Transaction
ID: 5b7b1077f1...bec7
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
1,607.3 ERG
Tokens:
Loading assets...
Outputs (4)
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.03 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1,607.26 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 86,593
Total coins transferred: 1,607.3 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000431 ERG
Raw Transaction Data
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],
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}
],
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"outputs": [
{
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"transactionId": "5b7b1077f14cd7de1968b2cec31d663fa04e52de8248659fbd8f8d0d4bf8bec7",
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"ergoTreeConstants": "0: 2000\n1: 2000\n2: 100000\n3: 0\n4: SigmaProp(ProveDlog(ECPoint(593abf,75cc6c,...)))\n5: 1\n6: 1\n7: 0\n8: 1\n9: 0\n10: 0\n11: 2\n12: 0\n13: false",
"ergoTreeScript": "{\n val b1 = getVar[Byte](0.toByte).get\n val bi2 = SELF.R4[BigInt].get\n val l3 = SELF.R6[Long].get\n val l4 = if (l3 > placeholder[Long](0)) { l3 } else { placeholder[Long](1) }\n val l5 = placeholder[Long](2)\n val bi6 = bi2 * SELF.R9[Long].get + l4.toBigInt / l5.toBigInt\n val prop7 = SELF.R5[SigmaProp].get\n val coll8 = SELF.R7[Coll[Byte]].get\n val bool9 = coll8.size == placeholder[Int](3)\n val bi10 = bi2 * l4.toBigInt / l5.toBigInt\n val prop11 = placeholder[SigmaProp](4)\n val coll12 = SELF.propositionBytes\n val bool13 = INPUTS.filter({(box13: Box) => box13.propositionBytes == coll12 }).size == placeholder[Int](5)\n val bool14 = OUTPUTS.forall({(box14: Box) => box14.propositionBytes != coll12 })\n if (b1 == placeholder[Byte](6)) {(\n val box15 = OUTPUTS(placeholder[Int](7))\n val box16 = OUTPUTS(placeholder[Int](8))\n sigmaProp(allOf(Coll[Boolean](if (bool9) { allOf(Coll[Boolean](box15.value.toBigInt >= bi2 - bi6, box15.propositionBytes == prop7.propBytes)) } else {(\n val tuple17 = box15.tokens(placeholder[Int](9))\n allOf(Coll[Boolean](tuple17._1 == coll8, tuple17._2.toBigInt >= bi2 - bi6, box15.propositionBytes == prop7.propBytes))\n )}, if (bool9) { allOf(Coll[Boolean](box16.value.toBigInt >= bi10, box16.propositionBytes == prop11.propBytes)) } else {(\n val tuple17 = box16.tokens(placeholder[Int](10))\n allOf(Coll[Boolean](box16.propositionBytes == prop11.propBytes, tuple17._1 == coll8, tuple17._2.toBigInt >= bi10))\n )}, bool13, bool14)))\n )} else { if (b1 == placeholder[Byte](11)) {(\n val box15 = OUTPUTS(placeholder[Int](12))\n sigmaProp(allOf(Coll[Boolean](allOf(Coll[Boolean](box15.value == SELF.value, box15.propositionBytes == prop7.propBytes, box15.tokens == SELF.tokens)), bool13, bool14))) && prop7\n )} else { sigmaProp(placeholder[Boolean](13)) } }\n}",
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"assets": [
{
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"index": 0,
"amount": 1,
"name": "Hell's Harlequin",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "SSigmaProp",
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},
"R6": {
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"sigmaType": "SLong",
"renderedValue": "3000"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "4d65774d6172742c426c69747a5443472c53656c6c"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R9": {
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"sigmaType": "SLong",
"renderedValue": "0"
},
"R4": {
"serializedValue": "06050ba43b7400",
"sigmaType": "SBigInt",
"renderedValue": "CBigInt(50000000000)"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
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"transactionId": "5b7b1077f14cd7de1968b2cec31d663fa04e52de8248659fbd8f8d0d4bf8bec7",
"blockId": "71d51a5496954f2858f6c640173e124866d4bb5b645ec4b68e8386aa148d1606",
"value": 30000000,
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