarscored/server.R
View File

@ -1,351 +1,175 @@
function(input, output, session) {
plotly.style <- list(
fig_bgcolor = 'rgb(255, 255, 255)',
plot_bgcolor = 'rgba(0, 0, 0, 0)',
paper_bgcolor = 'rgba(0, 0, 0, 0)',
font = list(
color = '#FFF', family = 'Roboto Mono')
)
output$useraddy <- renderUI({
textInput("addy", "SOURCE ADDRESS:",
placeholder = "paste in an address or click random")
})
output$inputaddy <- renderUI({
url.addy <- parseQueryString(session$clientData$url_search)
if(length(url.addy) > 0) {
default.addy <- names(url.addy)[1]
userRecord <- reactive({
if(!is.null(input$addy)) {
if(nchar(input$addy) > 0) {
df[user_address == input$addy]
} else {
default.addy <- NA
empty.df
}
if(is.na(default.addy)) {
textInput(
inputId = 'addy'
, label = NULL
, width = '100%'
, placeholder = 'a Solana address'
)
} else {
textInput(
inputId = 'addy'
, label = NULL
, width = '100%'
, value = default.addy
)
empty.df
}
})
# observeEvent(input$address, {
# if(!is.null(input$address)) {
# if(substr(input$address, 1, 5) == 'terra') {
# updateTextInput(session, 'addy', value = input$address)
# }
# }
# })
observeEvent(input$addy, {
if(!is.null(input$address)) {
if(input$addy == input$address) {
updateActionButton(session = session, inputId = 'connect', label = 'Disconnect')
svgColored <- reactive({
new.svg <- svgdata
if(!is.null(input$addy)) {
if(nchar(input$addy) > 0) {
new.style <- c()
for(i in 1:7) {
tmp <- userRecord()[[categories[i]]]
new.style <- c(new.style, c(rep(1, tmp), rep(0, (3-tmp))))
}
for(i in 1:21) {
new.svg <- str_replace(string = new.svg, pattern = "%s", replacement = ifelse(new.style[i] == 1, "100%", "20%"))
}
} else {
updateActionButton(session = session, inputId = 'connect', label = 'Connect Wallet')
for(i in 1:21) {
new.svg <- str_replace(string = new.svg, pattern = "%s", replacement = base.style[i])
}
}
})
inRangeScores <- reactive(
df[ total_score >= input$scorethreshold[1] & total_score <= input$scorethreshold[2]]
)
inRangeMetricScores <- reactive(
df[ total_score >= input$scorethreshold[1] & total_score <= input$scorethreshold[2]]
# metric.score.data[`Total Score` >= input$scorethreshold[1] & `Total Score` <= input$scorethreshold[2]]
)
output$title_sentence <- renderText({
paste0('Rankings for ',
# format(n.scores, big.mark = ','),
' Solana addresses scored across 21 metrics in 7 categories.')
})
is.blank <- function(x, false.triggers=FALSE){
if(is.function(x)) return(FALSE) # Some of the tests below trigger
# warnings when used on functions
return(
is.null(x) || # Actually this line is unnecessary since
length(x) == 0 || # length(NULL) = 0, but I like to be clear
all(is.na(x)) ||
all(x=="") ||
(false.triggers && all(!x))
)
}
observeEvent(input$wallet_address, {
print('observeEvent input$wallet_address')
print(input$wallet_address)
})
output$your_address <- renderText({
val <- 'Wallet not connected'
print('output$your_address input$wallet_address')
print(input$wallet_address)
if (!is.blank(input$wallet_address)) {
val <- paste0('Your address is ', input$wallet_address)
}
paste0(val)
})
output$scoreplot <- renderPlotly({
plot.data <- df %>% group_by(total_score) %>% summarize( N=n() ) %>% as.data.table()
plot.data <- plot.data[ total_score >= input$scorethreshold[1] & total_score <= input$scorethreshold[2]]
plot.data[, color_group := ifelse(total_score >= input$scorethreshold[1] & total_score <= input$scorethreshold[2], 'in', 'out')]
fig <- plot_ly(
data = plot.data[total_score > 0]
, x = ~total_score
, y = ~N
, color = ~color_group
, type = 'bar'
, colors = c('#5494F8', '#dddddd')
)
# fig <- fig %>% add_annotations(
# x=28,
# y=80000,
# xref = 'x',
# yref = 'y',
# text = paste0(format(nrow(df), big.mark=',', scientific=FALSE), ' <br>addresses selected'),
# xanchor = 'right',
# showarrow = F,
# font = list(size = 20, color = '#5494F8', family = 'Roboto Mono')
# )
fig <- fig %>% layout(
xaxis = list(
title = ''
, showgrid = FALSE
, fixedrange = TRUE
, color = '#C4CDD5'
)
, yaxis = list(
title = ''
, showticklabels = TRUE
, showgrid = TRUE
, fixedrange = TRUE
, gridwidth = 0.5
, color = '#C4CDD5'
, gridcolor = '#202933'
)
, showlegend = FALSE
, plot_bgcolor = plotly.style$plot_bgcolor
, paper_bgcolor = plotly.style$paper_bgcolor
) %>%
plotly::config(displayModeBar = FALSE) %>%
plotly::config(modeBarButtonsToRemove = c('zoomIn2d', 'zoomOut2d'))
fig
})
# lapply(unique(score_criteria$category), function(tmp.category) {
# cat.name.fix <- tolower(gsub(x = tmp.category, pattern = ' ', '_', fixed = TRUE))
# output[[cat.name.fix]] <- renderText({
# if(is.null(input$addy) | input$addy == '') {
# paste0('avg score: ', sprintf('%.1f', round(mean(inRangeScores()[[tmp.category]]), 1)))
# } else {
# paste0('score: ',
# scores[address == input$addy][[tmp.category]],
# ' (avg ',
# sprintf('%.1f', round(mean(inRangeScores()[[tmp.category]]), 1)),
# ')')
# }
# })
# })
lapply(score_criteria$metric_name, function(metric) {
output[[metric]] <- renderText({
paste0(format(sum(inRangeMetricScores()[[metric]] > 0), big.mark=',', scientific=FALSE), ' addresses')
})
})
# now change the colors of the score boxes:
observeEvent(input$addy, {
lapply(score_criteria$metric_name, function(tmp.metric) {
# change.class <- metric.score.data[address == input$addy][[tmp.metric]] > 0
change.class <- df[user_address == input$addy][[tmp.metric]] > 0
if(length(change.class) == 0) change.class <- FALSE
toggleClass(id = paste0(tmp.metric, '_div'),
class = 'bright',
condition = change.class)
toggleClass(id = paste0(tmp.metric, '_c'),
class = 'showey',
condition = change.class)
})
})
output$user_score <- renderText({
if(!length(input$addy)) {
paste0(0, '/42')
} else {
cur <- df[ (user_address == input$addy) ]
score <- ifelse(nrow(cur) > 0, cur$total_score[1], 0)
paste0(score, '/42')
for(i in 1:21) {
new.svg <- str_replace(string = new.svg, pattern = "%s", replacement = base.style[i])
}
}
new.svg
}
)
output$svgout <- renderUI({
HTML(svgColored())
})
observeEvent(input$randomaddy, {
updateTextInput(session, "addy", value = sample(df$user_address, 1))
}, suspended = F)
output$vs_mean <- renderText({paste0('vs. Mean Score of ', round(mean(inRangeScores()[['total_score']]), 1))})
getTableData <- reactive(inRangeScores()[order(-total_score)][1:500])
output$cat_scores_table <- renderReactable({
reactable(
getTableData()[, list(
address = paste0(substr(user_address, 1, 12), '...')
