我写了一个simple script，找出给定info_hash的示例对等IP。我无法在BEP-0005中看到这种信息：我如何从DHT中获取torrent文件？
答案 0 :(得分：4)
DHT不提供种子。它只是为各个信息提供对等列表。 Torrent文件，或者更确切地说是不可变信息字典，由bittorrent群本身提供。
您必须部分实施BEP3，BEP10，最后BEP9才能执行元数据交换。另外，实施BEP29和BEP11可以提供改进的连接，这在检索小群组上的元数据时非常有用
其次，消耗DHT的资源而不提供任何或反复锤击节点的请求 - 尤其是引导节点 - 被认为是不礼貌的。如果您打算获取大量torrent文件，则应将DHT节点作为守护程序运行，例如通过Juliusz Chroboczek的dht lib（C）或mine（java）。我的实现还包含元数据检索服务。 libtorrent还应提供实现相同目标的所有必要部分。
答案 1 :(得分：-1)
这是一个base64编码的.pcap文件，它在实践中显示了完整的通信（注意最后一个数据包）。对它进行解码并在Wireshark中打开将向您显示完整的流程 - 结合8472答案中列出的BEP，这可以作为一个例子。
Cg0NCnQAAABNPCsaAQAAAP//////////AwAbAExpbnV4IDQuNy43LTEwMC5mYzIzLng4Nl82NAAEAC
0ARHVtcGNhcCAxLjEyLjIgKEdpdCBSZXYgVW5rbm93biBmcm9tIHVua25vd24pAAAAAAAAAHQAAAAB
AAAASAAAAHEAAAAAAAQAAgADAGFueQAJAAEABgAAAAwAGwBMaW51eCA0LjcuNy0xMDAuZmMyMy54OD
ZfNjQAAAAAAEgAAAAGAAAAbAAAAAAAAABePwUAEVBWkkwAAABMAAAAAAQAAQAGvF/0eXJ3AAAIAEUI
ADwSdEAAQAYV/QoFtU4FT02hviznAcLkEQgAAAAAoAJyEEblAAACBAW0BAIICgAwA3wAAAAAAQMDB2
wAAAAGAAAAbAAAAAAAAABePwUAS9dWkkwAAABMAAAAAAAAAQAGAAFcmVhFAAAIAEXIADwAAEAANgYx
sQVPTaEKBbVO5wG+LJHhxT3C5BEJoBKpsBhCAAACBAW0BAIICowrE6cAMAN8AQMDB2wAAAAGAAAAZA
AAAAAAAABePwUAftdWkkQAAABEAAAAAAQAAQAGvF/0eXJ3AAAIAEUIADQSdUAAQAYWBAoFtU4FT02h
viznAcLkEQmR4cU+gBAA5e+2AAABAQgKADADn4wrE6dkAAAABgAAAKgAAAAAAAAAXj8FALnXVpKIAA
AAiAAAAAAEAAEABrxf9HlydwAACABFCAB4EnZAAEAGFb8KBbVOBU9Nob4s5wHC5BEJkeHFPoAYAOWS
fwAAAQEICgAwA5+MKxOnE0JpdFRvcnJlbnQgcHJvdG9jb2wAAAAAABAAAS8LTqkWlonb4v9JQHUAwB
V1zWOiLWx0MEQ2MC0S839rfuHUu/yML4eoAAAABgAAAGQAAAAAAAAAXj8FADBgV5JEAAAARAAAAAAA
AAEABgABXJlYRQAACABFyAA01vVAADYGWsMFT02hCgW1TucBviyR4cU+wuQRTYAQAVTu3wAAAQEICo
wrE8sAMAOfZAAAAAYAAAAgAQAAAAAAAF4/BQDwYVeS/wAAAP8AAAAAAAABAAYAAVyZWEUAAAgARcgA
