Transaction
ID: bae052ec46...4dff
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
993.1 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
993.09 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 382,190
Total coins transferred: 993.1 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000405 ERG
Raw Transaction Data
{
"id": "bae052ec46a6ec08af7a487d09ed25fe1c3fc0fd86a29e9978a83ac1e8d34dff",
"blockId": "632a07f17401befc04ce3f8737589f992d69c9479b13372c51764d8975d91e5b",
"inclusionHeight": 1381400,
"timestamp": 1729874863724,
"index": 26,
"globalIndex": 7954348,
"numConfirmations": 382190,
"inputs": [
{
"boxId": "9a56855ed74cb90bc6132bf045565414073d53963af54d5bfb3ee1dd3ea1c867",
"value": 1000000,
"index": 0,
"spendingProof": "3e54f94de6860fd017a275f82577f55c221655c6749eb26ca38b8cfab9ed1973cc1d7cae75927e94ac8402d0f8ddd894b3e56838d0d0da97",
"outputBlockId": "571b37587f195c7c4e9914ca38f1713018ea21db21ca5c966efae5e83bc6b255",
"outputTransactionId": "d562734127936d19e1b3014196793024be47e5e340c2e0b8c6c8188775a6aadb",
"outputIndex": 3,
"outputGlobalIndex": 43414305,
"outputCreatedAt": 1380598,
"outputSettledAt": 1380601,
"ergoTree": "0008cd028ee1019ca83537c95bbfb3d35afac4c16790d3f1597bd75b67e452b4f0d2cb63",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8ee101,cddaf3,...)))}",
"address": "9fbzAZAQauntRwsnCNFPb7DzT7854qWp4uxeWrhgiscW43aFGfN",
"assets": [
{
"tokenId": "ff7f67f63681de1dbfa89aca6a1a0daf5b1a6723e199a40ac680da2938d9dd2a",
"index": 0,
"amount": 1,
"name": "Paideia Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "803b41115865145ca3e89016f5ac2b4ea09f1aba62402a6abe50002347a14a6c",
"value": 993100231723,
"index": 1,
"spendingProof": "0d4493d5b9f51443311a727c07ee92441dfa7966bc84f94af8d220bfc952d68a7df115ad8a871f156859894c2f794fbae2952ab1b15bb6cb",
"outputBlockId": "571b37587f195c7c4e9914ca38f1713018ea21db21ca5c966efae5e83bc6b255",
"outputTransactionId": "d562734127936d19e1b3014196793024be47e5e340c2e0b8c6c8188775a6aadb",
"outputIndex": 6,
"outputGlobalIndex": 43414308,
"outputCreatedAt": 1380598,
"outputSettledAt": 1380601,
"ergoTree": "0008cd028ee1019ca83537c95bbfb3d35afac4c16790d3f1597bd75b67e452b4f0d2cb63",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8ee101,cddaf3,...)))}",
"address": "9fbzAZAQauntRwsnCNFPb7DzT7854qWp4uxeWrhgiscW43aFGfN",
"assets": [
{
"tokenId": "01dce8a5632d19799950ff90bca3b5d0ca3ebfa8aaafd06f0cc6dd1e97150e7f",
"index": 0,
"amount": 3721917809,
"name": "CYPX",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "399746928be71d173a4082243ffb30e079eb1a365b05c2625bfd29c0b404a663",
"index": 1,
"amount": 2,
"name": "Gobsmasher",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0ebc5ffcdd090ad97bbf74bdf1413710698c84f1eeab44b5e31b6a5e38ec7b1c",
"index": 2,
"amount": 1,
"name": "Anuven",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fb9f142a42cbfcbe0baf300e218528c8030d5aca6f90c1277ae1fd7221b3b492",
"index": 3,
"amount": 1,
"name": "Vyrion",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0dcafdaf68979323e260d0c3ef3d67cf3de3ee5b2db2011d345321a8afa8968b",