, score = total_score
, longevity = longevity
, activity = activity
, governor = governor
, bridgor = bridgor
, staker = staker
, explorer = explorer
)]
, onClick = 'select'
, selection = 'single'
, rowStyle = JS(
"function(rowInfo) {
if (rowInfo && rowInfo.selected) {
return { backgroundColor: '#172852' }
}
}"
), defaultColDef = colDef( headerStyle = list(background = '#10151A') )
, borderless = TRUE
, outlined = FALSE
, columns = list(
address = colDef(name = 'Address', minWidth = 165, align = 'left'),
score = colDef(name = 'Score', align = 'right'),
longevity = colDef(name = 'longevity', align = 'right'),
activity = colDef(name = 'activity.', align = 'right'),
governor = colDef(name = 'governor.', align = 'right'),
bridgor = colDef(name = 'bridgor', align = 'right'),
staker = colDef(name = 'staker', align = 'right'),
explorer = colDef(name = 'explorer', align = 'right')
)
output$outputslider <- renderUI({
sliderTextInput(
inputId = "scoreslider",
label = NULL,
choices = 1:21,
selected = c(5, 15),
grid = TRUE,
width = "100%"
)
})
#observing the row selected in the table
# to change the input address
tableSelected <- reactive(getReactableState('cat_scores_table', 'selected', session))
output$scorehist <- renderPlotly({
output$selected <- renderPrint({
print(getTableData()[tableSelected()]$address)
})
observeEvent(tableSelected(), {
new.addy <- getTableData()[tableSelected()]$address
if(length(new.addy) == 1) {
updateTextInput(session, 'addy', value = new.addy)
if(length(input$scoreslider) > 0) {
active.scores <- input$scoreslider[1]:input$scoreslider[2]
} else {
active.scores <- 5:15
}
to.plot <- rbind(
data.table(total_score = 1:5, N = 0),
df[, .N, by = total_score][order(total_score)],
data.table(total_score = 19:21, N = 0)
)
to.plot[, bar_color := ifelse(total_score %in% active.scores, bar.plot.colors[1], bar.plot.colors[2])]
plot_ly(to.plot,
x = ~total_score, y = ~N, type = 'bar',
marker = list(color = to.plot$bar_color)) %>%
layout(bargap = 0.2,
xaxis = list(title = "",
showticklabels = FALSE,
showgrid = FALSE,
fixedrange = TRUE),
yaxis = list(title = "",
showticklabels = FALSE,
showgrid = FALSE,
fixedrange = TRUE,
type = "log"),
showlegend = FALSE,
margin = list(l=6, r=6, b=0, t=0, autoexpand = FALSE),
plot_bgcolor = "transparent",
paper_bgcolor = "transparent") %>%
config(displayModeBar = FALSE,
showLink = FALSE)
})
output$bdnldscores <- renderUI({
tmp.label <- paste("Get Scores for ",
format(nrow(df[total_score >= input$scoreslider[1] & total_score <= input$scoreslider[2]]), big.mark = ","),
" Users")
downloadButton(outputId = 'download_scores_metrics',
label = tmp.label,
icon = NULL)
observeEvent(input$clearaddy, {
updateTextInput(session, 'addy', value = '')
})
output$download_scores_metrics <- downloadHandler(
filename = function() {
paste('scores_', input$scorethreshold[1], '_to_', input$scorethreshold[2], '_', Sys.Date(), '.csv', sep='')
paste('scores_', input$scoreslider[1], '_to_', input$scoreslider[2], '_', Sys.Date(), '.csv', sep='')
},
content = function(file) {
to.download <- merge(inRangeScores(), inRangeMetricScores(), by = c('address', 'Total Score'))
to.download <- df[total_score >= input$scoreslider[1] & total_score <= input$scoreslider[2]]
write.csv(to.download, file)
}
)
addTooltip(session, id = 'net_from_shuttle_cex',
title = paste0(
'Received more from Bridges or CEXs than sent (or 0 sent) in the last 90 days', '<hr>',
'Difficulty: Easier', '<br>',
'Points Value: 1', '<hr>',
'Data Metric Name: net_from_shuttle_cex'),
placement = 'bottom', trigger = 'hover',
options = NULL)
# table with links to queries:
output$metric_defs <- renderReactable({
reactable(score_criteria[, list(score_name, metric_name, points, score_description, velocity_query)],
defaultColDef = colDef(
#align = 'center',
headerStyle = list(background = '#10151A')
),
defaultPageSize = 15,
pagination = FALSE,
borderless = TRUE,
outlined = FALSE,
#maxWidth = 100,
columns = list(
score_name = colDef(name = 'Score Name', maxWidth = 150, align = 'left'),
metric_name = colDef(name = 'Metric Name', align = 'left'),
points = colDef(name = 'Points', maxWidth = 75, align = 'right'),
score_description = colDef(name = 'Score Description', align = 'left'),
velocity_query = colDef(name = 'Query', maxWidth = 75, align = 'left', cell = function(velocity_query) {
# Render as a link
url <- sprintf(paste0(velocity_query))
htmltools::tags$a(href = url, target = '_blank', 'link', onclick = "mixpanel.track('ae-click-velocity-link')")
}))
)
output$userscore <- renderText({
userRecord()$total_score
})
output$make_toggle_button <- renderUI({
actionButton(
inputId = 'toggle_button',
label = 'Show Table')
output$useractivity <- renderText({
round(userRecord()[["activity_value"]])
})
output$usernfts <- renderText({
round(userRecord()[["nft_value"]])
})
output$userlongevity <- renderText({
round(userRecord()[["longevity_value"]])
})
output$uservariety <- renderText({
round(userRecord()[["variety_value"]])
})
output$userstaking <- renderText({
round(userRecord()[["staking_value"]])
})
output$userbridge <- renderText({
round(userRecord()[["bridge_value"]])
})
output$usergovernance <- renderText({
round(userRecord()[["governance_value"]])
})
observeEvent(input$toggle_button, {
toggleElement(
id = 'metric_defs'
)
if(input$toggle_button[1] %% 2 == 0) {
# change to collapse
updateActionButton(inputId = 'toggle_button', label = 'Hide Table')
} else {
# change to expand
updateActionButton(inputId = 'toggle_button', label = 'Show Table')
}
})
output$download_all_data <- downloadHandler(
filename <- function() {
#'all_data.csv'
ifelse(Sys.info()[['user']] == 'rstudio-connect',
'/rstudio-data/lunatics_all_data.csv',
'all_data.csv')
},
content <- function(file) {
file.copy('all_data.csv', file)
},
contentType = 'csv'
)
}

483
apps/solana/solarscored/ui.R
View File

@ -1,355 +1,164 @@
# SolarScored leaderboard
# #useraddy .form-group {
# display: table-row;
# }
#
# #addy-label {
# padding-right: 30px;
# }
fluidPage(
title = 'SolarScored',
tags$head(
tags$link(rel = 'stylesheet', type = 'text/css', href = 'shiny.css'),
tags$link(rel = 'stylesheet', href = 'https://fonts.googleapis.com/css?family=Roboto+Mono'),
tags$link(rel = 'stylesheet', href = 'https://fonts.googleapis.com/css?family=Inter')
tags$link(rel = "stylesheet", type = "text/css", href = "shiny.css"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Orbitron"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Exo+2"),
tags$link(rel = "stylesheet", href = "https://fonts.googleapis.com/css?family=Roboto+Mono"),
tags$link(rel = "icon", href = "flipside.svg")
),
tags$style(
type='text/css',
'.shiny-output-error { visibility: hidden; size: 0.1em}',
'.shiny-output-error:before { visibility: hidden; size: 0.1em}'
),
# LINK to mixpanel
tags$head(tags$script(src = 'mixpanel.js')),
# SUPPRESS loading warnings/errors
withTags({
header(
class='top-banner',
section(
a(
class='fs-logo'
, href='https://www.flipsidecrypto.com'
, img(src = 'newlogo.svg')
, onclick = "mixpanel.track('lts-click-logo-icon')"
)
, section(
class='socials'
, a(class='twitter', target = '_blank', href='https://twitter.com/flipsidecrypto', 'Twitter', onclick = "mixpanel.track('lst-click-twitter-icon')")
, a(class='linkedin', target = '_blank', href='https://www.linkedin.com/company/flipside-crypto', 'LinkedIn', onclick = "mixpanel.track('lts-click-linkedin-icon')")
, a(class='discord', target = '_blank', href='https://flipsidecrypto.com/discord', 'Discord', onclick = "mixpanel.track('lts-click-discord-icon')")
, a(href='https://app.flipsidecrypto.com/auth/signup/velocity', target = '_blank', 'Sign Up', onclick = "mixpanel.track('lts-click-signup-icon')")
)
)
)
}),
useShinyjs(),
br(),
fluidRow(class = 'description', textOutput('your_address')),
solAttestR::SolWalletHandler("wallet_address"),
fluidRow(class = 'titles', 'SolarScored Rankings'),
fluidRow(class = 'description', 'Version 0.1 of Creating an LTV metric on Solana. Can be used to quantify user value and behavior for the Foundation or projects looking to airdrop or target users.'),
