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– Sales Department – For all sales inquiries or non technical questions.
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python – Generate many, many folders fast

I’ve made a program which makes the folders a-z, and in each of those makes the folders a-z, and in each of… you get it. many, many folders. its quite slow at the moment, would there be any way to optimize?

import os
from os import chdir,mkdir,rmdir
from os.path import isdir
from sys import exit

if os.name == "nt":
    os.system("color")

DIRLIMIT = 4
LOGLIMIT = 2

CHAR_GREEN = "u001b(32m"
CHAR_RESET = "u001b(0m"
CHAR_WHITE = "u001b(37m"
CHAR_CYAN = "u001b(36m"
CHAR_MAGENTA = "u001b(35;1m"
CHAR_YELLOW = "u001b(33m"

PREFIX = "dir_"
CHARS_ALPHABET = ("A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z", " ") #last character is empty whitespace

colors_dict = {
    0: CHAR_RESET,
    1: CHAR_GREEN,
    2: CHAR_YELLOW,
    3: CHAR_MAGENTA,
    4: CHAR_CYAN,
    5: CHAR_WHITE
}



def make_recursive():
    usr = int(input("Input how many directores you want:n> "))
    print(f"Making '{usr}' directories with prefix '{PREFIX}'n")
    for curGoal in range(usr):
        curGoal += 1
        try:
            mkdir(f"./{PREFIX}{curGoal}")
            chdir(f"./{PREFIX}{curGoal}")
            print(f"Made directory '{PREFIX}{curGoal}', navigated")
        except (FileNotFoundError, OSError):
            input(f"I can't go any further, MAX_PATH is still limited at 260 characters for this system. Please remove this limit, and run me again!nnPress the enter key to exit...")
            return
        except FileExistsError:
            chdir(f"./{PREFIX}{curGoal}")
            print(f"Already found directory '{PREFIX}{curGoal}', navigated")

    input("nDone!nnPress enter to exit...")
    return

def rmtree(path : str, level : int = 0):
    try:
        start = autotab(level)

        if start != None:
            print(f"{start}Working on level {level}{CHAR_RESET}tttt'{path}'")

        os.rmdir(path)  
    except OSError:
        for folder in os.listdir(path):
            try:
                rmtree(f"{path}/{folder}", level+1)
            except NotADirectoryError:
                os.remove(f"{path}/{folder}")
    if os.path.exists(path):
        rmtree(path)
    
def make_letters():
    for char in CHARS_ALPHABET:
        mkdir(f"./{char}")

def start_makealphabet():
    try:
        mkdir("./Alphabet")
        chdir("./Alphabet")
    except FileExistsError:
        input("Alphabet already exists!nnPress the enter key to delete it...")

        rmtree("./Alphabet")

        input("nAlphabet deleted!nnPress the enter key to exit...")
        return

    make_alphabet()

    input(f"nnnn{CHAR_MAGENTA}Generation done!nn{CHAR_RESET}Press the enter key to exit...")
    exit()

def autotab(level):
    if level == 0 or level > LOGLIMIT:
        return None
    try:
        returnString = colors_dict(level)
    except KeyError:
        returnString = ""
    while level != 1:
        level -= 1
        returnString += "t"
    
    return returnString

def make_alphabet(level=1, curpath=""):
    for char in CHARS_ALPHABET:
        mkdir(f"./{char}")
        start = autotab(level)
        if start != None:
            print(f"{start}Working on level {level}{char}{CHAR_RESET}")
        chdir(f"./{char}")
        if level < DIRLIMIT:
            make_alphabet(level+1, f"{curpath}{char}")
        else:
            with open(f"{curpath}{char}", "w"):
                pass
        chdir("..")

if __name__ == "__main__":
    try:
        start_makealphabet()
    except KeyboardInterrupt:
        input("Program stopped.nnPress the enter key to exit...")
        exit()

App Windows – Fast Video Cataloger v7.0.1.0 (x64) | NulledTeam UnderGround

Fast Video Cataloger v7.0.1.0 (x64)

Fast Video Cataloger v7.0.1.0 (x64) | 107 MB | Language: English

Fast Video Cataloger is a professional Windows video software for searching, browsing and organizing digital video files Search, browse, find and play all your video files fast and easy. Fast Video cataloger is the fastest local video content management system available for Windows PC. Do not take our words for it, test our video software on your own video files. You can download the fully functional program for free without providing any email address. The installation is client only and does not require any IT department support for server setups. You can be up and testing in less than 3 minutes.