"index": 4,
"amount": 2,
"name": "Temptress",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "91387b9800730a4a84d1e060dacbab51848e8aa27b4f7e710c1c2acf89624957",
"index": 5,
"amount": 1,
"name": "Ergnome #866 Gelatoswap the Tasty Fairy",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "07b106166d190a1a04fa231893168fdd33c97419107822ea55c39f53f630ea6a",
"index": 6,
"amount": 1,
"name": "Apparition Slayer",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "6ad70cdbf928a2bdd397041a36a5c2490a35beb4d20eabb5666f004b103c7189",
"index": 7,
"amount": 69420,
"name": "rsHOSKY",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fc0e31589aa240fb8270efa3c41a661bc6377437c87a1d653ab68eb493409197",
"index": 8,
"amount": 1,
"name": "Siege of Kom El",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "af1a2e8005f6ffc9e291e121d1fb08795c5a079409b8ca56e20eb2f4f6f8553b",
"index": 9,
"amount": 8400000000,
"name": "🐶",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "5d960d87549e69ad75f375654793b8f9643d0155daa0de81e9a8d6600381de9f",
"transactionId": "bae052ec46a6ec08af7a487d09ed25fe1c3fc0fd86a29e9978a83ac1e8d34dff",
"blockId": "632a07f17401befc04ce3f8737589f992d69c9479b13372c51764d8975d91e5b",
"value": 10000000,
"index": 0,
"globalIndex": 43439936,
"creationHeight": 1381397,
"settlementHeight": 1381400,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[Coll[Coll[Byte]]]](5.toByte).get\n val box2 = CONTEXT.dataInputs(0)\n val func3 = {(box3: Box) => box3.R4[AvlTree].get }\n val coll4 = func3(box2).getMany(coll1(0), getVar[Coll[Byte]](0.toByte).get)\n val coll5 = coll4(1).get\n val coll6 = Coll[Int](0)\n val func7 = {(opt7: Option[Coll[Byte]]) => opt7.get.slice(6, 38) }\n val box8 = INPUTS(0)\n val avlTree9 = func3(box8)\n val coll10 = avlTree9.getMany(coll1(1), getVar[Coll[Byte]](1.toByte).get)\n val coll11 = func7(coll10(1))\n val coll12 = getVar[Coll[Coll[Byte]]](3.toByte).get\n val coll13 = coll12(1)\n val coll14 = coll4(3).get\n val coll15 = Coll[Int](0, 3)\n val coll16 = func7(coll10(2))\n val coll17 = func7(coll10(3))\n val coll18 = coll12(0)\n val coll19 = coll4(5).get\n val coll20 = Coll[Int](0, 1)\n val coll21 = func7(coll10(0))\n val coll22 = Coll[Coll[Byte]](coll16, coll21)\n val coll23 = coll12(2)\n val coll24 = coll4(7).get\n val coll25 = coll12(3)\n val coll26 = coll4(9).get\n val coll27 = Coll[Coll[Byte]](coll16, coll17)\n val coll28 = coll12(4)\n val coll29 = coll4(11).get\n val coll30 = coll12(5)\n val coll31 = coll4(15).get\n val coll32 = coll12(7)\n val coll33 = coll4(17).get\n val coll34 = coll12(8)\n val coll35 = coll4(19).get\n val coll36 = coll12(9)\n val coll37 = coll4(13).get\n val coll38 = coll12(6)\n val coll39 = coll4(21).get\n val coll40 = coll12(10)\n val coll41 = coll4(25).get\n val coll42 = coll12(12)\n val coll43 = coll4(23).get\n val coll44 = coll12(11)\n val coll45 = coll4(0).get\n val coll46 = coll12(13)\n val box47 = OUTPUTS(0)\n val coll48 = box47.tokens\n val coll49 = box8.tokens\n val tuple50 = coll48(1)\n