br(),
fluidRow(class = 'description', textOutput('title_sentence')),
br(),
fluidRow(
class = 'wrapper',
column(
5,
fluidRow(class = 'choose', 'Select a score range (0 to 42) to subset addresses'),
fluidRow(
div(
style = 'margin: auto; width: 90%;'
, sliderInput(inputId = 'scorethreshold', label = NULL, min = 1, max = 42, value = c(1, 42), width = '100%')
)
)
, fluidRow(
a(
downloadButton(
'download_scores_metrics'
, label = 'Download Scores & Metrics'
, icon = icon('arrow-down')
, onclick = "mixpanel.track('lts-download-scores')")
)
)
)
, column(
7
, plotlyOutput('scoreplot', height = '200px')
)
), # close wrapper
br(),
chooseSliderSkin("Round"),
fluidRow(
class = 'wrapper'
, fluidRow(
column(
7
, div(class = 'toppad', 'Enter an Address or pick one from the Leaderboard')
, uiOutput('inputaddy')
, column(
5
, div(class = 'userscore', 'Score'
, br()
, textOutput('user_score')
, textOutput('vs_mean'))
)
)
)
, br()
, 'Leaderboard Summary'
, fluidRow(
class = 'doesscroll'
, tags$table(
tags$tr(
tags$th(
'LONGEVITY'
, div(class = 'catscore', uiOutput('activity'))
)
, tags$th(
'ACTIVITY'
, div(class = 'catscore', uiOutput('governance'))
)
, tags$th(
'GOVERNANCE'
, div(class = 'catscore', uiOutput('degeneracy'))
)
, tags$th(
'BRIDGING'
, div(class = 'catscore', uiOutput('cash_out_vs_hodl'))
)
, tags$th(
'STAKING'
, div(class = 'catscore', uiOutput('airdrops'))
)
, tags$th(
'EXPLORING'
, div(class = 'catscore', uiOutput('explorer'))
)
, tags$th(
'NFTS'
, div(class = 'catscore', uiOutput('nfts'))
)
fluidRow(class = "titlerow",
column(9, class = "title", img(src = "solarscored-logo.svg", width = '480px')),
column(3,
div(id = "icons",
div(class = "aboutlinks",
a(id = 'fork',
href = "https://github.com/FlipsideCrypto/user_metrics/tree/main/apps/solana/solarscored",
img(src = "github.svg", width = "30px"),
target = "_blank")),
bsTooltip(id = "fork",
title = "Fork this App",
placement = "bottom", trigger = "hover"),
div(class = "aboutlinks",
a(id = "flippy",
href = "https://next.flipsidecrypto.xyz/",
img(src = "flipside.svg", width = "30px"),
target = "_blank")),
bsTooltip(id = "flippy",
title = "Get the Data",
placement = "bottom", trigger = "hover"),
div(class = "aboutlinks",
a(id = "solana", href = "https://solana.com",
img(src = "solana.svg", width = "30px"),
target = "_blank")),
bsTooltip(id = "solana",
title = "Solana",
placement = "bottom", trigger = "hover")
))),
fluidRow(class = "appbody",
fluidRow(class = "dashmid",
column(7,
div(class = "addybuttons",
uiOutput("useraddy"),
actionButton(inputId = "randomaddy", label = img(src = "random.svg", height = "26")),
),
tags$tr(
tags$td(
id = 'longevity_1_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Newbie')
, div(class = 'rightDiv', div(class='hidey', id = 'longevity_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('longevity_1'))
)
, tags$td(
id = 'activity_1_div'
, div(
class='outerDiv'
, div(
class = 'leftDiv'
, 'Occasional'
)
, div(class = 'rightDiv', div(class='hidey', id = 'activity_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('activity_1'))
)
, tags$td(
id = 'governor_1_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Gov Degen')
, div(class = 'rightDiv', div(class='hidey', id = 'governor_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('governor_1'))
div(id = "wheelpart",
uiOutput("svgout") %>%
withSpinner(hide.ui = FALSE, color = "#9945FF", size = 2)),
a(id = "pic",
capture::capture(
selector = "svg",
filename = "mysolarscore.png",
options = list(bgcolor = "#FFF"),
#scale = 2,
img(src = "camera.svg", height = "20"),
title = "Download the Circle")),
bsTooltip(id = "pic",
title = "Download the Wheel",
placement = "top", trigger = "hover"),
),
tags$td(id = 'bridgor_1_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Bridgor'),
div(class = 'rightDiv', div(class='hidey', id = 'bridgor_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('bridgor_1'))),
tags$td(id = 'staker_1_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Stakor'),
div(class = 'rightDiv', div(class='hidey', id = 'staker_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('staker_1'))),
tags$td(id = 'explorer_1_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Exploror'),
div(class = 'rightDiv', div(class='hidey', id = 'explorer_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('explorer_1'))),
tags$td(id = 'nfts_1_div',
div(class='outerDiv',
div(class = 'leftDiv', 'I dabble'),
div(class = 'rightDiv', div(class='hidey', id = 'nfts_1_c', img(src = 'badge_1.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('nfts_1')))
column(5,
div(id = "leftbox",
div(class = "boxtitle", "Address Metrics"),
div(id = "totalscore",
div(class = "score", textOutput("userscore")),
div(class = "yourscore", "SolarScore")),
bsTooltip(id = "totalscore",
title = "Your total score out of a possible 21 points, up to 3 for each of the 7 categories.",
placement = "top", trigger = "hover"),
fluidRow(class = "metricrow",
div(class = "metricholder", id = "boxuseractivity",
div(class = "metric", textOutput("useractivity")),
div(class = "metricname", "Activity"),
bsTooltip(id = "boxuseractivity",
title = "# transactions in the last 90 days.",
placement = "top", trigger = "hover")),
div(class = "metricholder", id = "boxusernfts",
div(class = "metric", textOutput("usernfts")),
div(class = "metricname", "NFTs"),
bsTooltip(id = "boxusernfts",
title = "90 day buy + mint volume (SOL)",
placement = "top", trigger = "hover")),
div(class = "metricholder", id = "boxusergovernance",
div(class = "metric", textOutput("usergovernance")),
div(class = "metricname", "Gov"),
bsTooltip(id = "boxusergovernance",
title = "# governance votes in the last 90 days",
placement = "top", trigger = "hover")),
div(class = "metricholder", id = "boxuservariety",
div(class = "metric", textOutput("uservariety")),
div(class = "metricname", "Variety"),
bsTooltip(id = "boxuservariety",
title = "# programs interacted with in the last 90 days",
placement = "top", trigger = "hover"))
),
tags$tr(
tags$td(
id = 'longevity_2_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Experienced')
, div(class = 'rightDiv', div(class='hidey', id = 'longevity_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('longevity_2'))
)
, tags$td(
id = 'activity_2_div'
, div(
class='outerDiv'
, div(
class = 'leftDiv'
, 'Active'
)
, div(class = 'rightDiv', div(class='hidey', id = 'activity_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('activity_2'))
)
, tags$td(
id = 'governor_2_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Solana Activist')
, div(class = 'rightDiv', div(class='hidey', id = 'governor_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('governor_2'))
fluidRow(class = "metricrow",
div(class = "metricholder2", id = "boxuserstaking",
div(class = "metric", textOutput("userstaking")),
div(class = "metricname", "Staking"),
bsTooltip(id = "boxuserstaking",
title = "SOL currently staked",
placement = "top", trigger = "hover")),
div(class = "metricholder2", id = "boxuserlongevity",
div(class = "metric", textOutput("userlongevity")),
div(class = "metricname", "Longevity"),
bsTooltip(id = "boxuserlongevity",
title = "# calendar months with a transaction in the last 90 days",
placement = "top", trigger = "hover")),
div(class = "metricholder2", id = "boxuserbridge",
div(class = "metric", textOutput("userbridge")),
div(class = "metricname", "Bridging"),
bsTooltip(id = "boxuserbridge",
title = "# times funds bridged onto Solana in the last 90 days",
placement = "top", trigger = "hover"))
),
tags$td(id = 'bridgor_2_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Bridgooor'),
div(class = 'rightDiv', div(class='hidey', id = 'bridgor_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('bridgor_2'))),
tags$td(id = 'staker_2_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Stakooor'),
div(class = 'rightDiv', div(class='hidey', id = 'staker_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('staker_2'))),
tags$td(id = 'explorer_2_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Explorooor'),