With Fast Video Cataloger you will:
– Index all your videos automatically and save hours
– Always find scenes and videos you are looking for
– Jump to the right scene by video thumbnails
– Browse your archived video files visually
– Enrich your videos and scenes with metadata, images and keywords

Instantly find scenes in your videos
Fast Video Cataloger automatically create evenly spaced thumbnails for each clip to assist searching through large collections of video clips on your PC in the fastest possible way. You can have all your videos organized without effort. We support video clips on your PC, External hard drives, usb sticks, DVDs, Dropbox. You can easily search, browse and get an overview of all your videos even if the devices with the video files are disconnected because you are on the road.

Find the right scenes fast
Navigate your videos fast and smart Fast video cataloger supports several ways of finding your video or scene inside huge collections.

Play from video thumbnails
Fast video cataloger comes with an integrated video player that can start playing videos right from the time of a captured thumbnail.

Archive video files
Fast Video Cataloger keeps archived videos searchable and browsable with thumbnails and keywords while raw files are stored externally.

Flexible video Keywording
Keywording on videos and scenes will support your workflow, empower your team and make your work on videos faster.

Customize with scripting
Fast video cataloger 5.x supports integrated scripting in c#. Customize the program or use it as a base to build your own video solutions. The installer includes examples to get you started as well as extensive api documentation.

Extend with custom meta data
Add custom meta data to videos and customize the your catalogs. Companies using Fast Video Cataloger often needs to store some company specific meta data with the video. Now you can add extra fields to your catalog and store custom meta data with your video. The custom data is also available through the scripting interface.

Contact sheet images
Printable and shareable contact sheet images make up overviews of your videos for discussions, presentations and notes.

Release Notes:

Requirements: 64 bit versions of Windows 7, Windows 8, Windows 8.1, Windows 10.

Homepage:

mining pools – miniZ fast Equihash miner 144,5 150,5,3 125,4 192,7 210,9 150,5 BeamHashIII 96,5

miniZ is fast and friendly Equihash <144.5> BeamHash III <150.5.3> <125.4> <192.7> <210.9> <150.5> <96.5> Cuda miner.

  • Supports mining of all Equihash <144.5> (BTG, BTCZ, XSG, LTZ, BZE), <150.5> (GRIMM), BeamHash III, <150.5.3> (Beam), <192.7> (Cryptocurrencies ZER, SAFE, GENX, VDL, ZERC, ANON), <125.4> (ZEL), <210.9> (AION) and <96.5> (MNX).
  • miniZ is compiled for Linux and Windows.
  • Requires at least 2GB of GPUs. Ex. GTX 1050 2GB.
  • Cool console output and telemetry monitoring.
  • Supports most mining pools.
  • Development fee is set at 2%.

In version – miniZ v1.5u – we have discontinued support for Cuda 8. If you are using older versions of miniZ: for Turing architectures (16xx and RTX series) you need to use Cuda 10.0.

miniZ v1.6v

  • Added support for BeamHash III. (Hashrate below)
  • Fixed –show-mode parameter, which was displayed only in combination with other parameters.
  • Included another low memory mode for 1060 3GB on ZEL. (works with –oc2)
  • Completely redesigned –ocX mechanism.
  • Changed the core, calls to 150.5. Let us know if this improves your driver’s CPU usage.
  • Best default core for GTX1070, at default settings, for all algorithms.

When adjusting your GPU’s OC settings, be sure to check if your GPU supports oc1 / oc2. This may slightly improve your productivity.
–oc1 / oc2 may have changed for some GPUs and algorithms in the new version.

Download : PASSWORD miniZ

Equihash – BeamHash III:

  • GTX 1050 2GB ~ 3.3 Sol / s
  • GTX 1050 Ti 4GB ~ 6.6 Sol / s
  • GTX 1060 3GB ~ 8.2 Sol / s
  • GTX 1660 Ti 8GB ~ 15.7 Sol / s
  • GTX 1070 8GB ~ 17.4 Sol / s
  • GTX 1070 Ti 8GB ~ 19.6 Sol / s
  • GTX 1080 8GB ~ 19.0 Sol / s
  • GTX 1080 Ti 11GB ~ 28.3 Sol / s
  • RTX 2070 8GB ~ 23.2 Sol / s

Equihash 150,5,3 (BeamHash II):

