algo | Implementation of common algorithms | Learning library
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kandi X-RAY | algo Summary
Implementation of common algorithms in different programming languages.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of algo
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algo Examples and Code Snippets
Lines of Code : 62License : Permissive (MIT License)
Copydef tarjan(g):
"""
Tarjan's algo for finding strongly connected components in a directed graph
Uses two main attributes of each node to track reachability, the index of that node
within a component(index), and the lowest index reacha Community Discussions
Trending Discussions on algo
QUESTION
I'm attempting to write a function that given a list will update the 0 values to contain the nearest non zero value. If zeros are at beginning of list then the closest non zero value should be used to replace the zero value.
In other words the following list :
[0 , 0 , 10 , 25 , 30 , 0 , 0 , 0, 55 , 55 , 55 , 55 , 60 , 60 , 60 , 60]
should be updated to :
[10 , 10 , 10 , 25 , 30 , 30 , 30, 30, 55 , 55 , 55 , 55 , 60 , 60 , 60 , 60]
Here is the code I've written so far :
...ANSWER
Answered 2022-Apr-09 at 10:51You can add a simple while loop so that the code will continue until there are no 0's in the list anymore. Something like this:
QUESTION
we are currently working with a cloud product that uses JSCH internally to connect to external sftp sources. Im investigating an connection reset exception that we are getting when trying to connect to azure sftp.
Using wireshark i determined that the problem occurs after we send the Client: Key Exchange Init. Establishing the same connection with filezilla we dont have this issue.
comparing the packages from jsch and filezilla i didn't see an obivious issue, but im not an expert on the ssh protocol. im gonna post both requests below if somebody could give me any pointers it would be greatly appreciated.
Request with JSCH (not working)
Request with Filezilla (working)
Response with Filezilla (working)
See below for the log output:
...ANSWER
Answered 2022-Feb-03 at 08:09i wanted to post a quick update for anybody that is having the same issue, i opened a similiar question on the microsoft q&a site and looks like it's an issue on the azure side that they are working on fixing for GA Microsoft Q&A
QUESTION
I am experiencing a persistent error while trying to use H2O's h2o.automl function. I am trying to repeatedly run this model. It seems to completely fail after 5 or 10 runs.
ANSWER
Answered 2022-Jan-27 at 19:14I think I also experienced this issue, although on macOS 12.1. I tried to debug it and found out that sometimes I also get another error:
QUESTION
I have a Python 3 application running on CentOS Linux 7.7 executing SSH commands against remote hosts. It works properly but today I encountered an odd error executing a command against a "new" remote server (server based on RHEL 6.10):
encountered RSA key, expected OPENSSH key
Executing the same command from the system shell (using the same private key of course) works perfectly fine.
On the remote server I discovered in /var/log/secure that when SSH connection and commands are issued from the source server with Python (using Paramiko) sshd complains about unsupported public key algorithm:
userauth_pubkey: unsupported public key algorithm: rsa-sha2-512
Note that target servers with higher RHEL/CentOS like 7.x don't encounter the issue.
It seems like Paramiko picks/offers the wrong algorithm when negotiating with the remote server when on the contrary SSH shell performs the negotiation properly in the context of this "old" target server. How to get the Python program to work as expected?
Python code
...ANSWER
Answered 2022-Jan-13 at 14:49Imo, it's a bug in Paramiko. It does not handle correctly absence of server-sig-algs extension on the server side.
Try disabling rsa-sha2-* on Paramiko side altogether:
QUESTION
I have following code in node.js using crypto-js to encrypt password using AES with Secret Key and IV.
...ANSWER
Answered 2022-Jan-07 at 19:19In the CryptoJS code, the second parameter in crypto.AES.encrypt() is passed as a string, so it is interpreted as passphrase.
Therefore, during encryption, an eight bytes salt is first created and from this, along with the passphrase, key and IV are derived using the KDF EVP_BytesToKey().
The IV derived with createRandomIv() and explicitly passed in crypto.AES.encrypt() is ignored!
hash.ToString() returns the result in OpenSSL format consisting of the prefix Salted__ followed by the salt and by the actual ciphertext, all Base64 encoded. eHex contains the same data, but hex instead of Base64 encoded.