div(class = 'rightDiv', div(class='hidey', id = 'explorer_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('explorer_2'))),
tags$td(id = 'nfts_2_div',
div(class='outerDiv',
div(class = 'leftDiv', 'NFT Enjoyooor'),
div(class = 'rightDiv', div(class='hidey', id = 'nfts_2_c', img(src = 'badge_2.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('nfts_2')))
div(id = "hovernote", "Hover over Metric for Details"),
),
tags$tr(
tags$td(
id = 'longevity_3_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Grizzled Veteran')
, div(class = 'rightDiv', div(class='hidey', id = 'longevity_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('longevity_3'))
)
, tags$td(
id = 'activity_3_div'
, div(
class='outerDiv'
, div(
class = 'leftDiv'
, 'Unhinged'
)
, div(class = 'rightDiv', div(class='hidey', id = 'activity_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('activity_3'))
)
, tags$td(
id = 'governor_3_div'
, div(
class='outerDiv'
, div(class = 'leftDiv', 'Rock the Vote')
, div(class = 'rightDiv', div(class='hidey', id = 'governor_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))
)
, br()
, div(class='small-text', textOutput('governor_3'))
),
tags$td(id = 'bridgor_3_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Bridgooooor'),
div(class = 'rightDiv', div(class='hidey', id = 'bridgor_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('bridgor_3'))),
tags$td(id = 'staker_3_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Stakooooor'),
div(class = 'rightDiv', div(class='hidey', id = 'staker_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('staker_3'))),
tags$td(id = 'explorer_3_div',
div(class='outerDiv',
div(class = 'leftDiv', 'Explorooooor'),
div(class = 'rightDiv', div(class='hidey', id = 'explorer_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('explorer_3'))),
tags$td(id = 'nfts_3_div',
div(class='outerDiv',
div(class = 'leftDiv', 'NFT Whale'),
div(class = 'rightDiv', div(class='hidey', id = 'nfts_3_c', img(src = 'badge_3.svg', width = '20px', height = '20px')))),
br(),
div(class='small-text', textOutput('nfts_3')))
),
) # close table
) # close table row
), # close wrapper
lapply(score_criteria$metric_name, function(i) {
score.info <- score_criteria[metric_name == i]
tmp.title <- paste0(
score.info$score_description, '<hr>',
'Difficulty: ', c('Easier', 'Harder', 'Degen Only')[score.info$points], '<br>',
'Points Value: ', score.info$points, '<hr>',
'Data Metric Name: ', score.info$metric_name)
shinyBS::bsTooltip(id = i,
title = tmp.title)
}),
br(),
fluidRow(class = 'wrapper',
div(class = 'boldwhite', 'Leaderboard for Selected Addresses'), br(),
div(class = 'subtitle', 'Click a row to explore an address. Click a column to sort by that Category.'),
reactableOutput('cat_scores_table'), br(),
fluidRow(class = 'downloadrow', a(downloadButton('download_all_data',
label = 'Download Raw Data by Address (~175MB)', icon = icon('arrow-down'),
onclick = "mixpanel.track('lts-download-all')")))),
br(),br(),
fluidRow(class = 'wrapper',
div(class = 'boldwhite', 'More About this App'),
br(),
div(class = 'disclaimer', "This app was created to showcase 21 behaviors that we associate with positive contribution to the Solana ecosystem.
These are certainly not the only ways that an address can contribute to the ecosystem, so we encourage you to DYOR. We've made all of
our data available, ether through the download links above, or if you want to go deeper, we have linked to every query used to create
this leadearboard in the table below. Note that there are ~6M addresses in the full data file as it includes addresses that scored 0 but still
had enough activity to show up in the calculation of at least one metric. The data refreshes once every two hours."),
br(),
div(class = 'disclaimer', 'We love geeking out on methodology and data, so if you have questions or ideas please visit us on our
discord. Thanks for stopping by SolarScored!'),
br(),
div(class = 'subtitle', 'Metric Details + Query Links'),
reactableOutput('metric_defs')
),
br(), br(), br(), br()
) # close fluid page
div(id = "botrightbox",
div(class = "boxtitle", "Download All Scores"),
div(id = "indent", "Select Addresses by Score:"),
div(id = "sliderbox",
plotlyOutput("scorehist", height = "100px"),
uiOutput("outputslider"),
uiOutput("bdnldscores")))
) #close left column box
) # close dashmid
#fluidRow(class = "dashbottom", "this is the bottom!")
), #close appbody
br(), br(), br()
) # close app

8255
apps/solana/solarscored/update_data.R
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File diff suppressed because it is too large Load Diff

360
apps/solana/solarscored/update_data_solarscored.Rmd
View File

@ -39,76 +39,74 @@ library(odbc)
user <- Sys.info()[['user']]
isRstudio <- user == 'rstudio-connect'
switch(
isRstudio
, source("/home/data-science/data_science/util/util_functions.R")
, source("~/data_science/util/util_functions.R")
)
if(isRstudio) {
source("/home/data-science/data_science/util/util_functions.R")
} else {
source("~/data_science/util/util_functions.R")
}
query <- "
SELECT signers[0]::string AS user_address
, COUNT(DISTINCT DATE_TRUNC('month', block_timestamp)) AS value
long.act.query <- "
WITH months AS (SELECT
signers[0]::string AS user_address,
count(tx_id) AS n_txn,
DATE_TRUNC('month', block_timestamp) AS month
FROM solana.core.fact_transactions
GROUP BY 1
WHERE
block_timestamp > current_date - 90
AND
user_address NOT IN (SELECT address FROM solana.core.dim_labels)
GROUP BY user_address, month
)
SELECT
user_address, sum(n_txn) AS activity_value, count(month) AS longevity_value
FROM months
GROUP BY user_address
"
longevity <- QuerySnowflake(query)
colnames(longevity)[2] <- 'value'
func <- function(x) {
if (x < 2) {return(0)}
if (x < 6) {return(1)}
if (x < 12) {return(2)}
sol.long.act <- QuerySnowflake(long.act.query)
long.func <- function(x) {
if (x < 1) {return(0)}
if (x < 2) {return(1)}
if (x < 3) {return(2)}
return(3)
}
longevity[, level := sapply(value, func) ]
longevity[, metric := 'n_months_active' ]
longevity <- longevity[, list(metric, user_address, value, level) ]
print(longevity %>% group_by(level) %>% summarize(n=n()) %>% as.data.table())
query <- "
SELECT signers[0]::string AS user_address
, COUNT(1) AS value
FROM solana.core.fact_transactions
WHERE block_timestamp >= CURRENT_DATE - 90
GROUP BY 1
"
activity <- QuerySnowflake(query)
colnames(activity)[2] <- 'value'
func <- function(x) {
if (x < 10) {return(0)}
if (x < 100) {return(1)}
if (x < 1000) {return(2)}
activity.func <- function(x) {
if (x < 5) {return(0)}
if (x < 10) {return(1)}
if (x < 20) {return(2)}
return(3)
}
activity[, level := sapply(value, func) ]
activity[, metric := 'n_user_tx' ]
activity <- activity[, list(metric, user_address, value, level) ]
print(activity %>% group_by(level) %>% summarize(n=n()) %>% as.data.table())
query <- "
sol.long.act[, longevity := sapply(longevity_value, long.func) ]
sol.long.act[, activity := sapply(activity_value, activity.func) ]
# GOVERNANCE
gov.query <- "
SELECT voter AS user_address
, COUNT(1) AS value
, COUNT(DISTINCT program_name) AS n_user_votes_programs
, COUNT(1) AS governance_value
--, COUNT(DISTINCT program_name) AS governance_value
FROM solana.core.fact_proposal_votes
GROUP BY 1
WHERE
block_timestamp > current_date - 180
AND
user_address NOT IN (SELECT address FROM solana.core.dim_labels)
GROUP BY user_address
ORDER BY 2 DESC
"
governor <- QuerySnowflake(query)
colnames(governor)[1] <- 'user_address'
colnames(governor)[2] <- 'value'
func <- function(x) {
if (x < 1) {return(0)}
if (x < 10) {return(1)}
if (x < 100) {return(2)}
sol.gov <- QuerySnowflake(gov.query)
gov.func <- function(x) {
if (x < 2) {return(1)}
if (x < 3) {return(2)}
return(3)
}
governor[, level := sapply(value, func) ]
governor[, metric := 'n_user_votes' ]
governor <- governor[, list(metric, user_address, value, level) ]
print(governor %>% group_by(level) %>% summarize(n=n()) %>% as.data.table())
sol.gov[, governance := sapply(governance_value, gov.func) ]
