davaymne

{
  "__inputs": [
    {
      "name": "DS_GRAPHQL_DATA SOURCE",
      "label": "GraphQL Data Source",
      "description": "",
      "type": "datasource",
      "pluginId": "fifemon-graphql-datasource",
      "pluginName": "GraphQL Data Source"
    },

davaymne

#!/bin/bash
# Log may contain different subgraphs - filter subgrafs manualy first of all
# query.20201126_44.log

GRAPHS_LIST="<PATH>/all-graphs-list.csv"
TIMESTAMP=$(date --date="yesterday" +%Y%m%d)
#NAME_BASE=$(echo $1 | cut -d'.' -f 1,2)
NAME_BASE="query.${TIMESTAMP}"
LOGS="/fluentd/log/query-node/${NAME_BASE}*"
SUMMARY_JSONL="/fluentd/log/summary/${NAME_BASE}.summary.jsonl"

davaymne

# Script to convert ipfs to b58decode, eg QmTN6gMCBCYTgbis33eSvr6sLsQoQ3R6a2KzR7CqmMABQP -> '0xdfffeffgkjfijfoiqfioqmfqiomfdfffeffgkjfijfoiqfioqmfqiomf
# Require: file with list of ipfs: each row is one ipfs
# Usage: python3 convert-ipfs-to-bytes32.py file.csv
import binascii
import base58
import sys

def ipfs_b32(ipfs):
    output  = base58.b58decode(ipfs)
    output = output[2:]

davaymne

#!/bin/bash
# Loga may contain different subgraphs - filter subgrafs manualy first of all
NAME_BASE=$(echo $1 | cut -d'.' -f 1)
SUMMARY_JSONL="${NAME_BASE}-summary.jsonl"
OUTPUT_JSONL="${NAME_BASE}.jsonl"
TREEBUF="${NAME_BASE}.treebuf"

AGORA=<PATH>agora1/agora/target/release/agora

echo "Converting log to jsonl $1"

davaymne

import sys

with open(sys.argv[1], 'r') as f:
    n = 0
    for line in f:
        if len(line) > n:
            n = len(line)
with open(sys.argv[1], 'r') as f:
    for line in f:
        new = '{}{}'.format(line[0].lower(), line[1:]).strip().ljust(n)

davaymne

#!/bin/bash

for id in $(cat $1);
do
  echo "Allocate $id, Amount $2"
  graph indexer rules set $id allocationAmount $2 parallelAllocations 1 decisionBasis always
done

davaymne

# Script for bulk costmodel provisioning.
# Require: tsv file (fields tab separated)
# File format: 4 fields: name, id, full path to costmodel, variable string
# How to use: python3 set-bulk-costmodel.py my-costmodels.tsv
import sys
import subprocess
with open(sys.argv[1], 'r') as f:
    for line in f:
        print(line)
        name, id, model, variables = line.split('\t')

davaymne

# Requires argument tsv file: b32   id  name    allocation
import sys
import subprocess
with open(sys.argv[1], 'r') as f:
    for line in f:
        print(line)
        b32, id, name, allocation = line.strip().split('\t')
        #print(id, model)
        # graph indexer rules never  $id
        cmd = ['graph', 'indexer', 'rules', 'never', id]

davaymne

# Consumes json summary file
# output call count per subgraph 

summaries=""
  day=2020115
  day_summary=$(jq -s 'group_by(.subgraph) |
    map({"subgraph":(.[0].subgraph), "calls":(reduce .[].calls as $calls (0; . + $calls)), "date":("'$day'") }) |
    map([.subgraph, .calls, .date] | join(", ")) | join(" \r\n ")' < $1)
  summaries+="${day_summary//\"} \r\n"
printf "${summaries//\"}" > subgraph_daily_summary.csv

davaymne

{
  "__inputs": [
    {
      "name": "DS_GRAPHQL_DATA SOURCE",
      "label": "GraphQL Data Source",
      "description": "",
      "type": "datasource",
      "pluginId": "fifemon-graphql-datasource",
      "pluginName": "GraphQL Data Source"
    },