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Fix typos
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@ -23,7 +23,7 @@
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=== Bitcore Library Examples
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==== Prerequisities
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==== Prerequisites
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* NodeJS >= 4.x or use our https://bitcore.io/playground[hosted online playground]
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@ -388,7 +388,7 @@ The final line appears because to validate the transactions' signatures, you tec
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----
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$ tx -a 49d2adb6e476fa46d8357babf78b1b501fd39e177ac7833124b3f67b17c40c2a
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warning: transaction fees recommendations casually calculated and estimates may be incorrect
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warning: transaction fee lower than (casually calculated) expected value of 0.1 mBTC, transaction might not propogate
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warning: transaction fee lower than (casually calculated) expected value of 0.1 mBTC, transaction might not propagate
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Version: 1 tx hash 49d2adb6e476fa46d8357babf78b1b501fd39e177ac7833124b3f67b17c40c2a 159 bytes
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TxIn count: 1; TxOut count: 1
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Lock time: 0 (valid anytime)
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@ -948,7 +948,7 @@ The native segwit address format is defined in BIP-173:
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https://github.com/bitcoin/bips/blob/master/bip-0173.mediawiki[BIP-173]:: Base32 address format for native v0-16 witness outputs
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BIP-173 only encodes witness (P2WPKH and P2WSH) scripts. It is not compatible with non-segwit P2PKH or P2SH scripts. BIP-173 is a checksummed Base32 encoding, as compared to the Base58 encoding of a "traditional" bitcoin address. BIP-173 addesses are also called _bech32_ addresses, pronounced "beh-ch thirty two", alluding to the use of a "BCH" error detection algorithm and 32-character encoding set.
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BIP-173 only encodes witness (P2WPKH and P2WSH) scripts. It is not compatible with non-segwit P2PKH or P2SH scripts. BIP-173 is a checksummed Base32 encoding, as compared to the Base58 encoding of a "traditional" bitcoin address. BIP-173 addresses are also called _bech32_ addresses, pronounced "beh-ch thirty two", alluding to the use of a "BCH" error detection algorithm and 32-character encoding set.
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BIP-173 addresses use 32 lower-case-only alphanumeric character set, carefully selected to reduce errors from misreading or mistyping. By choosing a lower-case-only character set, bech32 is easier to read, speak, and 45% more efficient to encode in QR codes.
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