# Bridgor - How many times are they bridging assets onto Solana (from a bridge or CEX)?
query <- "
bridge.query <- "
WITH tx AS (
SELECT DISTINCT tx_id
FROM solana.core.fact_events e
@ -117,9 +115,8 @@ query <- "
AND l.label_subtype = 'bridge'
WHERE e.block_timestamp >= CURRENT_DATE - 90
)
SELECT tx_to AS user_address
, COUNT(1) AS n_bridge
, SUM(CASE WHEN mint = 'So11111111111111111111111111111111111111112' THEN amount ELSE 0 END) AS value
SELECT tx_to AS user_address, COUNT(1) AS bridge_value
--, SUM(CASE WHEN mint = 'So11111111111111111111111111111111111111112' THEN amount ELSE 0 END) AS value
FROM solana.core.fact_transfers t
LEFT JOIN tx ON tx.tx_id = t.tx_id
LEFT JOIN solana.core.dim_labels l
@ -127,235 +124,140 @@ query <- "
AND (l.label_type = 'cex' OR l.label_subtype = 'bridge' )
WHERE t.block_timestamp >= CURRENT_DATE - 90
AND (tx.tx_id IS NOT NULL OR l.label_type IS NOT NULL)
GROUP BY 1
ORDER BY 3 DESC
"
bridgor <- QuerySnowflake(query)
colnames(bridgor)[1] <- 'user_address'
colnames(bridgor)[3] <- 'value'
func <- function(x) {
AND user_address NOT IN (SELECT address FROM solana.core.dim_labels)
GROUP BY user_address"
sol.bridge <- QuerySnowflake(bridge.query)
bridge.func <- function(x) {
if (x < 1) {return(0)}
if (x < 100) {return(1)}
if (x < 1000) {return(2)}
if (x < 2) {return(1)}
if (x < 3) {return(2)}
return(3)
}
bridgor[, level := sapply(value, func) ]
bridgor[, metric := 'bridged_sol' ]
bridgor <- bridgor[, list(metric, user_address, value, level) ]
print( bridgor %>% group_by(level) %>% summarize(n=n()) %>% as.data.table() )
sol.bridge[, bridge := sapply(bridge_value, bridge.func) ]
# Staker - How much SOL have they staked?
query <- "
staking.query <- "
WITH b0 AS (
SELECT *
, ROW_NUMBER() OVER (PARTITION BY stake_authority ORDER BY block_timestamp DESC) AS rn
FROM solana.core.ez_staking_lp_actions
)
SELECT stake_authority AS user_address
, COALESCE(post_tx_staked_balance, 0) * POWER(10, -9) AS value
, COALESCE(post_tx_staked_balance, 0) * POWER(10, -9) AS staking_value
FROM b0
WHERE rn = 1
AND
user_address NOT IN (SELECT address FROM solana.core.dim_labels)
"
staker <- QuerySnowflake(query)
colnames(staker)[2] <- 'value'
staker <- staker[ !is.na(value) ]
func <- function(x) {
sol.staking <- QuerySnowflake(staking.query)
staking.func <- function(x) {
if (x < 1) {return(0)}
if (x < 100) {return(1)}
if (x < 1000) {return(2)}
if (x < 5) {return(1)}
if (x < 15) {return(2)}
return(3)
}
staker[, level := sapply(value, func) ]
staker[, metric := 'staked_sol' ]
staker <- staker[, list(metric, user_address, value, level) ]
print( staker %>% group_by(level) %>% summarize(n=n()) %>% as.data.table() )
sol.staking[, staking := sapply(staking_value, staking.func) ]
# explorer
query <- "
WITH signers AS (
SELECT tx_id
, signers[0]::string AS user_address
FROM solana.core.fact_transactions
WHERE block_timestamp >= CURRENT_DATE - 90
GROUP BY 1, 2
)
SELECT user_address
, COUNT(DISTINCT COALESCE(l.label, e.program_id)) AS value
FROM solana.core.fact_events e
JOIN signers s ON s.tx_id = e.tx_id
LEFT JOIN solana.core.dim_labels l
ON l.address = e.program_id
WHERE e.block_timestamp >= CURRENT_DATE - 90
GROUP BY 1
# variety
variety.query <- "
select
signers[0]::string AS user_address,
count(distinct(program_id)) AS variety_value
from SOLANA.CORE.FACT_EVENTS
where block_timestamp > current_date - 90
AND user_address NOT IN (SELECT address FROM solana.core.dim_labels)
group by user_address
"
explorer <- QuerySnowflake(query)
colnames(explorer)[2] <- 'value'
func <- function(x) {
sol.variety <- QuerySnowflake(variety.query)
summary(sol.variety$n_programs)
var.func <- function(x) {
if (x < 1) {return(0)}
if (x < 10) {return(1)}
if (x < 25) {return(2)}
if (x < 5) {return(1)}
if (x < 10) {return(2)}
return(3)
}
explorer[, level := sapply(value, func) ]
explorer[, metric := 'n_unique_programs' ]
explorer <- explorer[, list(metric, user_address, value, level) ]
print( explorer %>% group_by(level) %>% summarize(n=n()) %>% as.data.table() )
sol.variety[, variety := sapply(variety_value, var.func) ]
# nfts
query <- "
mints.query <- "
WITH buys AS (
SELECT purchaser AS user_address
, SUM(sales_amount) AS buy_volume
FROM solana.core.fact_nft_sales
WHERE block_timestamp >= CURRENT_DATE - 180
AND succeeded
GROUP BY 1
), sells AS (
SELECT seller AS user_address
, SUM(sales_amount) AS sell_volume
FROM solana.core.fact_nft_sales
WHERE block_timestamp >= CURRENT_DATE - 180
AND succeeded
GROUP BY 1
WHERE block_timestamp >= CURRENT_DATE - 90
AND
succeeded = TRUE
AND
user_address NOT IN (SELECT address FROM solana.core.dim_labels)
GROUP BY user_address
), mints AS (
SELECT purchaser AS user_address
, SUM(mint_price) AS mint_volume
FROM solana.core.fact_nft_mints
WHERE block_timestamp >= CURRENT_DATE - 180
WHERE block_timestamp >= CURRENT_DATE - 90
AND succeeded
AND mint_currency = 'So11111111111111111111111111111111111111111'
AND mint_price <= 15
AND user_address NOT IN (SELECT address FROM solana.core.dim_labels)
GROUP BY 1
)
SELECT COALESCE(b.user_address, s.user_address, m.user_address) AS user_address
, COALESCE(b.buy_volume, 0) + COALESCE(s.sell_volume, 0) + COALESCE(m.mint_volume, 0) AS nft_volume
SELECT COALESCE(b.user_address, m.user_address) AS user_address
, COALESCE(b.buy_volume, 0) + COALESCE(m.mint_volume, 0) AS nft_value
FROM buys b
FULL OUTER JOIN sells s
ON s.user_address = b.user_address
--FULL OUTER JOIN sells s
-- ON s.user_address = b.user_address
FULL OUTER JOIN mints m
ON m.user_address = COALESCE(b.user_address, s.user_address)
ON m.user_address = b.user_address
"
mints <- QuerySnowflake(query)
colnames(mints)[2] <- 'value'
func <- function(x) {
sol.nfts <- QuerySnowflake(mints.query)
nfts.func <- function(x) {
if (x < 1) {return(0)}
if (x < 100) {return(1)}
if (x < 1000) {return(2)}
if (x < 5) {return(1)}
if (x < 10) {return(2)}
return(3)
}
mints[, level := sapply(value, func) ]
mints[, metric := 'nft_volume' ]
mints <- mints[, list(metric, user_address, value, level) ]
print( mints %>% group_by(level) %>% summarize(n=n()) %>% as.data.table() )