  • GTX 1050 Ti 4GB ~ 13 – 14 Sol / s
  • GTX 1060 3GB ~ 21 – 24 Sol / s
  • GTX 1660 Ti 6GB ~ 30 – 33 Sol / s
  • GTX 1070 Ti 8GB ~ 41 – 47 Sol / s
  • GTX 1080 8GB ~ 42 – 46 Sol / s
  • GTX 1080 Ti 11GB ~ 59 – 61 Sol / s
  • RTX 2070 8GB ~ 52 – 58 Sol / s
  • RTX 2080 Ti 8GB ~ 90 – 96 Sol / s

Equihash 125.4 (ZelHash):

  • GTX 1050 Ti 4GB ~ 12 – 14 Sol / s
  • GTX 1060 3GB ~ 21 – 24 Sol / s
  • GTX 1660 Ti 6GB ~ 31 – 34 Sol / s
  • GTX 1070 Ti 8GB ~ 40 – 46 Sol / s
  • GTX 1080 8GB ~ 42 – 46 Sol / s
  • GTX 1080 Ti 11GB ~ 59 – 63 Sol / s
  • RTX 2070 8GB ~ 51 – 57 Sol / s
  • RTX 2080 Ti 8GB ~ 90 – 97 Sol / s

Equihash 210.9:

  • GTX 1050 2GB ~ 77 – 85 Sol / s
  • GTX 1050 Ti 4GB ~ 84 – 92 Sol / s
  • GTX 1060 3GB ~ 139 – 171 Sol / s
  • GTX 1660 Ti 6GB ~ 187 – 201 Sol / s
  • GTX 1070 Ti 8GB ~ 227 – 264 Sol / s
  • GTX 1080 8GB ~ 242 – 273 Sol / s
  • GTX 1080 Ti 11GB ~ 352 – 375 Sol / s
  • RTX 2070 8GB ~ 273 – 312 Sol / s
  • RTX 2080 Ti 8GB ~ 478 – 517 Sol / s

Equihash 150.5:

  • GTX 1050 Ti 4GB ~ 8 Sol / s
  • GTX 1060 3GB ~ 14 – 15 Sol / s
  • GTX 1660 Ti 6GB ~ 17 – 19 Sol / s
  • GTX 1070 Ti 8GB ~ 27 – 31 Sol / s
  • GTX 1080 8GB ~ 28 – 31 Sol / s
  • GTX 1080 Ti 11GB ~ 38 – 41 Sol / s
  • RTX 2070 8GB ~ 32 – 36 Sol / s
  • RTX 2080 Ti 11GB ~ 60 – 65 Sol / s

Equihash 144.5 (ZHash):

  • GTX 1050 2GB ~ 19 – 21 Sol / s
  • GTX 1050 Ti 4GB ~ 21 – 23 Sol / s
  • GTX 1060 3GB ~ 36 – 41 Sol / s
  • GTX 1660 Ti 6GB ~ 47 – 50 Sol / s
  • GTX 1070 Ti 8GB ~ 64 – 73 Sol / s
  • GTX 1080 8GB ~ 69 – 75 Sol / s
  • GTX 1080 Ti 11GB ~ 96 – 98 Sol / s
  • RTX 2070 8GB ~ 76 – 85 Sol / s
  • RTX 2080 Ti 11GB ~ 128 – 139 Sol / s

Equihash 192.7 (Equihash Heavy):

  • GTX 1050 Ti 4GB ~ 11 – 12 Sol / s
  • GTX 1060 3GB ~ 20 – 23 Sol / s
  • GTX 1660 Ti 6GB ~ 25 – 27 Sol / s
  • GTX 1070 Ti 8GB ~ 37 – 42 Sol / s
  • GTX 1080 8GB ~ 37 – 40 Sol / s
  • GTX 1080 Ti 11GB ~ 51 – 55 Sol / s
  • RTX 2070 8GB ~ 43 – 48 Sol / s
  • RTX 2080 Ti 11GB ~ 79 – 84 Sol / s

Equihash 96.5:

  • GTX 1050 2GB ~ 7.1 KSol / s

  • GTX 1050 Ti 4GB ~ 7.8 – 8.5 KSol / s

  • GTX 1060 3GB ~ 12.4 – 13.6 KSol / s

  • GTX 1660 Ti 6GB ~ 15.2 – 16.0 Sol / s

  • GTX 1070 Ti 8GB ~ 21.4 – 23.5 KSol / s

  • GTX 1080 8GB ~ 22.7 – 24.5 KSol / s

  • GTX 1080 Ti 11GB ~ 28.3 – 30.6 KSol / s

  • RTX 2070 8GB ~ 21.2 – 23.9 KSol / s

  • RTX 2080 Ti 11GB ~ 38.3 – 40.6 KSol / s
    Latest versions:
    miniZ v1.5u2

  • Fixed a bug where shares in some pools were not published when mining ZEL.

