The vertices are hash160 or, in the case of the pic, base58 bitcoin addresses. How big a vertex appears, like in the pic, is probably determined by number of transactions. The edges are transactions, send and receive, colored by amounts transferred, small amounts grey, large amounts colors.
I was thrown out of geometry class in highschool, so I didn't take it.
Topic: . - page 9. (Read 39124 times)
Will it work with yED to graph the addresses visually?
For Ubuntu 11.04 64 bit
To download yED:
http://www.yworks.com/en/products_download.php?file=yEd-3.9.2.zip
To run yED:
Start yEd from commandline using,
For Ubuntu 11.04 64 bit
To download yED:
http://www.yworks.com/en/products_download.php?file=yEd-3.9.2.zip
To run yED:
Start yEd from commandline using,
Code:
java -Xmx512m -jar /path/to/yed.jar
It got nearly all of my often-used addresses, but had a LOT of false positives.
Also: with the satoshi client there are quite a few addresses that actually are
in your wallet but that you never "see". These are called "change" address,
they're created automatically by the client when you send money.
The way to check if they're yours is to run ./bitcoind validateaddress
and to check the "ismine" field in the JSON output.
Also, want to run it on my public address? I am curious what other addresses are correlated with it... 
If not, that's fine, I'll download it and attempt to compile myself.
If not, that's fine, I'll download it and attempt to compile myself.Here you go.
Even translated the result to the usual format.
I'd be curious to see if it worked. Let me know.
Code:
18TKNbSLTrd3a2W8mtoH5uNzFhWRWNcuHU
1HCPvWwBuUp7wqY69pgVeQZVv7KWj2foTC
15QeFbpe3o1rweuB4vHFG6FZHwZw6SKTe6
1EScB6WzkeDVUZwLSsAHxUNuRr8jN38MLm
17sUs5wQ9VrqxNwVg2ZGu2f77XW8QWzbAF
1MTvpvsZgjsWK588kgvm9RS35MQW46eyAW
1Ah5SFitc1zeWFck4CAdFaheAdU5RxiGq7
1M3z9w1tGaRKeGgoNCqXHLrfBRfyWh4WT6
14vWo67QCcWy6ET1Be7fsF4RW1QWNoJTwv
19yKfxN1xCcuk9nC6nDSV4PbpQifudjP4r
15mBZw6cjujDh61NBQu3pton78RAxdugmN
1MJ7EF8cDdkJY2YEYDJNFPiMg6oprMwb2K
1Ht1M1ndrRuKGWGuzBjxKfj6uWfrdVWQQr
1Q8mYsQhXREsHAmYWLqiD1iQjRns6pEE3v
13ViQh8GcaXHcSgwiM2szYfAHogdj2rjdu
17rgBsV5vhgFoXM67Xw9xLor5ZDG4Bbc5E
1LKbGSSZsBMixyLzKwt8k45VXY3Jxq6YBo
1Ce2FpRAgzqTPNVRE9oSTFtyHsjFQAeBwo
16jZP9v3RwoiVHYKTu89W2MvuHYHJjhV6n
