Transaction
ID: 89050aea15...66be
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.5649698 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00110484 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.56376496 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 47,363
Total coins transferred: 0.5659698 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000243 ERG
Raw Transaction Data
{
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"timestamp": 1770391407604,
"index": 3,
"globalIndex": 10261803,
"numConfirmations": 47363,
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{
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],
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],
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"outputs": [
{
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"ergoTree": "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",
"ergoTreeConstants": "0: 2\n1: Coll(-5,-4,-62,-115,-117,-94,76,64,118,0,15,50,84,-80,104,93,-64,-66,70,8,-15,-62,76,27,-107,-22,22,-72,45,34,41,32)\n2: 0\n3: 1\n4: 4\n5: 0\n6: 5\n7: 0\n8: 3\n9: 0\n10: Coll(-102,-33,117,-96,-58,-111,-107,78,-112,-118,-18,-109,59,39,-4,75,81,-128,79,22,-54,-75,-47,-30,38,79,88,26,-68,-21,23,3)\n11: 0\n12: 90\n13: 1\n14: 0\n15: true\n16: Coll(45,-126,27,3,-30,-34,114,118,-69,-21,-77,-1,65,-20,55,79,-99,110,-38,67,100,97,-111,76,1,38,-126,-49,100,95,-92,-54)\n17: 1\n18: 0\n19: false\n20: true\n21: Coll(122,-94,-75,-37,-122,16,-18,-68,-23,35,110,21,-55,109,-47,84,-91,113,115,65,96,4,98,-91,-79,-37,114,2,-73,30,-45,38)\n22: 0\n23: 0\n24: 1\n25: 10\n26: false\n27: Coll(58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107)\n28: 0\n29: Coll(-126,-103,-39,-114,21,-21,-18,127,-93,-102,-41,22,-34,124,-117,-79,-111,121,10,27,-12,-73,-61,-7,26,-13,90,14,54,24,119,6)\n30: 0\n31: 0\n32: 1\n33: 1\n34: 0\n35: 1\n36: 1\n37: 2\n38: 3\n39: 4\n40: 5\n41: 5\n42: 6\n43: 6\n44: 7\n45: 7\n46: 8\n47: 5\n48: 0\n49: 1\n50: 2\n51: 2\n52: 4\n53: 1\n54: false\n55: false\n56: false\n57: 1\n58: 0\n59: 5\n60: 0\n61: 2\n62: 30\n63: 2\n64: 0\n65: 1\n66: false\n67: 1\n68: 0\n69: 0\n70: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R8[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n val coll6 = SELF.R6[Coll[Byte]].get\n val coll7 = SELF.tokens(placeholder[Int](2))._1\n val coll8 = CONTEXT.dataInputs\n val coll9 = SELF.R5[Coll[Byte]].get\n val coll10 = SELF.R9[Coll[Coll[Byte]]].get\n val coll11 = coll10(placeholder[Int](3))\n val l12 = coll3(placeholder[Int](4))\n val l13 = coll3(placeholder[Int](5))\n val l14 = l4 - placeholder[Long](6)\n val func15 = {(box15: Box) =>\n box15.tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll11 }).fold(\n placeholder[Long](7), {(tuple17: (Long, (Coll[Byte], Long))) => tuple17._1 + tuple17._2._2 }\n )\n }\n val coll16 = SELF.R7[Coll[Coll[Byte]]].get\n val l17 = coll3(placeholder[Int](8))\n val coll18 = coll10(placeholder[Int](9))\n val coll19 = OUTPUTS.filter({(box19: Box) => blake2b256(box19.propositionBytes) == placeholder[Coll[Byte]](10) })\n val coll20 = OUTPUTS.filter({(box20: Box) => blake2b256(box20.propositionBytes) == blake2b256(SELF.propositionBytes) })\n sigmaProp((i1 == placeholder[Int](11)) && ((if ((l2 >= l4) && (l2 < l4 + placeholder[Long](12))) {(\n val coll21 = OUTPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll5 })\n if (coll21.size == placeholder[Int](13)) {(\n val box22 = coll21(placeholder[Int](14))\n val tuple23 = box22.R6[(Coll[Byte], Coll[Byte])].get\n val coll24 = tuple23._1\n val coll25 = tuple23._2\n val coll26 = Coll[Byte]()\n if (((blake2b256(coll24) == coll6) && (blake2b256(box22.propositionBytes) == coll5)) && if (coll25 == coll26) { placeholder[Boolean](15) } else {(\n val coll27 = coll8.filter({(box27: Box) => ((blake2b256(box27.propositionBytes) == placeholder[Coll[Byte]](16)) && (box27.R6[Coll[Byte]].get == coll7)) && (box27.R5[Coll[Byte]].get == coll25) })\n if (coll27.size == placeholder[Int](17)) {(\n val box28 = coll27(placeholder[Int](18))\n val coll29 = box28.R9[Coll[Long]].get\n (((coll29.fold(placeholder[Boolean](19), {(tuple30: (Boolean, Long)) =>\n val bool32 = tuple30._1\n if (bool32) { bool32 } else { if (blake2b256(box28.R7[Coll[Byte]].get.append(coll9).append(longToByteArray(tuple30._2)).append(box28.R8[Coll[Byte]].get).append(box28.R4[Coll[Byte]].get).append(coll24)) == box28.R5[Coll[Byte]].get) { placeholder[Boolean](20) } else { bool32 } }\n }) && if (coll11 == coll26) { box28.value >= l12 } else { box28.tokens.exists({(tuple30: (Coll[Byte], Long)) => (tuple30._1 == coll11) && (tuple30._2 >= l12) }) }) && ({(box30: Box) =>\n val coll32 = coll8.filter({(box32: Box) =>\n val opt34 = box32.R4[Coll[Byte]]\n (opt34.isDefined && (opt34.get == box30.R7[Coll[Byte]].get)) && (blake2b256(box32.propositionBytes) == placeholder[Coll[Byte]](21))\n })\n if (coll32.size > placeholder[Int](22)) {(\n val l33 = coll32.fold(coll32(placeholder[Int](23)), {(tuple33: (Box, Box)) =>\n val box35 = tuple33._2\n val box36 = tuple33._1\n if (box35.creationInfo._1 < box36.creationInfo._1) { box35 } else { box36 }\n }).creationInfo._1.toLong\n if (l33 < l13) { l13 } else { l33 }\n )} else { l4 }\n }(box28) < l14 - placeholder[Long](24))) && (box28.creationInfo._1.toLong < l4)) && (coll29.size.toLong <= placeholder[Long](25))\n )} else { placeholder[Boolean](26) }\n )}) {(\n val coll27 = coll8.filter({(box27: Box) => ((((((blake2b256(box27.propositionBytes) == placeholder[Coll[Byte]](27)) && (box27.tokens.size > placeholder[Int](28))) && (box27.R4[Coll[Byte]].get == placeholder[Coll[Byte]](29))) && (box27.R5[Coll[Byte]].get == coll7)) && box27.R6[Boolean].get) && box27.R8[Boolean].get) && coll16.exists({(coll29: Coll[Byte]) => coll29 == box27.tokens(placeholder[Int](30))._1 }) })\n val coll28 = coll27.map({(box28: Box) => box28.tokens(placeholder[Int](31))._1 })\n ((((((((((((((((((func15(box22) >= func15(SELF)) && (box22.tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll7 }).size == placeholder[Int](32))) && (box22.R4[Int].get == placeholder[Int](33))) && (box22.R5[Coll[Byte]].get == coll9)) && (box22.R7[Coll[Coll[Byte]]].get == coll16)) && (box22.R8[Coll[Long]].get(placeholder[Int](34)) == l13)) && (box22.R8[Coll[Long]].get(placeholder[Int](35)) == coll3(placeholder[Int](36)))) && (box22.R8[Coll[Long]].get(placeholder[Int](37)) == l4)) && (box22.R8[Coll[Long]].get(placeholder[Int](38)) == l17)) && (box22.R8[Coll[Long]].get(placeholder[Int](39)) == l12)) && (box22.R8[Coll[Long]].get(placeholder[Int](40)) == coll3(placeholder[Int](41)))) && (box22.R8[Coll[Long]].get(placeholder[Int](42)) >= coll3(placeholder[Int](43)))) && (box22.R8[Coll[Long]].get(placeholder[Int](44)) == coll3(placeholder[Int](45)))) && (box22.R8[Coll[Long]].get(placeholder[Int](46)) >= l2 + placeholder[Long](47))) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](48)) == coll18)) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](49)) == coll11)) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](50)) == coll10(placeholder[Int](51)))) && (box22.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](52))) && coll28.indices.forall({(i29: Int) => !coll28.slice(i29 + placeholder[Int](53), coll27.size).exists({(coll31: Coll[Byte]) => coll31 == coll28(i29) }) })\n )} else { placeholder[Boolean](54) }\n )} else { placeholder[Boolean](55) }\n )} else { placeholder[Boolean](56) } || if ((l2 < l4) && (coll19.size == placeholder[Int](57))) {(\n val box21 = coll19(placeholder[Int](58))\n val l22 = func15(SELF) - l17 / placeholder[Long](59)\n (((((((((func15(box21) >= l22) && (box21.tokens(placeholder[Int](60))._1 == coll7)) && (box21.R4[Int].get == placeholder[Int](61))) && (box21.R5[Long].get >= l2 + placeholder[Long](62))) && (blake2b256(box21.R6[Coll[Byte]].get) == coll6)) && (box21.R7[Long].get == l22)) && (box21.R8[Long].get == l4)) && (box21.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](63))) && (box21.R9[Coll[Coll[Byte]]].get(placeholder[Int](64)) == coll18)) && (box21.R9[Coll[Coll[Byte]]].get(placeholder[Int](65)) == coll11)\n )} else { placeholder[Boolean](66) }) || if ((l2 < l14) && (coll20.size == placeholder[Int](67))) {(\n val box21 = coll20(placeholder[Int](68))\n (((((((box21.tokens(placeholder[Int](69))._1 == coll7) && (func15(box21) >= func15(SELF))) && (box21.R5[Coll[Byte]].get == blake2b256(coll9.append(SELF.id)))) && (box21.R4[Int].get == i1)) && (box21.R6[Coll[Byte]].get == coll6)) && (box21.R7[Coll[Coll[Byte]]].get == coll16)) && (box21.R8[Coll[Long]].get == coll3)) && (box21.R9[Coll[Coll[Byte]]].get == coll10)\n )} else { placeholder[Boolean](70) }))\n}",
"address": "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",
"assets": [
{
"tokenId": "14a7f526d7b9ce16793308f473374bcd70bbdc5e41f297284728721058899fb0",
"index": 0,
"amount": 1,
"name": "Dev Game [dbe9e9]",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 10000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e207031dbd855e86ba5424219a1b2cd2d25076acf581436520869e88617152ee011",
"sigmaType": "Coll[SByte]",
"renderedValue": "7031dbd855e86ba5424219a1b2cd2d25076acf581436520869e88617152ee011"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "1108b6bed101028ac0d101a09c01a006b0e70280b518a08d06",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1716123,1,1716229,10000,400,23000,200000,50000]"
},
"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
},
"R9": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[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,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71,0008cd025ac8ab183ffde36068603120b00acdf141b91fe4e0c0c6d562b5f24e1e2cc2d1]"
},
"R4": {
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