sol.nfts[, nfts := sapply(nft_value, nfts.func) ]
explorer[ user_address == '9VhsSZ6ni7dZtmKRHE81yAd3UQW1oKu9LNEWRGFMA5wj' ]
explorer[ user_address == 'AoNVE2rKCE2YNA44V7NQt8N73JdPM7b6acZ2vzSpyPyi' ]
head(explorer)
colnames(longevity)
colnames(activity)
colnames(governor)
colnames(bridgor)
colnames(staker)
colnames(explorer)
full.data <- MergeDataFrames(list(sol.long.act,
sol.variety,
sol.nfts,
sol.staking,
sol.gov,
sol.bridge),
by = "user_address", all = TRUE)
ReplaceValues(full.data)
full.data[, total_score := longevity + activity + governance + bridge + staking + variety + nfts ]
a <- longevity[level > 0, list(user_address, level)]
b <- activity[level > 0, list(user_address, level)]
c <- governor[level > 0, list(user_address, level)]
d <- bridgor[level > 0, list(user_address, level)]
e <- staker[level > 0, list(user_address, level)]
f <- explorer[level > 0, list(user_address, level)]
g <- mints[level > 0, list(user_address, level)]
colnames(a) <- c( 'user_address','longevity' )
colnames(b) <- c( 'user_address','activity' )
colnames(c) <- c( 'user_address','governor' )
colnames(d) <- c( 'user_address','bridgor' )
colnames(e) <- c( 'user_address','staker' )
colnames(f) <- c( 'user_address','explorer' )
colnames(g) <- c( 'user_address','nfts' )
#full.data[, .N, by = total_score][order(total_score)]
df_list <- list(a, b, c, d, e, f, g)
df <- Reduce(function(x, y) base::merge(x, y, all=TRUE), df_list) %>% as.data.table()
df[ is.na(df) ] <- 0
# get rid of some behavior that can't be human OR is too low to qualify
full.data <- full.data[total_score > 0]
# longevity
df[, longevity_1 := as.numeric(longevity >= 1) ]
df[, longevity_2 := as.numeric(longevity >= 2) ]
df[, longevity_3 := as.numeric(longevity >= 3) ]
# activity
df[, activity_1 := as.numeric(activity >= 1) ]
df[, activity_2 := as.numeric(activity >= 2) ]
df[, activity_3 := as.numeric(activity >= 3) ]
# governor
df[, governor_1 := as.numeric(governor >= 1) ]
df[, governor_2 := as.numeric(governor >= 2) ]
df[, governor_3 := as.numeric(governor >= 3) ]
# bridgor
df[, bridgor_1 := as.numeric(bridgor >= 1) ]
df[, bridgor_2 := as.numeric(bridgor >= 2) ]
df[, bridgor_3 := as.numeric(bridgor >= 3) ]
# staker
df[, staker_1 := as.numeric(staker >= 1) ]
df[, staker_2 := as.numeric(staker >= 2) ]
df[, staker_3 := as.numeric(staker >= 3) ]
# explorer
df[, explorer_1 := as.numeric(explorer >= 1) ]
df[, explorer_2 := as.numeric(explorer >= 2) ]
df[, explorer_3 := as.numeric(explorer >= 3) ]
# nfts
df[, nfts_1 := as.numeric(nfts >= 1) ]
df[, nfts_2 := as.numeric(nfts >= 2) ]
df[, nfts_3 := as.numeric(nfts >= 3) ]
# if you do avg more than 1 tx per hour over 90 days, you don't
# get a score bc you're not a person you're a computer
# save these addresses to remove them later
full.data <- full.data[activity_value < 24*90]
full.data <- full.data[bridge_value < 24*90]
df[, longevity := longevity_1 + (longevity_2 * 2) + (longevity_3 * 3) ]
df[, activity := activity_1 + (activity_2 * 2) + (activity_3 * 3) ]
df[, governor := governor_1 + (governor_2 * 2) + (governor_3 * 3) ]
df[, bridgor := bridgor_1 + (bridgor_2 * 2) + (bridgor_3 * 3) ]
df[, staker := staker_1 + (staker_2 * 2) + (staker_3 * 3) ]
df[, explorer := explorer_1 + (explorer_2 * 2) + (explorer_3 * 3) ]
df[, nfts := nfts_1 + (nfts_2 * 2) + (nfts_3 * 3) ]
df[, total_score := longevity + activity + governor + bridgor + staker + explorer + nfts ]
# sudo cp ~/score_criteria.csv /rstudio-data
# score_criteria <- read.csv('/Users/kellen/data_science/viz/solarscored/score_criteria.csv') %>% as.data.table()
score_criteria <- read.csv('/rstudio-data/score_criteria.csv') %>% as.data.table()
# head(df)
# df <- rbind(
# longevity
# , activity
# , governor
# , bridgor
# , staker
# , explorer
# )
# g <- df %>% group_by(user_address) %>% summarize(level=sum(level)) %>% as.data.table()
# g <- g[order(-level)]
# print( g %>% group_by(level) %>% summarize(n=n()) %>% as.data.table() )
# head(g)
# g[, metric := 'total_score' ]
# g$value <- g$level
# df <- rbind(df, g)
# df[ metric == 'total_score' ]
df <- full.data
file.location <- ifelse(
isRstudio
, '/rstudio-data/solarscored_data.RData'
, '/Users/kellen/data_science/viz/solarscored/solarscored_data.RData'
, '~/user_metrics/apps/solana/solarscored/solarscored_data.RData'
)
save(
df
, score_criteria
, file = file.location
)
save(df, file = file.location)
```

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Side by Side

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apps/solana/solarscored/www/shiny.css
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@ -1,510 +1,325 @@
/*https://www.figma.com/file/lrdoh9PNj60h2yiwmW6bS0/Calculator-Tools?node-id=615%3A1412*/
body {
background-color: #12161b;
background-attachment: fixed;
background-size: auto 100%;
background-position: center;
padding-left: 10%;
padding-right: 10%;
color: #C4CDD5;
font-family: 'Inter';
font-size: 18px;
font-weight: 400;
font-size: 16px;
background: url('background.svg') no-repeat center center fixed;
-webkit-background-size: cover;
-moz-background-size: cover;
-o-background-size: cover;
background-size: cover;
font-family: 'Exo 2';
}
a {
color: #8880E5;
}
hr {
margin: 0;
background: #10151A;
opacity: 0.5;
border: 1px solid #C4CDD5;
a:hover {
color: #23D1BA;
}
a[title]:hover::after {
content: attr(title);
position: absolute;
top: -100%;
left: 0;
color: orange;
}
.container-fluid {
max-width: 1100px;
margin: 0 auto;
border-radius: 16px;
height: 100%;
margin-top: 50px;
padding: 30px;
background-color: #161d24;
width: 80%;
max-width: 1200px;
margin: auto;
padding-top: 1%;
}
.titles {
font-size: 2em;
font-weight: 700;
color: #5494F8;
line-height: 50.4px;
padding-bottom: 15px;
padding-left: 4%;
}
.description {
color: #ffffff;
font-weight: 500;
padding-left: 4%;
text-align: left;
}
.madewith {
padding-top: 2%;
color: #C4CDD5;
font-size: 0.85em;
padding-left: 4%;
text-align: left;
}
.subtitle {
font-size: 0.85em;
text-align: left;
padding-bottom: 5%;
}
.madewith a {
color: #C4CDD5;
text-decoration: underline;
/* remove the default column padding for the app logo */
.title {