CryptoJS does not automatically disable padding for stream cipher modes like CTR, so the data is padded with PKCS#7, although this would not be necessary for CTR.
In the Go code, the IV that is not required must first be removed. From the remaining data, salt and ciphertext are determined.
From salt and passphrase, key and IV can be retrieved with evp.BytesToKeyAES256CBCMD5().
With key and IV the decryption with AES-CTR can be performed.
Finally, the PKCS#7 padding must be removed.
The following Go code implements these steps. The input data was generated with the NodeJS code:
QUESTION
Based on the answer by Will Ness, I've been using a JavaScript adaptation for the postponed sieve algorithm:
...ANSWER
Answered 2021-Sep-29 at 06:18To allow any start value for printing. As explained below, I think there is no way to avoid it having to compute all the earlier primes, if you want an infinite sequence of higher primes.
Adjusted variable names to assist understanding the algorithm.
Changed what is stored in the map from 2 times a prime factor, to just the prime factor, to make it easier for readers to follow the algorithm.
Moved one part of the code into a subfunction, again for ease of reader understanding.
Changed the control flow of the 3-way choice in the middle of the algorithm, and added comments, that simplify understanding. It is probably very slightly slower, because it no longer tests the commonest-true condition first, but it is easier for readers.
QUESTION
def merge(arr,l,m,h):
lis = []
l1 = arr[l:m]
l2 = arr[m+1:h]
while((len(l1) and len(l2)) is not 0):
if l1[0]<=l2[0]:
x = l1.pop(0)
else:
x = l2.pop(0)
lis.append(x)
return lis
def merge_sort(arr,l,h): generating them
if lANSWER
Answered 2022-Jan-04 at 13:28Several issues:
As you consider
Wrong Righthto be the last index of the sublist, then realise that when slicing a list, the second index is the one following the intended range. So change this:l1 = arr[l:m]l1 = arr[l:m+1]l2 = arr[m+1:h]l2 = arr[m+1:h+1]As
mergereturns the result for a sub list, you should not assign it toarr.arris supposed to be the total list, so you should only replace a part of it:
QUESTION
What is the time complexity of this particular implementation of Dijkstra's algorithm?
I know several answers to this question say O(E log V) when you use a min heap, and so does this article and this article. However, the article here says O(V+ElogE) and it has similar (but not exactly the same) logic as the code below.
Different implementations of the algorithm can change the time complexity. I'm trying to analyze the complexity of the implementation below, but the optimizations like checking visitedSet and ignoring repeated vertices in minHeap is making me doubt myself.
Here is the pseudo code:
...ANSWER
Answered 2021-Dec-22 at 00:38Despite the test, this implementation of Dijkstra may put Ω(E) items in the priority queue. This will cost Ω(E log E) with every comparison-based priority queue.
Why not E log V? Well, assuming a connected, simple, nontrivial graph, we have Θ(E log V) = Θ(E log E) since log (V−1) ≤ log E < log V² = 2 log V.
The O(E + V log V)-time implementations of Dijkstra's algorithm depend on a(n amortized) constant-time DecreaseKey operation, avoiding multiple entries for an individual vertex. The implementation in this question will likely be faster in practice on sparse graphs, however.
QUESTION
I have the following df:
...ANSWER
Answered 2021-Dec-15 at 18:52I believe this works:
QUESTION
I have a directed graph (DAG) representing a river network. On some of the rivers (edges) there are flow gauging stations. I would like to rank these stations according to their hierarchy from the most upstream river segments. The most upstream stations will have a class 1. Stations with only 1 station rank upstream will have a class 2, stations with 2 station ranks upstream will have a class 3, and so on. Is there an algorithm in igraph to do that? I searched in the doc for terms like "rank", "hierarchy", "order" but didn't find anything resembling to what I would like to perform.
I also used "distances" from the most downstream edge (the outlet of the river network) for the classification but it does not account for the relations among the stations (edges with very different distances can have the same rank depending on the river network configuration)...
Any suggestion on a graph algorithm to do that?
Here is an illustration of the classification:
Here is the data I use for testing (NOT related to the picture):
...ANSWER
Answered 2021-Dec-07 at 22:28You can try the code below
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