79b2QAA2BloHBU9NoQoFtU7nAb4skeHFPsLkEU2AGAFUnnoAAAEBCAqMKxPLADADnxNCaXRUb3JyZW
50IHByb3RvY29sAAAAAAAQAAEvC06pFpaJ2+L/SUB1AMAVdc1joi1sdDBENjAtinilZ4eOkwl3Zn+F
AAAAbhQAZDE6ZWkwZTE6bWQxMTp1dF9tZXRhZGF0YWkyZTY6dXRfcGV4aTFlZTEzOm1ldGFkYXRhX3
NpemVpMzgzOWUxOnBpNTkxMzdlNDpyZXFxaTIwNDhlMTp2MTc6bGliVG9ycmVudCAwLjEzLjZlAAAA
GQUAIAEAAAYAAABkAAAAAAAAAF4/BQAcYleSRAAAAEQAAAAABAABAAa8X/R5cncAAAgARQgANBJ3QA
BABhYCCgW1TgVPTaG+LOcBwuQRTZHhxfmAEADt7mcAAAEBCAoAMAPDjCsTy2QAAAAGAAAAyAAAAAAA
AABePwUAgGJXkqUAAAClAAAAAAQAAQAGvF/0eXJ3AAAIAEUIAJUSeEAAQAYVoAoFtU4FT02hviznAc
LkEU2R4cX5gBgA7RBfAAABAQgKADADw4wrE8sAAABSFABkMTptZDExOnV0X21ldGFkYXRhaTJlNjp1
dF9wZXhpMWVlMTpwaTQ5MTY0ZTQ6cmVxcWkyMDQ4ZTE6djE3OmxpYlRvcnJlbnQgMC4xMy42ZQAAAA
AAAAADCRrhAAAAyAAAAAYAAAB8AAAAAAAAAF4/BQB54leSXAAAAFwAAAAAAAABAAYAAVyZWEUAAAgA
RcgATNb3QAA2BlqpBU9NoQoFtU7nAb4skeHF+cLkEU2AGAFU7d4AAAEBCAqMKxPsADADw/////////
//////////////////////4HwAAAAGAAAAZAAAAAAAAABePwUARXtYkkQAAABEAAAAAAQAAQAGvF/0
eXJ3AAAIAEUIADQSeUAAQAYWAAoFtU4FT02hviznAcLkEa6R4cYRgBAA7e2FAAABAQgKADAEC4wrE+
xkAAAABgAAAGQAAAAAAAAAXj8FAOaCWJJEAAAARAAAAAAAAAEABgABXJlYRQAACABFyAA01vhAADYG
WsAFT02hCgW1TucBviyR4cYRwuQRroAQAVTtPQAAAQEICowrFBUAMAPDZAAAAAYAAACEAAAAAAAAAF
4/BQAUg1iSYwAAAGMAAAAABAABAAa8X/R5cncAAAgARQgAUxJ6QABABhXgCgW1TgVPTaG+LOcBwuQR
rpHhxhGAGADtUoEAAAEBCAoAMAQMjCsUFQAAABsUAmQ4Om1zZ190eXBlaTBlNTpwaWVjZWkwZWUAhA
AAAAYAAABkAAAAAAAAAF4/BQDZDVmSRAAAAEQAAAAAAAABAAYAAVyZWEUAAAgARcgANNb5QAA2Blq/
BU9NoQoFtU7nAb4skeHGEcLkEc2AEAFU7LEAAAEBCAqMKxQ5ADAEDGQAAAAGAAAAbAAAAAAAAABePw
UA/w1ZkkoAAABKAAAAAAAAAQAGAAFcmVhFAAAIAEXIADrW+kAANgZauAVPTaEKBbVO5wG+LJHhxhHC
5BHNgBgBVMl0AAABAQgKjCsUOQAwBAwAAA8tFAIAAGwAAAAGAAAAZAAAAAAAAABePwUADw5ZkkQAAA