1GVshgfm7dKWQaKnGfZpVfUgHMc667SSy2
16oGSr3q8H7m7mhFiRZgLZiBFPSLWxYJ6H
1MmRmJY9Kkepn98tUDw6mgRu8FDtqRv3Sq
1GcJTf4xWe8eNXmg37pJEYQz9zfynaWR1F
1EFwce8G1jEM384H4XAmgDg4oKS4CNYmjc
16EN1R3GUgTKPDbwYG8MuorjebKBqRfQQC
1L76oj8piiQjZTX81LvJTY8nqJCRQme24M
19YgjvW48TFLh7VDx4kqtoQdUntr6nbwvb
1M4Px4n2mudnCvMur56MgJmBoVmJBsUE1e
1BP5oZMunWkn4AumtVidxvSgdprMtc7TiS
14rh6vEzfpCz7KhiiMnBVFDPbSDtk5XhU8
11bUZzLby1Z1SAgS9UcHC3V2FXLTkJ5u73
1QBWU6Wzg7ER9ryiTqDsxsj452m7bMnGwK
13XPKVAR7AWzoiN1Pph7fGjcx7o1iMP6KK
16Fc6U3K9YBToqifj43jpiqynj7ug3MNye
1DwMrunRyaYPq94577j7Kj6zBf3uLhZDpW
18eWPzRWH12L4CmdeBc66eimdAKeyZWSi6
1N1VFUQLdQp6L2Z25H4zswoxc5L8NppSSJ
1K8F2dzKzvxixkMQhb8dq7LBCuKxCPFgW8
11Eqw5T99VsNtSzjBTrWGQHPsRrk4RmB2B
18LzGvrFokVvWZJAWw5wDsaErX5VrovGeQ
137DULuj5JhNc9V3Q4MEi1AJQX65QAG4xf
1EZp1rmPjBhZ5FvuAvfUqrZWM3uoF8p3h8
12pL3fwPGz9GsVE8L8v5agiQDpZhWYHGXV
1KxJd5v5orAoFuSkdUZSXc4UXmDa95bAND
1HjzgWVCkCXYW6LWX8THBtNwbKbYxUdpFe
1BfSfnbz7hbSgcXerakXuyf7FHRKcmpJcA
1GJFN1SN8Y9SJdSDK16uzGjV5wsGmEgMvn
1FAkUHN2rzf2PvLJ1E4NZ6r7zZsjw7Xa32
12LwQUq9HKsbaHmtPH46NgABYcp8A3sXWB
11FNssaGrVp9amTvi8sG6qb7mZB4d1VQYQ
1BrXK4M4c6xihr3gJj5mBht6xVoFzgtFvK
11D1dSTNJdhfpAf98USCJdUJp3917q3TJy
152SqwUX8R6PoEmJkxprU8Hr3GGbF5QpPn
1PRQk473DBQrdBhgAY6GcTXeezkyhPqvBx
1Hd3F12RoDQfHYShYBKPDC4NrxyPmk24Ne
1K5oHkRCZJeLB7p1E8yMEa4X7LAz3fbsCU
18Vv4whHTnGAe4f582trW4fLz3T3RUFhnC
1DP4bm1xBkKaRMcmZk996hsYSXcfmxH687
16TxHT4Par4xrKEoTYUDGGqcmZhBijTC2q
1CeADvshNvXVoxw1t1nqhwczYh5CefvuJB
1N5iVMVEEv6G2iSmJFPrPZ4mxkBCFdCmkA
14Z6Qa7Z1QNUTmEP5LkAjsXDzy151Jbwya
12ALSWvaVPekEkDWc5CrDDZvtSpDiWnWM8
1BG5Rbhc88VFLGCk5S3AmumgCa2ro1y1uz
17oFBQJau137iTPjkzyzayvTm7Wouu5DGn
1Ghu4ACM8UGtFxUmGx4BSJ3cA4hkB1iafy
1AcPdXqmJw67Mf6KvMo6d2iPZXoWLN2snM
18etxowpqFzYVbh2DwikcRvijfBZ6VWvjC
1D6FXvnELTfXSsZ8H5MSdfxFMofq1n4LBy
1JbkiKFGEqDHje1wSfHwiRbfxsbodmTK5s
1HCPvWwBuUp7wqY69pgVeQZVv7KWj2foTC
15QeFbpe3o1rweuB4vHFG6FZHwZw6SKTe6
1EScB6WzkeDVUZwLSsAHxUNuRr8jN38MLm
17sUs5wQ9VrqxNwVg2ZGu2f77XW8QWzbAF
1MTvpvsZgjsWK588kgvm9RS35MQW46eyAW
1Ah5SFitc1zeWFck4CAdFaheAdU5RxiGq7
1M3z9w1tGaRKeGgoNCqXHLrfBRfyWh4WT6
14vWo67QCcWy6ET1Be7fsF4RW1QWNoJTwv
19yKfxN1xCcuk9nC6nDSV4PbpQifudjP4r
15mBZw6cjujDh61NBQu3pton78RAxdugmN
1MJ7EF8cDdkJY2YEYDJNFPiMg6oprMwb2K
1Ht1M1ndrRuKGWGuzBjxKfj6uWfrdVWQQr
1Q8mYsQhXREsHAmYWLqiD1iQjRns6pEE3v
