le-dawg

  #Count occurences of string in dataframe
  #Check how many rows in DataFrame contain certain substring s in column col
  print(len(df[df['col'].str.contains("s")].index.values[:]))
  
  #Index of columns in dataframe containing string
  #Get indices of rows that contain substring s in column col
  print(df[df['col'].str.contains("s")].index.values[:])

le-dawg

    # Rapidly initalize 2D list
    2dlist = [[0] * 3 for i in xrange(3)]
    print(2dlist)
    # [[0, 0, 0], [0, 0, 0], [0, 0, 0]]

le-dawg

//This snippet is a very short jQuery function that is executed when the javascript is exectued on load.

// Troubleshooting:
// You might want to add a specific class to the accordion element itself and then append that to the first div: ('div#accordionID > ...

jQuery(function(){
   jQuery('div > div.x-accordion-heading > a.x-accordion-toggle').click();
});

le-dawg

grep -rlI git: . --exclude-dir={.git,.circleci,.gitattributes,.gitignore,.editorconfig} | xargs sed -i 's/git:/https:/g'

le-dawg

2018-11-30 05:31:50.350 [info] <0.13017.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 0"
2018-11-30 05:31:50.350 [info] <0.13018.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 1"
2018-11-30 05:31:50.351 [info] <0.13019.0>@aec_pow_cuckoo:generate_int_:214 Executing cmd: "./cuda29 -h 70684B536E66476C35763739436C67506E536E30517A4572694679354553722B367445573178497555796B3D71443150754864755743593D  -d 2"
2018-11-30 05:31:51.392 [debug] <0.13017.0>@aec_pow_cuckoo:parse_generation_result:479 GeForce GTX 1070 with 8118MB @ 256 bits x 4004MHz
2018-11-30 05:31:51.392 [debug] <0.13017.0>@aec_pow_cuckoo:parse_generation_result:479 Looking for 42-cycle on cuckoo30("phKSnfGl5v79ClgPnSn0QzEriFy5ESr+6tEW1xIuUyk=qD1PuHduWCY=",0) with 50% edges, 64*64 buckets, 17

le-dawg

Keybase proof

I hereby claim:

• I am le-dawg on github.
• I am truedawg (https://keybase.io/truedawg) on keybase.
• I have a public key ASCRWLIs65PdPP1f0Skwx0FVzT_-sPXO_srKeI-zndncjAo

To claim this, I am signing this object:

le-dawg

# fix for mpl bug that cuts off/clips/clipping top/bottom of seaborn viz
b, t = plt.ylim() # discover the values for bottom and top
b += 0.5 # Add 0.5 to the bottom
t -= 0.5 # Subtract 0.5 from the top
plt.ylim(b, t) # update the ylim(bottom, top) values
plt.show() # ta-da!

# https://github.com/mwaskom/seaborn/issues/1773

le-dawg

le-dawg

So you want to mine in AWS without getting caught

tl;dr: AWS mining is against TOC so even if you have credits you will be invoiced and your credits burned. Watch out. These methods only help mitigate or lower the risk of discovery. Share responsibly.

Problem

AWS is firewalled af on top of the policy mentioned in tl;dr. A good way is to use a mining proxy with TLS. Even better would be a point-to-point VPN. Using VPN directly is also a good solution - but services that let you configure that you only want one certain port to run via VPN and not the SSH connection that is your lifeline are costly. This document sketches a few solutions, provides some links, and documents one particular approach. And remember, methods of detection will soon encompass deep learning: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9178288

le-dawg

conda create -n NAME python=3.7.5 
conda activate NAME
conda install -c conda-forge pandas logging networkx matplotlib cadcad scipy numpy seaborn