Hash Block Calculator Download
Berniece Rybacki
A blockchain is a chain of individual blocks where every block consists of header and body. The body is the list of all transaction done by the creator of the block while the header consists of the identification details used to prove the validity of the block and transaction. The header of each block comprises the following six parameters used to create the hash of the block:
The input values need to be in little endian hexadecimal format. So, when taking the values from a block explorer we might have to convert them form decimal to hexadecimal (usually big endian) and subsequently into little endian.
Bitcoin mining uses the hashcash proof of work function; the hashcash algorithm requires the following parameters: a service string, a nonce, and a counter. In bitcoin the service string is encoded in the block header data structure, and includes a version field, the hash of the previous block, the root hash of the merkle tree of all transactions in the block, the current time, and the difficulty. Bitcoin stores the nonce in the extraNonce field which is part of the coinbase transaction, which is stored as the left most leaf node in the merkle tree (the coinbase is the special first transaction in the block). The counter parameter is small at 32-bits so each time it wraps the extraNonce field must be incremented (or otherwise changed) to avoid repeating work.The basics of the hashcash algorithm are quite easy to understand and it is described in more detail here.When mining bitcoin, the hashcash algorithm repeatedly hashes the block header while incrementing the counter & extraNonce fields. Incrementing the extraNonce field entails recomputing the merkle tree, as the coinbase transaction is the left most leaf node. The block is also occasionally updated as you are working on it.
The body of the block contains the transactions. These are hashed only indirectly through the Merkle root. Because transactions aren't hashed directly, hashing a block with 1 transaction takes exactly the same amount of effort as hashing a block with 10,000 transactions.
The compact format of target is a special kind of floating-point encoding using 3 bytes mantissa, the leading byte as exponent (where only the 5 lowest bits are used) and its base is 256.Most of these fields will be the same for all users. There might be some minor variation in the timestamps. The nonce will usually be different, but it increases in a strictly linear way. "Nonce" starts at 0 and is incremented for each hash. Whenever Nonce overflows (which it does frequently), the extraNonce portion of the generation transaction is incremented, which changes the Merkle root.
Moreover, it is extremely unlikely for two people to have the same Merkle root because the first transaction in your block is a generation "sent" to one of your unique Bitcoin addresses. Since your block is different from everyone else's blocks, you are (nearly) guaranteed to produce different hashes. Every hash you calculate has the same chance of winning as every other hash calculated by the network.
For example, this python code will calculate the hash of the block with the smallest hash as of June 2011, Block 125552. The header is built from the six fields described above, concatenated together as little-endian values in hex notation:
Note that the hash, which is a 256-bit number, has lots of leading zero bytes when stored or printed as a big-endian hexadecimal constant, but it has trailing zero bytes when stored or printed in little-endian. For example, if interpreted as a string and the lowest (or start of) the string address keeps lowest significant byte, it is little-endian.
Conclusion: Use eth.getBlock(). Take the object it returns as output. Remove unwanted elements and keep only those that are inputs to a blockHeader. Convert numbers to Hex and handle values with 0s.Restructure the object to form an array of strings.Pass this array into a rlp.encode function.Take the rlp output and apply a keccak256 hash on it.
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First lets follow the Python example given in the Block hashing algorithm at _hashing_algorithm, which calculates the block hash of Bitcoin Block 125552, -testnet/block /00000000000000001e8d6829a8a21adc5d38d0a473b144b6765798e61f98bd1d.Note that I had to replace string decode() and encode() with binascii.unhexlify() and binascii.hexlify() on my Python installation.
If you have many miners, then you can multiply the hash rate and power consumption by the number of miners you have. Or just fill the form in for one miner, and then multiply that number by the number of miners you have.
The Bitcoin price is rising at slightly less than 0.3403% per day on average over the past year. We suggest you enter a custom Bitcoin price into our calculator based on what you expect the average price to be over the next year.
50 BTC per block may seem high, but it is important to consider the price of Bitcoin at that time was much less than it is today. As the Bitcoin block reward continues to halve, the value of Bitcoin is predicted to increase. So far, that trend has remained true.