BEAAAAAAQAAQAGvF/0eXJ3AAAIAEUIADQSe0AAQAYV/goFtU4FT02hviznAcLkEc2R4cYXgBAA7ezu
AAABAQgKADAEMIwrFDlkAAAABgAAAAwGAAAAAAAAXj8FAFsRWZLsBQAA7AUAAAAAAAEABgABXJlYRQ
AACABFyAXc1vtAADYGVRUFT02hCgW1TucBviyR4cYXwuQRzYAQAVQfdQAAAQEICowrFDkAMAQMZDg6
bXNnX3R5cGVpMWU1OnBpZWNlaTBlMTA6dG90YWxfc2l6ZWkzODM5ZWVkNjpsZW5ndGhpMTIyMDExND
JlNDpuYW1lMzU6VWJ1bnR1IFRoZSBDb21wbGV0ZSBNYW51YWwgMjAxNi5wZGYxMjpwaWVjZSBsZW5n
dGhpNjU1MzZlNjpwaWVjZXMzNzQwOvq1ayK6Etm4T4hmMT8z0PsZ+HPTtomCPusw+v/ZxRxS35MlyX
XC/uwHO1w0tocuYw3toTL211a5Zz6aJfJfE+Vh2S7XL2UdLB6c5ND6S6t8im5XB7fwW80o0VTem7Vr
dT2P2W7cE8bxZuMKMPNGMfsLKr5nu8f8Aig7o7qOibzwY2LeeM9iohbmYdM+mM4g3n1DMPqYbKUV5y
I6RCHFpRnu8U2JsY4bEmVIPKHQxrjI+Q0tg7gfkEw4SRA1X5SHJbuDpPoudniZbvF9DO7XpEEIYdR8
BNquTogPOT5ooNJPJI/v1INvXmKrGBnmtt/paHpZWU0Gl8JcHHl7BZq0RsG7T5JteHWfNo/sqWqLmr
svZIAsfF2MdTL7r2zp5pUfuIRtQeEjV9Dtja0fTqbx4IhSx3gox+s2OqWOLURMDY+UDEhXn9Ie8fsu
kn+XRI+ihlwOAq8bunAQdgun8apPI7aBS5LAvjrQED/jf42qaKwe4Leq8fSQM4rT1CPnt/hlyp9EYO
L434AGq9a4D+55o+tB6jXTAobqiApOegIWi4aj+dzWXIokLrMcUKC8ZHT+UPFR7woWIEMb0PfGYNVI
Op/nh0t4CMGo1/Jtjd1yJ/AUx2v6d+/IMv+kx2uEDMxZLwSTCdhJ+xgO5uHq3UlATqkgfmBI0RUF3D
ML/eMqBfa6/+nWyfBYyt1/uD0JMLqqSbZQkFpq/VOE5Na7nnHy6T/5Oq1hliB6GmENzWsmUYvy+BS+
+it6J35CkAaZC7Vo7k8Ct5xcxbdpL1gnn2mJsy+PGci9JMVueIwcLDUqI193Vt6xFSxpM5/s0dHDA0
SmCXDOqIvy9Abc3WSBk49ajMvEbV4iZJRdRUSDI/85eqSyL57+s2A1COva+Z3dFlTHfF62pYKGVjS7
+Zysxk009983GKpYedOODTCK4PmEsPEb1BNd1dWIY5Ppt0CI2A4UleJA+cTIZssEct0NsVJlzldsVT
FRbP8JcAteB+KJVXkhDQydfQkhnDwjNJvmpL9Td1V8MC4Jeue3jY47pWjewjHEg62rr4JeTnhFXDG4
GOXPCG7I2/oGyxnRsStPuV2fub1ajweOLKeT3ue9et1qor5VI81w1R5bU3Jke/r43fYRMwzeALVyzC
7UFKe4ivM5s21JwtNsZ874HhQHUZgZHa5yRfIMm/QJqVCde6JR11QeGqeDArw8brqtGLV+v/H75dOX
B1zSmbBhOsF+sEcTt0dQgoVQH50y0UDmWhgtrRoPZgTrYfI+d7DxfMRvgKlJrrv5/NvUtuIW1NA9VS