padding-left: 0;
}
.wrapper {
background: #141920;
border-radius: 16px;
border: 0.5px solid #454F5B;
padding: 2% 4% 2% 4%;
}
.wrapper2 {
background: #141920;
opacity: 0.4;
border-radius: 16px;
padding: 0;
}
#last_update {
font-family: Roboto Mono;
font-size: 0.8em;
font-style: italic;
}
.floatinput {
/* upper right icon links */
#icons {
display: flex;
padding-top: 10px;
padding-left: 30px;
}
.appbody {
margin-top: 10px;
}
/* centering the address input + buttons */
.addybuttons {
display: flex;
margin: auto;
align-items: baseline;
vertical-align: bottom;
justify-content: center;
}
.choose {
font-weight: 600;
color: #ffffff;
padding-bottom: 3%;
#useraddy label {
font-family: 'Orbitron';
font-size: 13.6px;
}
.irs-min, .irs-max {
visibility: hidden !important;
#useraddy {
min-width: 400px;
}
.irs-from, .irs-to {
#addy {
border: solid #E2E4F7 2px;
border-radius: 8px;
min-width: 400px;
}
.btn-default, .btn-default:focus {
border: solid #E2E4F7 2px;
border-radius: 8px;
margin-top: auto;
}
.btn-default:hover {
background-color: #E2E4F7;
border: solid #E2E4F7 2px;
}
.btn-capture {
background-color: transparent !important;
color: grey;
border: 0 !important;
opacity: 0.7;
}
.irs-bar {
background: linear-gradient(270deg, #014486 0%, #5494F8 100%) !important;
border-radius: 100px;
}
.irs--shiny .irs-line {
top: 25px;
height: 4px;
background-color: #454F5B;
border-radius: 100px;
}
.irs-handle {
background-color: #ffffff !important;
border: 1px solid #ffffff !important;
.btn-capture:hover {
background-color: transparent !important;
color: grey;
border: 0 !important;
opacity: 1;
}
#download_scores_metrics {
background: #5494F8;
width: 100%;
margin-top: 2%;
padding-top: 12px;
padding-bottom: 12px;
color: white;
vertical-align: middle;
font-size: 0.9em;
}
#download_all_data {
background: #5494F8;
padding-top: 10px;
padding-bottom: 10px;
color: white;
vertical-align: middle;
font-size: 0.9em;
}
.toppad {
padding-top: 3%;
padding-bottom: 15px;
font-weight: 600;
color: #ffffff;
}
.boldwhite {
font-weight: 600;
color: #ffffff;
}
.userscore {
background-color: #212B36;
border-radius: 4px;
padding: 10%;
color: #ffffff;
font-weight: 600;
font-size: 1.05em;
}
#user_score {
font-family: Roboto Mono;
font-size: 1.2em;
font-weight: 300;
padding-top: 3%;
}
#vs_mean {
font-weight: 300;
font-size: 0.9em;
}
.nomargin {
margin: 0;
}
.sidepiece {
width: 1% !important;
}
.col-sm-2 {
width: 19.6% !important;
}
.showey {
visibility: visible !important;
}
.outerDiv{
margin: 0px auto;
}
.leftDiv {
float: left;
text-align: left;
}
.rightDiv {
float: right;
text-align: right;
}
.doesscroll {
overflow-x: scroll;
min-width: 800px;
white-space: nowrap;
}
table {
table-layout: fixed;
width: 100%;
border-collapse:separate;
border-spacing: .5em;
white-space: nowrap;
overflow-x: scroll;
}
th {
background: #212B36;
color: #ffffff;
font-weight: 600;
font-size: .8em;
border-radius: 4px;
padding: 5px;
}
.catscore {
font-family: Roboto Mono;
font-weight: 400;
font-size: 0.85em;
}
.hidey {
visibility: hidden;
}
#n_governance_votes_c, #n_projects_staked_c, #n_airdrop_and_gov_stakes_c, #n_airdrops_claimed_c, #repeat_protocol_claims_c, #n_protocols_claimed_c, #n_dex_trades_c, #n_lp_deposits_c, #n_tokens_used_c, #n_transactions_c, #days_since_last_txn_c, #n_contracts_c, #net_from_shuttle_cex_c, #prop_luna_staked_c, #prop_drops_kept_c {
visibility: hidden;
}
#n_governance_votes, #n_projects_staked, #n_airdrop_and_gov_stakes, #n_airdrops_claimed, #repeat_protocollaims, #n_protocols_claimed, #n_dex_trades, #n_lp_deposits, #n_tokens_used, #n_transactions, #days_since_last_txn, #n_contracts, #net_from_shuttle_cex, #prop_luna_staked, #prop_drops_kept {
font-weight: 400;
}
td {
border: 1px solid #212B36;
border-radius: 4px;
font-weight: 600;
font-size: 0.78em;
padding: 5px;
vertical-align: middle;
}
.bright {
background: #172852;
border: 1px solid #172852;
border-radius: 4px;
color: #ffffff;
}
.about {
font-size: 0.98em;
}
.output {
font-weight: 300;
}
.plotly {
font-family: Roboto Mono !important;
font-style: normal;
font-weight: normal;
font-size: 14px;
line-height: 150%;
display: flex;
align-items: center;
text-align: center;
color: #919EAB !important;
.form-group {
margin-bottom: 0 !important;
}
.form-control {
background: #10151A;
border: 1px solid #97B8F5;
border-radius: 4px;
font-family: Roboto Mono !important;
color: #FFFFFF;
min-height: 42px;
}
.toppart {
background-color: #10151A;
border: 1px solid #97B8F5;
border-radius: 16px;
font-size: 18px;
padding: 4%;
outline:none;
border-color:#97B8F5;
box-shadow:0 0 10px #97B8F5;
}
.aligns {
text-align: right;
}
#event_history {
padding-top: 2%;
font-family: Roboto Mono !important;
font-size: 0.8em;
color: #FFFFFF;
white-space: nowrap;
}
input[type=radio].rt-select-input {
visibility: hidden;
}
.rt-select {
width: 0;
}
.rt-td-select {
width: 0;
}
.rt-page-button-current {
color: #FFF;
}
.rt-thead {
background-color: #10151A;
color: #FFFFFF;
}
.ReactTable {
background-color: #171e25;
color: #C4CDD5;
border: none;
font-size: 0.9em;
margin: -5px;
font-family: Roboto Mono;
}
.rt-th {
border: 0px solid #000000 !important;
padding-top: 15px;
padding-bottom: 15px;
font-weight: 400;
font-family: Inter;
}
.rt-tr {
padding-top: 5px;
padding-bottom: 5px;
}
.rt-pagination {
margin: 0;
background: #171e25;
opacity: 0.5;
border-bottom: 1px solid #C4CDD5;
border-top: 1px solid #C4CDD5;
}
.btn, .btn-default {
color: #FFF;
border: none;
}
.btn:hover {
background-color: #222b36;
}
.downloadrow {
text-align: center;
}
.disclaimer {
font-family: Inter;
font-size: 14px;
font-style: normal;
font-weight: 400;
line-height: 24px;
letter-spacing: 0em;
text-align: left;
display: float;
color: #919EAB;
}
#inputaddy > .form-group {
margin-bottom: 0;
}
#connect {
color: #5484F8;
background: #141920;
border: none;
padding: 0;
font-family: Roboto Mono;
#randomaddy {
margin-left: 10px;
margin-right: 10px;
}
#connect:hover {
color: #CACEF0 !important;
background-color: transparent !important;
#leftbox {
border: 2px #E2E4F7 solid;
border-radius: 8px;
padding: 3px;
background-color: #ffffff99;
margin-top: 28px;