13ViQh8GcaXHcSgwiM2szYfAHogdj2rjdu
17rgBsV5vhgFoXM67Xw9xLor5ZDG4Bbc5E
1LKbGSSZsBMixyLzKwt8k45VXY3Jxq6YBo
1Ce2FpRAgzqTPNVRE9oSTFtyHsjFQAeBwo
16jZP9v3RwoiVHYKTu89W2MvuHYHJjhV6n
1GVshgfm7dKWQaKnGfZpVfUgHMc667SSy2
16oGSr3q8H7m7mhFiRZgLZiBFPSLWxYJ6H
1MmRmJY9Kkepn98tUDw6mgRu8FDtqRv3Sq
1GcJTf4xWe8eNXmg37pJEYQz9zfynaWR1F
1EFwce8G1jEM384H4XAmgDg4oKS4CNYmjc
16EN1R3GUgTKPDbwYG8MuorjebKBqRfQQC
1L76oj8piiQjZTX81LvJTY8nqJCRQme24M
19YgjvW48TFLh7VDx4kqtoQdUntr6nbwvb
1M4Px4n2mudnCvMur56MgJmBoVmJBsUE1e
1BP5oZMunWkn4AumtVidxvSgdprMtc7TiS
14rh6vEzfpCz7KhiiMnBVFDPbSDtk5XhU8
11bUZzLby1Z1SAgS9UcHC3V2FXLTkJ5u73
1QBWU6Wzg7ER9ryiTqDsxsj452m7bMnGwK
13XPKVAR7AWzoiN1Pph7fGjcx7o1iMP6KK
16Fc6U3K9YBToqifj43jpiqynj7ug3MNye
1DwMrunRyaYPq94577j7Kj6zBf3uLhZDpW
18eWPzRWH12L4CmdeBc66eimdAKeyZWSi6
1N1VFUQLdQp6L2Z25H4zswoxc5L8NppSSJ
1K8F2dzKzvxixkMQhb8dq7LBCuKxCPFgW8
11Eqw5T99VsNtSzjBTrWGQHPsRrk4RmB2B
18LzGvrFokVvWZJAWw5wDsaErX5VrovGeQ
137DULuj5JhNc9V3Q4MEi1AJQX65QAG4xf
1EZp1rmPjBhZ5FvuAvfUqrZWM3uoF8p3h8
12pL3fwPGz9GsVE8L8v5agiQDpZhWYHGXV
1KxJd5v5orAoFuSkdUZSXc4UXmDa95bAND
1HjzgWVCkCXYW6LWX8THBtNwbKbYxUdpFe
1BfSfnbz7hbSgcXerakXuyf7FHRKcmpJcA
1GJFN1SN8Y9SJdSDK16uzGjV5wsGmEgMvn
1FAkUHN2rzf2PvLJ1E4NZ6r7zZsjw7Xa32
12LwQUq9HKsbaHmtPH46NgABYcp8A3sXWB
11FNssaGrVp9amTvi8sG6qb7mZB4d1VQYQ
1BrXK4M4c6xihr3gJj5mBht6xVoFzgtFvK
11D1dSTNJdhfpAf98USCJdUJp3917q3TJy
152SqwUX8R6PoEmJkxprU8Hr3GGbF5QpPn
1PRQk473DBQrdBhgAY6GcTXeezkyhPqvBx
1Hd3F12RoDQfHYShYBKPDC4NrxyPmk24Ne
1K5oHkRCZJeLB7p1E8yMEa4X7LAz3fbsCU
18Vv4whHTnGAe4f582trW4fLz3T3RUFhnC
1DP4bm1xBkKaRMcmZk996hsYSXcfmxH687
16TxHT4Par4xrKEoTYUDGGqcmZhBijTC2q
1CeADvshNvXVoxw1t1nqhwczYh5CefvuJB
1N5iVMVEEv6G2iSmJFPrPZ4mxkBCFdCmkA
14Z6Qa7Z1QNUTmEP5LkAjsXDzy151Jbwya
12ALSWvaVPekEkDWc5CrDDZvtSpDiWnWM8
1BG5Rbhc88VFLGCk5S3AmumgCa2ro1y1uz
17oFBQJau137iTPjkzyzayvTm7Wouu5DGn
1Ghu4ACM8UGtFxUmGx4BSJ3cA4hkB1iafy
1AcPdXqmJw67Mf6KvMo6d2iPZXoWLN2snM
18etxowpqFzYVbh2DwikcRvijfBZ6VWvjC
1D6FXvnELTfXSsZ8H5MSdfxFMofq1n4LBy
1JbkiKFGEqDHje1wSfHwiRbfxsbodmTK5s
As an example, 11bUZzLby1Z1SAgS9UcHC3V2FXLTkJ5u73 is an address that is not in my address book. And interestingly, a google search turns up nothing but this post, indicating that once again, you're somehow getting addresses that don't exist in the blockchain yet.
