7 Available Tokens Data From Subgraph

note: here use RPC node to grab block close to chainhead and use it for timetravel query

# wait one minute - closing allocations takes a while so not needed
#Sys.sleep(60)


# Select columns needed for rewards_per_token calculation and general info
# Remove queries_per_indexer as it no longer exists
rewards_info = synced_subgraphs %>%
  select(deployment, signalled_tokens, total_allocated_tokens, rewards_proportion)
  # Optional: Add queries_per_indexer_48h here if needed for rewards_info analysis later
  # select(deployment, signalled_tokens, total_allocated_tokens, rewards_proportion, queries_per_indexer_48h)

# Now pull total available tokens
query = '{
  indexers(where: {id: "0x74dbb201ecc0b16934e68377bc13013883d9417b"}) {
    stakedTokens
    delegatedTokens
    availableStake
  }
}'

# Send POST request to the GraphQL API
response = POST(url, body = list(query = query), encode = "json")
# Parse the JSON response
content = content(response, "text", encoding='UTF-8')
json_data = fromJSON(content, flatten = TRUE)

# get available tokens amounts
available_tokens = as.data.frame(json_data$data$indexers) %>% 
  mutate(available_stake = as.numeric(availableStake)/10^18,
         total_stake = (as.numeric(stakedTokens)/10^18)+(as.numeric(delegatedTokens))/10^18) %>% 
  select(-availableStake, -delegatedTokens, -stakedTokens)

# Calculate rewards per token
rewards_info$rewards_per_token = rewards_info$rewards_proportion / rewards_info$total_allocated_tokens

# Sort by rewards per token in descending order
rewards_info = rewards_info[order(-rewards_info$rewards_per_token), ] %>% filter(rewards_per_token > 0, rewards_per_token < 9999999)

available_tokens

##   available_stake total_stake
## 1        112970.1     2579844

rewards_info

## # A tibble: 278 × 5
##    deployment         signalled_tokens total_allocated_tokens rewards_proportion
##    <chr>                         <dbl>                  <dbl>              <dbl>
##  1 QmbWhGfCrewoQvwJ7…             1.00                    100             0.0100
##  2 QmbK8eiivKro8XT9x…             1.00                    100             0.0100
##  3 QmVa4x9Jqhq2b3QbU…             1.00                    100             0.0100
##  4 QmZqKd3ZvqwWcLsyd…             1.00                    100             0.0100
##  5 QmbPUyAyzyVVFpaJC…             1.00                    100             0.0100
##  6 QmdUknu8tyvH1BAE1…             1.00                    100             0.0100
##  7 QmZ3TUhnG2cJxniWh…             1.00                    100             0.0100
##  8 Qme4i64hYrHrAgwuH…             1.00                    100             0.0100
##  9 QmSdc5FFbLzF436KE…             1.00                    100             0.0100
## 10 QmPB1fZxWhgMA9u6K…             1.00                    100             0.0100
## # ℹ 268 more rows
## # ℹ 1 more variable: rewards_per_token <dbl>

save.image('/root/github/indexer_analytics_tutorial/data/chapters_snapshots/08-available_tokens.RData')