padding-top: 15px;
padding-bottom: 10px;
}
#botrightbox {
border: 2px #E2E4F7 solid;
border-radius: 8px;
padding: 3px;
background-color: #ffffff99;
margin-top: 20px;
padding-top: 15px;
padding-bottom: 10px;
}
#terraddress > div > button {
color: #7F8CED;
background-color: #10151A;
border-radius: 4px;
border: none;
margin-top: 15px;
margin-bottom: 15px;
padding: 30px;
min-width: 100%;
svg {
max-height: 485px;
margin: auto;
display: block;
}
#connectpop > div > div > div.modal-header > button > span {
color: white !important;
font-size: 2em;
#wheelpart {
background-color: transparent;
position: relative;
margin-top: 16px;
}
.modal-content {
background-color: #171e25 !important;
color: #FFF !important;
#svgout {
position: absolute;
width: 100%;
height: 100%;
top: 0;
left: 0;
}
.modal-body {
#score {
text-align: center;
padding-left: 10%;
padding-right: 10%;
font-family: Orbitron;
font-size: 48px;
z-index: 9;
}
.modal-header {
#scorehist {
margin-bottom: -38px;
}
/* make the slider more reasonably - color wise
These are the ticks and text of the sliders
.irs-grid-pol, .irs-grid-text
*/
.irs {
font-family: Roboto Mono !important;
}
/* make the slider more reasonably - color wise */
.irs-line {
background-color: #E2E4F7 !important;
}
.irs-grid-pol.small {
visibility: hidden !important;
}
.irs-min, .irs-max, .irs-from, .irs-to {
font-size: .9em !important;
top: 6px !important;
}
.irs-max, .irs-min {
color: #686973 !important;
}
.irs-to, .irs-handle, .irs-from, .irs-max, .irs-min, .irs--sharp .irs-bar, .irs-single {
background-color: #26D994 !important;
}
.irs-handle:hover {
opacity: 75%;
background-color: #26D994 !important;
}
.irs--round .irs-bar {
background-color: #26D994;
}
.irs-handle>i:first-child {
border-top-color: #9945FF !important;
}
.irs-handle>i:first-child:hover, .irs-to:before, .irs-from:before, .irs-single:before {
border-top-color: transparent !important;
}
.irs-handle {
border: none !important;
}
.modal-footer {
visibility: hidden;
.irs-grid {
visibility: hidden !important;
font-size: 0;
height: 0;
width: 0;
}
.irs-grid-text {
visibility: hidden !important;
visibility: hidden !important;
font-size: 0;
height: 0;
width: 0;
}
.irs--round .irs-handle {
border: none !important;
top: 28px;
width: 20px;
height: 20px;
}
.top-banner {
background: #12161b;
height: 48px;
left: 0;
position: absolute;
top: 0;
.metric {
font-family: 'Exo 2';
text-align: center;
width: 100%;
font-size: 1.25em;
background: -webkit-linear-gradient(#9945FF, #14F195);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.top-banner > section {
align-items: center;
display: flex;
height: 100%;
justify-content: space-between;
margin: 0 auto;
max-width: 900px;
.metricname {
font-family: Orbitron;
color: #9945FF;
text-align: center;
width: 100%;
font-size: .8em;
padding-bottom: 10px;
}
.top-banner a {
background-color: transparent;
color: #FFF;
#bdnldscores, #dnldscores {
text-align: center;
margin: auto;
}
.top-banner a:hover, .top-banner a:active {
color: #FFF;
text-decoration: none;
.score {
font-family: 'Exo 2';
text-align: center;
width: 100%;
font-size: 1.7em;
background: -webkit-linear-gradient(#9945FF, #14F195);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.fs-logo {
padding-left: 5px;
.yourscore {
font-family: Orbitron;
color: #9945FF;
text-align: center;
width: 100%;
font-size: 1.1em;
padding-bottom: 10px;
}
.boxtitle {
text-align: center;
font-size: 1em;
font-family: Orbitron;
margin-bottom: 10px;
}
.aboutlinks {
padding-left: 20px;
padding-bottom: 15px;
}
.socials {
align-items: center;
.metricrow {
margin: 5px;
display: flex;
}
.socials a {
display: inline-block;
margin: 0 0.5em;
overflow: hidden;
text-indent: -9999px;
white-space: nowrap;
width: 24px;
.metricholder {
width: 25%;
}
.socials a:last-child {
margin-right: 0;
overflow: visible;
text-indent: 0;
width: auto;
.metricholder2 {
width: 33%;
}
.socials a:last-child::before {
content: "|";
margin: 0 0.5em;
#indent {
text-align: center;
padding-bottom: 4px;
font-size: .85em;
}
.twitter {
background: url("data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8.94 18.7051C11.4989 18.7212 13.9577 17.7118 15.7672 15.9023C17.5767 14.0928 18.5861 11.634 18.57 9.0751V8.6326C19.2267 8.15147 19.7951 7.56023 20.25 6.8851C19.6316 7.15555 18.9773 7.33491 18.3075 7.4176C19.0177 6.99444 19.5506 6.32835 19.8075 5.5426C19.1456 5.93968 18.4199 6.21883 17.6625 6.3676C16.6139 5.25027 14.9461 4.97529 13.5943 5.69684C12.2425 6.41839 11.5428 7.95705 11.8875 9.4501C9.16635 9.31653 6.63036 8.03218 4.9125 5.9176C4.02372 7.46019 4.4828 9.42766 5.9625 10.4176C5.43646 10.3973 4.92259 10.2534 4.4625 9.9976V10.0351C4.45287 11.6359 5.56204 13.0263 7.125 13.3726C6.63573 13.5042 6.12322 13.5247 5.625 13.4326C6.07495 14.7902 7.33014 15.7181 8.76 15.7501C7.56691 16.7105 6.08407 17.2391 4.5525 17.2501C4.28396 17.2423 4.01606 17.2198 3.75 17.1826C5.30022 18.1703 7.1019 18.691 8.94 18.6826' fill='%23F4F6F8'/%3E%3C/svg%3E%0A") no-repeat center center;
#sliderbox {
margin-left: 14%;
margin-right: 14%;
}
.linkedin {
background: url("data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M19.6575 3.00002H4.3425C3.61669 2.99566 3.02038 3.57199 3 4.29752V19.65C3.01639 20.3773 3.61508 20.9559 4.3425 20.9475H19.6575C20.3849 20.9559 20.9836 20.3773 21 19.65V4.29752C20.9796 3.57199 20.3833 2.99566 19.6575 3.00002ZM8.3325 18.3075H5.6925V9.75002H8.3325V18.3075ZM7.0425 8.55752C6.19951 8.55777 5.51036 7.88527 5.49 7.04252C5.47516 6.6264 5.63396 6.22284 5.92839 5.92841C6.22282 5.63398 6.62638 5.47519 7.0425 5.49002C7.8561 5.54668 8.48716 6.2232 8.48716 7.03877C8.48716 7.85435 7.8561 8.53087 7.0425 8.58752V8.55752ZM18.36 18.255H15.75V14.07C15.75 13.0725 15.75 11.775 14.355 11.775C12.96 11.775 12.75 12.87 12.75 13.9725V18.21H10.08V9.75002H12.57V10.875H12.6225C13.1428 9.97149 14.1234 9.43343 15.165 9.48002C17.8575 9.48002 18.36 11.28 18.36 13.5675V18.255Z' fill='%23F4F6F8'/%3E%3C/svg%3E%0A") no-repeat center center;
#hovernote {
font-style: italic;
text-align: center;
font-size: .85em;
color: #56575E;
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