The higher the hash rate of an individual Bitcoin mining machine, the more bitcoin that machine will mine. Typically, a higher hash rate requires more energy, but that is not always the case. Some machines have the same hash rate but require different amounts of energy to power. That's because one may be newer and therefore more efficient with its power consumption.
Difficulty is a variable that determines how hard it is for a miner to find a block. It is adjusted up and down algorithmically by the Bitcoin network based on the network-wide hash rate - the sum of all miners' hash rates on the entire network.
Disclosure: Mining metrics are calculated based on a network hash rate of 346,968,946,852 GH/s and using a BTC - USD exchange rate of 1 BTC = $ 26,026.50. These figures vary based on the total network hash rate and on the BTC to USD conversion rate. The block reward is fixed at 6.25 BTC. Future block reward and hash rate changes are not taken into account. The average block time used in the calculation is 599 seconds. The electricity price used in generating these metrics is $ 0.12 per kWh. Network hash rate varies over time, this is just an estimation based on current values.
remote file duplicati-b9726ce8a1b9a43d7b027f1b28049d50e.dblock.zip.aes is listed as Uploaded with size 621805568 but should be 786287405, please verify the sha256 hash "zsWsgxkwU7xcE51TLVhd/g9eNzr5J/ITbrIGA2kxtOs="
I'm trying to use this logic to recreate the merkle root for block #100000. There are 4 transactions in this block. I start by copying the transaction hash for the coinbase transaction and the one following back-to-back into a Sha256 calculator to get the hash. Then I hash that hash one more time: Sha256(sha256()). I repeat that procedure one more time with the second two transactions in the block. Finally, I repeat the procedure again using the resulting hashes to obtain the Merkle Root. Unfortunately, this doesn't tie to the Merkle Root shown in the block header at blockchain.info.
The complete hash is 01000000010000000000000000000000000000000000000000000000000000000000000000FFFFFFFF4D04FFFF001D0104455468652054696D65732030332F4A616E2F32303039204368616E63656C6C6F72206F6E206272696E6B206F66207365636F6E64206261696C6F757420666F722062616E6B73FFFFFFFF0100F2052A01000000434104678AFDB0FE5548271967F1A67130B7105CD6A828E03909A67962E0EA1F61DEB649F6BC3F4CEF38C4F35504E51EC112DE5C384DF7BA0B8D578A4C702B6BF11D5FAC00000000
to build the tree the steps are simple, just make sure you calculate the hash correctly, so I suggest you test first on the hash functions and then on the tree construction, to avoid unnecessary loss of time in trivial errors
We are hoping to anonymously track parking behavior in several two-hour parking areas by reading license plates at various times in a day and recording how often individual vehicles move. I believe we should be able to do this with python code that reads each license plate and saves it as a variable containing random characters. Then, if is reads the same license plate later in the data set, it will "remember" it and change it to the same set of characters. We should do this for both the "State" Field and the "Number" field. I think I should be able to do this in the field calculator.
That would almost work in a CalculateField code block. The license plate comes into the function as "a", and a.encode() is doing some conversion thing to the string so that it's acceptable to hashlib. That is "a" is the string variable that will have the original license plate in it.
TL;DR About the math, the function is one-way, which means with the same input it should always produce the same output, but it can't go the other direction. Given the hash you can't get the license plate. They use this for storing passwords. When you log in, the password you type gets pushed through the hash function, and then the result is compared with the stored hash from a table or database. If they match, you typed it correctly, but anyone who steals the password table cannot see your password. This is why sysadmins say "I can reset your password for you but I can't tell you what the old one was."
Thanks for this! I should have mentioned that I am a beginning python user and so I'm not exactly sure where and how to enter this code. I've attached a screen shot of a sample data set, and I was hoping to enter the code in the field calculator; would it look like this?:
Also, my dataset would have several features with the same license plate but different time stamps. Would the code "remember" each license plate and change it to the same string as before? Is that embedded in the code that I would be importing when I "import hashlib" at the beginning?
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