HpdjgAK4L4B8+H1goUB90SNT30tSOyf+BVL+Cy9XXlIH26X9YvJ3I3yDd36R8NLqWWF+Z095uS/XLV
j1saLWlXD+TBJG02A2jUSnP2Zsu55rc9TXqiE8NpFAY3v0E5Y57XuV02eY8NkJPbb+QWLv4p56Xn7U
0P0FUKt2J33ag/Hn7wvrcjiBtFL5YKzfzMSFM9PlyIz3qEmIa4HF+tGXfDNOc2QVes4fWEuIFr2cDI
vN/eMmbo0xPVQvWypH+4oWpXEefW7hM/v8PmdRW2/IasgYD+cXs1gi4+tU8XZpXsL1x3cKVfeRc8wM
sofjjm4hncjr8EyfJ7vdE6WQuBJsAVCbyt6GowWbQG2AWvVwzGkFlgShu8ZPo1MKAjBOLEUaUZ2Asw
zY27KFxCK7vSUXx6SuyJ7/dlWF2vv94DLlSAydydQjk114lIrvY0wrcMBgAABgAAAGQAAAAAAAAAXj
8FAIcRWZJEAAAARAAAAAAEAAEABrxf9HlydwAACABFCAA0EnxAAEAGFf0KBbVOBU9Nob4s5wHC5BHN
keHLv4AQAQTnLgAAAQEICgAwBDGMKxQ5ZAAAAAYAAAAMBgAAAAAAAF4/BQBnElmS7AUAAOwFAAAAAA
ABAAYAAVyZWEUAAAgARcgF3Nb8QAA2BlUUBU9NoQoFtU7nAb4skeHLv8LkEc2AEAFUH4IAAAEBCAqM
KxQ5ADAEDHLdrT/EhXN8cAOyCumI4uC5vOUsJtRRIo5xOfftqGRhHyrWxlHDd3UfaQMcDYfieGtTKt
w4b0zL/6EA8itJDyvGuYq6lZtpLuGEzhPeKQwgipSuqWS+cRprXUSnzu4BtISU4iUh4Rg5CF9ZdHA8
/O5s5RL0bxA7ep17d6Xyj06PPBXhBNOB21znRzRuzhM3K3ogJvPYUZzmdT/EUAt+esBn1bwRSJlPGj
+LjfdhI52vCHmawcoSNqTa2Whu1uuUCH7jxAvJDw930fobmvqOJCe+vhmjRy9lET/OgD8oh5MxZVYP
KLCLUpqrGV/A0fEfaYW40z8iDCLZUydvFeeWLd1sudAw+zBhPsiFhdleo5YYq9PgHWJmPXxKxKGinH
6XXgwacfE2ZQwZJv5lN5FsNlSQk1b2bsjjR318ocADA6co7OLZMWpilfTnM8hHHRdyEItajHRZ8Tm4
QwuzuACVj70SD8UsUHbPitIm6PIzK5153TN4L6J/iDn21+DKzum8ZlaicEqyDZTo+S0XGFHsQulZ1w
vsg+7LeV4FQTu26MWdFQIE821iMXrbutWEl+9U5/q8vjwhjhmEw8A87U4eYXF5lOld+O+F4LEEoO9+
RRfYnhxGOz70Hmi2kcWBh7qDq8cD2r5mhvqcvZzcGsO5NaTFLHtPDnaFXv5UDpMoZWnYp55BVTW9ox
mqLpxAReRuJVw+EXBqU3UMoEP602uafaPFESv/SbG37jFGfFk3FRkD7Taob7G1iyq4mg179G26BVI9
rKUCyVU22Szaz04Jce4lgypJcK5z8Y/GRNpDXIsD7xyICAii8YgIG5eoXx876iwNebqU1iVOB4sAZc
OjINKBpge6lzh2NKTvFlMJ+OOd3H4nNC8CsJWYfjpmcuMSGIGareGg2RObqKMmZQEkefK/OvJuCgfx