Hmmm...
Sub.
(Forum admins: please install the SMF Bookmark Mod to avoid these noisy "sub" posts.)
(Forum admins: please install the SMF Bookmark Mod to avoid these noisy "sub" posts.)
Now what you need to do is group addresses based on the inputs and create a list of "wallets" in the same fashion. I have a tool that does that, to a point...
It already does that: that's what the "closure" callback does.
As a matter of fact, second teaser: here's the transitive closure of the Linode hack address
where slush lost BTC 3K+ (all these addresses are controlled by the same person).
Edit : changed it to look like usual addresses instead of hash160
Code:
Starting method "closure" on whole block chain
Building address equivalence graph ...
done.
Clustering 3824484 addresses ...
done.
Showing address cluster for address eb1379c139bc2cd4cbfad64803e4b1a3738c85cd
113ym88TLsNUgQomGpVP97K1kwVLGk5r7V
11ikGgzoMdHAED9zW4NXFAN2ftDqvnABuq
11j58CBch6wHCDAVNCsckgHvDz6kD9aNHq
11k4H81T4ZRRDV7gFDcpfq2YcrSHp8AHrS
11kC2MhWdJyasnAQXRNzq3aUYxS5RZCESz
11kuSZPHuN7xCVtDSaow2UKLbJ3hX8T93Q
11LmyEU8KHVLj7rpE2zowZ5Je6WWtCJMhG
11ND26Juq3MkR7idBvqoJpxH3TppmbAYcR
11VinxmU2KPe2VkPaw8ouMNqSn8fqZNcfX
11W3eKv1E91P78tySdsgjtXfSN1DV1PNfc
12fDonKoU5hFpSJsFLEFRYrA3fVhCwEzDy
12oDTWFdtYwyUJfM1kGKcb3boQPxajgD58
12T5J1miwQgTK7mkqAhKm9nbdxMFP6SCE9
12XawgQWSrJFXwyoFtYdH5YBdkRBZMJ6oY
12yThcNZMuh8DQmw8MfX3vsdf89A5rMMec
131FBNVNsbzNwdh6uem9S9UBME3oiyiKT7
131ULLsD2zN7AB9KMuA9gH6vGv8QSoF39s
13DSq3J6u73rw9z5zXc2XBjSbZyZ5xarMQ
13JkZtPevDBeY6BNigxVrWQBuFBrqap927
13sxza6sdLr6qzEDA4raCZSbSGUq795wm7
145zQpb3wrJivNFQXpnxdEwjrisismDJLQ
1464JjjmsVfynGEykPVoKdmp1ChmYj7GsW
14fq1GqCLX4YayWz9pWiUoyBicCtLaMsGh
14J2Pkyne7XbCoT4aHsvUXM6913A4kNcwc
14NswevWjkamPqX4uQZatvYLGyvpLCpxsS
14ubFfgCjfKWts9wq9pGjGAtfvzi5ikrpm
151kxrqcoiquNUmkubCHFF1U7yEe72fnRz
15c3bKSX1UhuuSntNCUsWsBvzKxPw2PWW5
15gwFHzpTvAjFsJPDHG2QDwkQHYg9nSn3p
15mfn3efeGjmDZQEc5SZxXVqM3TLEDSk4d
15PW28638KQLFLWN64DyFXL9FkbSomBoP2
15RJx3MuMQY7kwmoP3yM8Fhc18c8XF54VA
16B31S2Q7oUsTnS1W65ycEnoRCeWEc3yVv
16Fieafx2vMyeqpkoBWaWXvNLf6BsrpuCM
1768xp9WcjTigs1H9XNdXq9nCfbCmZkz9V
17SDJ7FSmriKLe9yqsbNYJ94N65MwL8NbN
17wj9yoynVvhgi11svbK6PDDxtMxhQzJzQ