val tuple51 = coll48(2)\n val box52 = OUTPUTS(1)\n val coll53 = box52.tokens\n val tuple54 = coll53(0)\n val coll55 = coll1(2)\n val coll56 = coll55(2)\n val coll57 = getVar[Coll[Coll[Byte]]](4.toByte).get\n val box58 = OUTPUTS(2)\n val coll59 = box58.tokens\n val coll60 = Coll[Byte](\n 78.toByte, -58.toByte, 31.toByte, 72.toByte, 91.toByte, -104.toByte, -21.toByte, -121.toByte, 21.toByte, 63.toByte, 124.toByte, 87.toByte, -37.toByte, 79.toByte, 94.toByte, -51.toByte, 117.toByte, 85.toByte, 111.toByte, -35.toByte, -68.toByte, 64.toByte, 59.toByte, 65.toByte, -84.toByte, -8.toByte, 68.toByte, 31.toByte, -34.toByte, -114.toByte, 22.toByte, 9.toByte, 0.toByte\n )\n val coll61 = box58.R5[Coll[Long]].get\n val l62 = coll61(0)\n val l63 = CONTEXT.preHeader.timestamp + byteArrayToLong(coll10(4).get.slice(1, 9))\n val box64 = OUTPUTS(3)\n val box65 = OUTPUTS(4)\n val box66 = OUTPUTS(5)\n val box67 = OUTPUTS(6)\n val box68 = OUTPUTS(7)\n val box69 = OUTPUTS(8)\n val box70 = OUTPUTS(9)\n val box71 = OUTPUTS(10)\n sigmaProp(\n allOf(\n Coll[Boolean](\n Coll[Byte](\n 86.toByte, -120.toByte, -65.toByte, -67.toByte, -42.toByte, -51.toByte, -23.toByte, 50.toByte, 106.toByte, -33.toByte, 112.toByte, 32.toByte, 46.toByte, -95.toByte, 91.toByte, -8.toByte, 104.toByte, -19.toByte, 105.toByte, 24.toByte, 90.toByte, -12.toByte, 110.toByte, 39.toByte, 82.toByte, -123.toByte, -105.toByte, 7.toByte, 20.toByte, -101.toByte, 93.toByte, 91.toByte\n ) == blake2b256(coll1.flatMap({(coll72: Coll[Coll[Byte]]) => coll72 }).flatMap({(coll72: Coll[Byte]) => coll72 })), box2.tokens(0)._1 == placeholder[\n Coll[Byte]\n ](0), allOf(\n Coll[Boolean](\n coll4(2).get.patch(1, blake2b256(substConstants(coll5.slice(6, coll5.size), coll6, Coll[Coll[Byte]](coll11))), 32) == coll13, coll4(4).get.patch(\n 1, blake2b256(substConstants(coll14.slice(6, coll14.size), coll15, Coll[Coll[Byte]](coll16, coll11.append(coll17)))), 32\n ) == coll18, coll4(6).get.patch(1, blake2b256(substConstants(coll19.slice(6, coll19.size), coll20, coll22)), 32) == coll23, coll4(8).get.patch(\n 1, blake2b256(substConstants(coll24.slice(6, coll24.size), coll20, coll22)), 32\n ) == coll25, coll4(10).get.patch(1, blake2b256(substConstants(coll26.slice(6, coll26.size), coll15, coll27)), 32) == coll28, coll4(12).get.patch(\n 1, blake2b256(substConstants(coll29.slice(6, coll29.size), coll20, coll27)), 32\n ) == coll30, coll4(16).get.patch(1, blake2b256(substConstants(coll31.slice(6, coll31.size), coll20, coll27)), 32) == coll32, coll4(18).get.patch(\n 1, blake2b256(substConstants(coll33.slice(6, coll33.size), coll20, coll27)), 32\n ) == coll34, coll4(20).get.patch(1, blake2b256(substConstants(coll35.slice(6, coll35.size), coll20, coll27)), 32) == coll36, coll4(14).get.patch(\n 1, blake2b256(substConstants(coll37.slice(6, coll37.size), coll20, coll27)), 32\n ) == coll38, coll4(22).get.patch(1, blake2b256(substConstants(coll39.slice(6, coll39.size), coll6, Coll[Coll[Byte]](coll16))), 32) == coll40, coll4(\n 26\n ).get.patch(1, blake2b256(substConstants(coll41.slice(6, coll41.size), coll20, coll27)), 32) == coll42, coll4(24).get.patch(\n 1, blake2b256(substConstants(coll43.slice(6, coll43.size), coll20, coll27)), 32\n ) == coll44, coll4(27).get.patch(1, blake2b256(substConstants(coll45.slice(6, coll45.size), coll15, coll27)), 32) == coll46\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box47.propositionBytes) == coll46.slice(1, 33), box47.value >= 1000000L, coll48(0) == coll49(\n 0\n ), tuple50._1 == coll21, tuple50._2 == 9223372036854775807L, tuple51._1 == coll11, tuple51._2 == 9223372036854775807L, coll48.size == 3\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box52.propositionBytes) == coll13.slice(\n 1, 33\n ), box52.value >= 1000000L, tuple54._1 == coll16, tuple54._2 == 1L, coll53.size == 1, box52.R4[AvlTree].get.digest == avlTree9.insert(\n Coll[(Coll[Byte], Coll[Byte])](\n (coll55(0), coll18), (coll55(1), coll13), (blake2b256(coll56.append(coll57(0))), coll23), (blake2b256(coll56.append(coll57(1))), coll25), (\n blake2b256(coll55(3).append(coll57(2))), coll28\n ), (coll55(4), coll30), (coll55(5), coll38), (coll55(6), coll32), (coll55(7), coll34), (coll55(8), coll36), (coll55(9), coll40), (\n coll55(10), coll44\n ), (coll55(11), coll42), (coll55(12), coll46)\n ), getVar[Coll[Byte]](2.toByte).get\n ).get.digest\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box58.propositionBytes) == coll40.slice(1, 33), box58.value >= 1000000L, coll59(0)._1 == coll17, coll59(1) == coll49(\n 1\n ), coll59.size == 2, box58.R4[Coll[AvlTree]].get.forall(\n {(avlTree72: AvlTree) => avlTree72.digest == coll60 }\n ), l62 >= l63 - 3600000L, l62 < l63 + 3600000L, coll61.slice(1, coll61.size).forall({(l72: Long) => l72 == 0L }), box58.R6[\n Coll[Coll[Long]]\n ].get.flatMap({(coll72: Coll[Long]) => coll72 }).forall({(l72: Long) => l72 == 0L }), box58.R7[Coll[(AvlTree, AvlTree)]].get.forall(\n {(tuple72: (AvlTree, AvlTree)) => (tuple72._1.digest == coll60) && (tuple72._2.digest == coll60) }\n ), box58.R8[Coll[Long]].get.forall({(l72: Long) => l72 == 0L })\n )\n ), allOf(\n Coll[Boolean](\n box64.value >= 1000000L, blake2b256(box64.propositionBytes) == coll30.slice(1, 33), box65.value >= 1000000L, blake2b256(\n box65.propositionBytes\n ) == coll38.slice(1, 33), box66.value >= 1000000L, blake2b256(box66.propositionBytes) == coll42.slice(1, 33), box67.value >= 1000000L, blake2b256(\n box67.propositionBytes\n ) == coll32.slice(1, 33), box68.value >= 1000000L, blake2b256(box68.propositionBytes) == coll36.slice(1, 33), box69.value >= 1000000L, blake2b256(\n box69.propositionBytes\n ) == coll44.slice(1, 33), box70.value >= 1000000L, blake2b256(box70.propositionBytes) == coll34.slice(1, 33)\n )\n ), allOf(Coll[Boolean](box71.value >= SELF.value, box71.propositionBytes == SELF.propositionBytes))\n )\n )\n )\n}",
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},
{
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"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
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}