sGKA13sYT06E16h9vGmRFkc6+wMLc/260dUVeYUvyn9oLCtmwmFJLntxCSq0elvIIpIX3zeAy561+D
Hu5aomN3gMAg6oq+3UPXQC5jZMev8b+Q5PY/Qx1vm8eAH41SFx95LAKWUffuxefS3EXDPwAGtudN02
zAcJqpuScJ7G2cie3+aQyc2nAtd57QVayRe+8gzUL5QB8dad20GHT8XU1hgczXqox/AWEYG1ef9rqC
a4oIem6nr0liOivWLDt0dQo+eT928lF5vDMtSfD6HzsVNEcZP0pO6u+ahTBbTcfT7jhCxITq6QERt/
jQFZas7GEIHZK66OnXBeG7IMNLP0o/2WE/JPeZAvOPv61UrP9iaacifZfV8oaZ4niCKp9kQLKMRiQU
FvdDAbUJVlmA71C7WwbgSQiouuNfmHkj1LPmTUPraX7U4WF97O0QzKrLt0GCMd4L30RfA8asn+vPXv
kQ0h0M1RiPrkL90Zuww3S/wXifmh21MMopJ30WF5lu5I5BvPJ3cQ7S8g3N7fFnl63f7xdVK3v3ivh8
O6Jvbjkvtj5JWc/zV+OtTyFT7AoZWO6U0CJ+GXFzrF+8xJdlMTX0S0tLWtNr+aNk/FIVS4EMuz1mha
OW39isF6jQ+VpnQMG5Yd7Ns4Dluoriskk/OkVLOaAZZH1Ha8ozuePg/gSkp4xxagI7KhhYDWGlwfQt
l+DreFQZ//SoKPpKGGCR5wgZw7lb3d6K2ohzMww0dwKCp3qLLfrWbl7N/3metWQVBzdGhak8DJ0dPR
Bttvt+cFGmVhVFYYhbVc9YfIzhLYWoWoN/d0DO1/YI/2IFUeMlHtikODkFVD04fT+RlIiid6hwQwhb
V9Z7AMUT7JE0tyDMKW+iVN6CujHMUlp9EWB3B6OArwuFZBeyDnT+jwkp9Fhj0XiqvqtZWaBJGZeda/
WnzptQmTTf0DRATDfxFeeA9n9nbmyzZpv3BFeQuzP3WokhK3wTANIEM9F7fazn5b17y1DAYAAAYAAA
BkAAAAAAAAAF4/BQCCElmSRAAAAEQAAAAABAABAAa8X/R5cncAAAgARQgANBJ9QABABhX8CgW1TgVP
TaG+LOcBwuQRzZHh0WeAEAEa4XAAAAEBCAoAMAQxjCsUOWQAAAAGAAAAQAQAAAAAAABePwUAf5JZkh
8EAAAfBAAAAAAAAQAGAAFcmVhFAAAIAEXIBA/W/UAANgZW4AVPTaEKBbVO5wG+LJHh0WfC5BHNgBgB
VF6xAAABAQgKjCsUWgAwBDBjx12hMb4dvmVmMbnqdB/1egi6goYQGKvUhTkK8KhYiSARwDczMJ+hIH
xeJd6VeXoeQzrEOFmUPhVTjHwecpRapE77A62xzBRaQwUR4UkUeQA8hIw/BiUFL53pr7l0amBq194C
Yt9zA+P8sT36fzUVliMrPooMj6wr22owrM/b11HrpXHstrJnrmKG0LKgmYHBMNosV8DGlyWKg0OaLW
4D7zNRYGB5Mz/YE8cF+4uUyRAMkx79mUPRQDLiBNz9MnSUIfgijRD/vaL5WesP1NAf0Q+bT8d0qFpN
MmjhoeMlKnOOiZZFc4HG+gK58GrAj+uLiTbxCT6FKZIiOG/FqDU3tFrykGqzLty3eZo9kC0dRwl7OC