17YJDc1sUBqGg1rEQk2G2eLJtBXVFaN2HB
186TtMPXXQA1AFJrL3KQj4Veku872Q3Uqu
18dseD6wzXNnh2xWZg2L4LKdzLF5LG77gX
18F48fPRZEXWC2CHUvHbeeGUc16DPz6ByV
18NUp8Faisnip5MDTP7Xah7CzdPCFtJBWy
193SkpewDQXavnfxSJL2wecnx8udaTvWqP
19EJp2xvst7DrKmRyyLNK2xRsmeA3KkEXN
1ANL1cBJqdcaGxGCmsDc7e9xYGLeqsNkR9
1AUrDgnJ4qhA4eUaX2UPFUMpPmsNY6FeoH
1AWHAN6WySSCWir71YNSzGYfMDFA3qEUzb
1AxMp2swgVKbycg5sgNwwCh59PKhSQ7Bji
1B1tvB5mR8AdMxfY88P3EYQqic1vnPgvHP
1BDoXc5F4c3B7xhq9Ti67vTKGBL4VvuGee
1BYgT1Aa8uqepeDUDwygC1wKQQVA7iHLUr
1BZZYQrzUHEpSiJYFPGvZi2aGBCY1mhUvr
1CDcfFif32Eqnr1rZRRyJe9jvYS1wWMgrD
1ChYdQGcrXUmbjfXnKX5Ws8NC7QVgCMnsf
1CjLmm25ty4aSjxzG8Er4qSiQ63bqaQGA8
1CnJdd97uKz72kiHgwV3FrieDVsmKVvGXN
1D68upM6ad9GDZX1XRRvouRQSBG8FTUZ64
1D7eHcVqfmMsk6oLjBy5xNmojMAeafgqFd
1DFGAm3CXhsWNxRqFDcUru3RyTaG5KRN7U
1DGxyMnGgQwjD5YTTRaCHCUrDGY7GExEsi
1DMuVKe9PKpx3dbs2b2MnXuVmLfA4drHif
1DrFr4tKxzwW8pyiaET8B6ezMR1fUbxXBm
1FdkVB5vycm5AwJPfi2TRoi7kbpuspBUYK
1FHKfBVSUpCdipCjP4xANHtho8ZGpauTay
1FuTgYeeaLTW7UofPhJ7ePvV4sNPvoSFvr
1FWQ1pCEsJ2HLccn6ZX7PjHPuwjqxXEHw3
1FxzTCyknhEMwmvZVQkWSHJPuRkTAxLcrZ
1GGPVq6s7LCL4NoKHwLfovuWib6JqXgKp6
1Gh2gFT23asTnXH5EvQN87MeK8nZwZSgbf
1H2Ez99VeyYp9mCiUkLwLq8xFLHxJZuyLq
1HVEoKcpFp6EaCDEKNj1pkCvUwKpXGeY5R
1JdYpuFFEBcS6BnRpfeJj6z4a9ha553cBX
1JHvK2NeBnw3CoK7p5Vp7MxvwPCMc59e8b
1JLBnSF8kYD5f3b6fN5vvS3NddXi4ZZdmE
1Jrw9x9jvbVW872fqjLjGdpXd8jphxuQS9
1Kd74Jb8k3XicEcomvcdHJRnJ33Y2tnZCQ
1KGWneein7cyg8enNbDWTiX9EKbZZAdLyt
1KHebJWXvyeE1YB7h1sMzzywU6g4CXAenY
1KkPGLwopJMcFvpKdNMc3ew3PBzecm3QVp
1KnFe5ZCSmR5Pqs2fchRahX6ybhJNQHnJv
1KrV7UeoAJUQjCT672MsuuE3rDjTZZNpU9
1KSuLUcAJBe4Q75NJimYMBM1j7g272EJJc
1KUUQccsbw4thehTw1VeeyyE3T8225LBCC
1L1Y4H1scyWZCHmx2gXiM2guL7wR3zxmRB
1L7NR1yebk1KDNz3u1bK2cYNAspf2CGjL5
1LNXcXnYqyEB1vssC5s91hLj8yxFT4Rki8
1LubDSX88v16HSTHPZAgC9spSAoDz5bnwz
1LVpFavdTY2DHXExuC1JADh8kKMSz8ZBEo
1M7KnJG7Qe7Ymu4EsfEdPoU8jJv3tRvMBP
1MCPC3YfSG91FF9U2ndntUq1rBDFUHsV8Y
1MDQzpxEjFBt9cX8A8Lhr2a5taJynKCy5Y
1MdzcSx5bYxUPvFTKNHp5v7P7UbqiMHqKv
1MHqULM4JiMUYf9o9v19rMEJhxrhcUjHLV
1MisTTJvY7G1kWLG6vtHBMGDZKAwBfSiUB
1MKR29gF8YiF22FHZeQ5NeVVaN3F1Dewz9
1MSNDH4qWyps9Ch4z8WMk5kEDJJUXyZxt7
1N4D6E6ot99iTKNRprD6qqdu5vH6E2tVCj
1Njy6vDn8F163PhHvm744w6ehw5jj8bpzT
1NRy8GbX56MymBhDYMyqsNKwW9VupqKVG7
1NvrDeRNQ4be58s16tLvrEJGQPdrkakEpq
1P1y6bQ4psazd93XdvLMYuQGuEGyxqYM6G
1PubqviWyeYy9khFWZsGQ8g44tTSgBeRVq
1PY1emk6tJjtq6LAUSY3cbvBLJtQwpxk1c
1Q58P9vnMY3dfCeaftioox57V5NAJ9SQiE
1QGkj282ZygUnJq6XSfuzLhWscj2qRRjEF
1QKmhLwdstrEDxdyyzwirvEDGFGKu31xeF
Done in 20.621 seconds
The C++ utilities I wrote for Armory are almost that fast (but in linux only, have no idea why windows is so damned slow!). I buffer blk000X.dat into RAM 50 MB at a time, and then pass around pointers to this data and scan it directly -- to avoid any extra copies. It's a lot of pointers...
Looks like you went and re-did by hand pretty much what
the OS does for free when you use memory-mapped files ...
I used memory-mapped files in version 0.60 to 0.77 of Armory. Not only was it slow as dirt in Windows (though it worked brilliantly in Linux), it won't work on any 32-bit systems once the blockchain reaches 4GB+. 32-bit processes can't allocate enough virtual memory. Hell, Win32 wouldn't take it at all even with 4 GB RAM, and a 1 GB blockchain (hence why Armory never worked in Win32). Not only that, but mmap is OS-dependent. If you want to use Map-Of-File-Views (the mmap equiv in Windows) you're going to deal with windows.h and LPWCSTRs.
I'm so glad I got rid of that. That's why I emulate it now, and it cleaned up my code a bit not having to branch base on OS.
I understand about the python wrappers. You don't have to use the python, there's a pure C++ library underneath, though it's not obvious how to use it. BlockUtilsTest.cpp has a lot of examples, but it's not intended for educational purposes: it's really for me to do my unit-testing.
And in the end, I always approve of people digging in and implementing pieces of Bitcoin. There's no better way to really undrestand it.
Also, want to run it on my public address? I am curious what other addresses are correlated with it... If not, that's fine, I'll download it and attempt to compile myself.
If not, that's fine, I'll download it and attempt to compile myself.Here you go.
Even translated the result to the usual format.
I'd be curious to see if it worked. Let me know.