kM2tNQ+1tr9RIZz3NfctzVtq1vILNuiKDAzFDsXtZMwhWlzicCYqm+eSqj7BytPfyZCzT5lqmRXr68
ggGDDLqeO/YHXqpFsvR3TFQeNJdPyAAL+kHcSPTRY7+L3W3XbPUfiIJGuJrYUfwCV5+ZvEoHn3P5qt
aEb8LKXuDfzbo7z6KoC8M1ZKQA1AwX5kabF0k+lKPX5HDNLclIJQUr8RyU6k7dU2YQ3DrqdDhNFDcT
67oXb1nZSuQJkzXCzA2Mj2jZflbugup/Yx4L2l1Bw9cCUqsG4bqkAIv0OO7zjENZoALR+a6rilPceN
Sxt/p1S1Urk8NeGGD7fT6ze6PftXbtwwqQCJYrrUT+oigljbNHlcKrjRps5aB7HCWq3+8H/fpmPC5O
XDK95NPIiYm6OzUovfs+K5Q23JBmXZweZsCuSsihg0drj4k/PIFE27d2yAuRDMk80AlDbsXK6pO0Mq
mO8bUzEBbxeTvZwxyo53VwF0GPc+39AnroXf19y20NJLe/dmWcqILYCQ4KLnTOV4i6NGXm8p7/9zBA
YMAgCwtomLw+AmjyeGtZgjbQ3KZhgAsk819jXflehTXgurxg2Ss2JtYrnm+LPUqezZdzpR0G6coEGk
VQOYxgsrH3nO3f6ieXaYl/usOJsXsVcv1DOkUNTvC66worW5PWCFTX5KFhLDNSPfEYMknWsJqKpn8v
6myZDl1GM/wP8vn9z/7YKpYYm0VZpkd1T4Gr0lmt72eCNb2Sc2PZAbwx9Xd6TrOdVzM5LwdBL66HB4
y1Jsi9CRGg/RwBDkHA+UgpKror7f48BOZoI4LINF3Ty64eHXvTdrSP+NoF5JzC6yOhdl91O4ym9KB4
PGCbSX0pjfsxQec5wrdB+Wl/kzBDMb1PhKwVvSC0qMHeAcrg1BFadsNJe7ZAYUtuDsBcu0sxFEyQrJ
on8G+RO+v5HmUAQAQAAAYAAABkAAAAAAAAAF4/BQCqklmSRAAAAEQAAAAABAABAAa8X/R5cncAAAgA
RQgANBJ+QABABhX7CgW1TgVPTaG+LOcBwuQRzZHh1UKAEAEx3TwAAAEBCAoAMARSjCsUWmQAAAAGAA
AAZAAAAAAAAABePwUAd7ZZkkQAAABEAAAAAAQAAQAGvF/0eXJ3AAAIAEUIADQSf0AAQAYV+goFtU4F
T02hviznAcLkEc2R4dVCgBEBMd0yAAABAQgKADAEW4wrFFpkAAAABgAAAGQAAAAAAAAAXj8FAAo6Wp
JEAAAARAAAAAAAAAEABgABXJlYRQAACABFyAA01v5AADYGWroFT02hCgW1TucBviyR4dVCwuQRzoAR
AVTc4wAAAQEICowrFIUAMARbZAAAAAYAAABkAAAAAAAAAF4/BQA7OlqSRAAAAEQAAAAABAABAAa8X/
R5cncAAAgARQgANBKAQABABhX5CgW1TgVPTaG+LOcBwuQRzpHh1UOAEAEx3OQAAAEBCAoAMAR9jCsU
hWQAAAAFAAAAbAAAAAAAAABePwUAe6A2kwEAHABDb3VudGVycyBwcm92aWRlZCBieSBkdW1wY2FwAg
AIAF4/BQCm016RAwAIAF4/BQB4oDaTBAAIAL1BAAAAAAAABQAIABgAAAAAAAAAAAAAAGwAAAA=