Code:
18TKNbSLTrd3a2W8mtoH5uNzFhWRWNcuHU
1HCPvWwBuUp7wqY69pgVeQZVv7KWj2foTC
15QeFbpe3o1rweuB4vHFG6FZHwZw6SKTe6
1EScB6WzkeDVUZwLSsAHxUNuRr8jN38MLm
17sUs5wQ9VrqxNwVg2ZGu2f77XW8QWzbAF
1MTvpvsZgjsWK588kgvm9RS35MQW46eyAW
1Ah5SFitc1zeWFck4CAdFaheAdU5RxiGq7
1M3z9w1tGaRKeGgoNCqXHLrfBRfyWh4WT6
14vWo67QCcWy6ET1Be7fsF4RW1QWNoJTwv
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What does 0x80ab5bcd943419b8988234e8e19b83389edc542a mean? It's not a Bitcoin address in the typical format.
Yeah, sorry about that, I should have dropped the 0x in front. Once
you remove the 0x, it's the ripemd-160 hash of the public key.
So:
. Copy everything but the '0x' , in your example, that would be : 80ab5bcd943419b8988234e8e19b83389edc542a
. Go paste that number in http://blockchain.info
. You'll land on a page that has the usual representation, in this case: 1CjLmm25ty4aSjxzG8Er4qSiQ63bqaQGA8
I have to ask though, why not display the hashed address to begin with? Just an extra step of complication?
Not sure what you mean by hashed addresses.
What I am displaying *is* a hashed address.
You mean base58-encoded addresses like "1CjLmm25ty4aSjxzG8Er4qSiQ63bqaQGA8" ?
If so, then : these things are way too expensive to compute, this was designed for spped.
Quote
Also, want to run it on my public address? I am curious what other addresses are correlated with it... If not, that's fine, I'll download it and attempt to compile myself.
Give me a sec If not, that's fine, I'll download it and attempt to compile myself. What does 0x80ab5bcd943419b8988234e8e19b83389edc542a mean? It's not a Bitcoin address in the typical format.
Yeah, sorry about that, I should have dropped the 0x in front. Once
you remove the 0x, it's the ripemd-160 hash of the public key.
So:
. Copy everything but the '0x' , in your example, that would be : 80ab5bcd943419b8988234e8e19b83389edc542a
. Go paste that number in http://blockchain.info
. You'll land on a page that has the usual representation, in this case: 1CjLmm25ty4aSjxzG8Er4qSiQ63bqaQGA8
I have to ask though, why not display the hashed address to begin with? Just an extra step of complication?
Also, want to run it on my public address? I am curious what other addresses are correlated with it...
If not, that's fine, I'll download it and attempt to compile myself. 
my mom got my wallet pasw. if you know someone who can torture my mom so she can tell the pasw i will pay 20.000 btc 
damn it. you got me 
let's share the btc and don't tell anyone. will be our little secret
let's share the btc and don't tell anyone. will be our little secret Send some love to 15uxVpSgWtfQ25ae6YYxG3US3eWRpYqKkp if that is the case.
I sure do loves me some stolen coins
To try and understand the nitty-gritty of how bitcoin works, I've
written a fairly fast blockchain parser in C++ (x86-64 ubuntu only).
It can currently do the following things:
. Compute simple blockchain stats, full chain parse (< 1 second)
. Extract all known transactions for a popular address (20 seconds)
. Compute the list of addresses that provably belong to the same person (20 seconds):
. Compute and print the balance for all keys ever used since the beginning of time (30 seconds):
. You can quite easily add your own data extraction code
written a fairly fast blockchain parser in C++ (x86-64 ubuntu only).
It can currently do the following things:
. Compute simple blockchain stats, full chain parse (< 1 second)
. Extract all known transactions for a popular address (20 seconds)
. Compute the list of addresses that provably belong to the same person (20 seconds):
. Compute and print the balance for all keys ever used since the beginning of time (30 seconds):
. You can quite easily add your own data extraction code
Nice! Mind sharing a top-level overview of how you do it? Data structures? Do you know how much that is I/O limited?
The C++ utilities I wrote for Armory are almost that fast (but in linux only, have no idea why windows is so damned slow!). I buffer blk000X.dat into RAM 50 MB at a time, and then pass around pointers to this data and scan it directly -- to avoid any extra copies. It's a lot of pointers...
please stop posting my btc addresses 
You have 8000+ coins and hack Linode
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