  • Corrected default kernels for GTX1070, at stock settings, for all algorithms.

  • 144.5 (BTG, XSG, BTCZ, BTH, BZE, …): Major improvements for various GPUs. Up to 6.5% depending on GPU.

  • 125.4 (ZEL): Minor improvements. Up to 1% depending on GPU.

  • Fixed connection delay issues.

  • Added –ocX option to automatically tune the best kernel for your GPU and OC settings, for all algorithms.

  • Added –show-mode option to show the miniZ kernel used by each GPU.

  • Reduced memory usage by 144.5 for all GPUs.

  • Reduced memory usage by 3GB GPU for 125.4, on Windows 10 (work in progress).

computational complexity – Fast division by 3 or 5

There was a question about this topic posted on StackExchange 12 years ago, see here. Basically, it says that there is nothing better than the 3000 years-old technique, and the suggestion in modern times is to “let the compiler do its job”.

Well, here is what mine is doing. Divide the following integer by 3:

222730506728397170591387079211836683557072632289734369842905278066498119541270318525897952142956554114412930297037751282

The result is this:

74243502242799056863795693070612227852360000000000000000000000000000000000000000000000000000000000000000000000000000000

Obviously it is totally wrong, despite using the BigNum library in Perl. I know you can compute the multiplication $3x$ very fast: $3x = 2x + x = (x$ << $1) + x$ using the bit shifting operator. But what about the division?

I came up with the following rudimentary algorithm, but I am wondering if there is a faster solution.

Algorithm

Let $x$ be the number to be divided by $3$. Pre-compute $3^k$ and $2cdot 3^k$ for $k=0,cdots,n$ with $n=lfloorlog_3 xrfloor$. In other words, $n$ is the largest integer such that $3^nleq x$. Very useful step, since I have a bunch of large integers (all equal to zero modulo $3$) that I need to divide by $3$ and by any power of $3$ that is also a divisor. Here I assume $x$ is the largest of the integers that I am dealing with. Then the initialization step consists of:

  • $z leftarrow x$
  • $d_{n+1} leftarrow 0$
  • $nleftarrow n+1$

The loop consists of:

  • $y=z-d_n 3^n$
  • If $2cdot 3^{n-1} < y$ then $d_{n-1}=2$ else if $3^{n-1} <
    y$
    then $d_{n-1}=1$ else $d_{n-1}=0$.
  • $z leftarrow y$
  • $nleftarrow n-1$

Repeat the loop until $n=0$.

The sequence $d_1,cdots,d_n$ is the digits of $x/3$ in base $3$. If $3$ divides $x$ then $d_0=0$. Thus
$$frac{x}{3}=sum_{k=1}^nd_{k}3^{k-1}.$$

Note that $2cdot 3^{k} = 3^{k}$ << $1$ (faster than the multiplication by $2$). In the final sum, use pre-computed values for $d_k 3^{k-1}$.

mining pools – Bminer: a fast Equihash/Ethash/Cuckaroo29m miner for AMD/NVIDIA GPUs 16.2.9

Bminer is a highly optimized cryptocurrency miner that runs on modern AMD / NVIDIA GPUs (Maxwell and Pascal, i.e. GPUs with a computing power of 5.0 or higher). Bminer is one of the fastest miners available today – we use a variety of techniques, including tiling and pipelining, to realize the full potential of the hardware.

Bminer also comes with REST APIs to simplify product deployments (like mining farms).
Bminer supports Equihash based coin mining (like Zcash) with 2% devfee.
Bminer supports Zhash / Equihash 144.5 based coin mining (e.g. BitcoinGold, BitcoinZ) with 2% from devfee.
Bminer supports Ethash based coin mining (like Ethereum) with 0.65% devfee.
Bminer also supports dual mining mode – simultaneous mining of Ethash based coins (like Ethereum) and Blake14r based coins (like Decred) / Blake2s (like Verge). Devfee for dual mining mode is 1.3%, and the second coin (e.g. Decred / Verge) is mined without devfee.
Bminer supports Tensority based coin mining (like Bytom (BTM)) with 2% devfee.
Bminer supports Grin (GRIN) mining with 1% devfee.

Download

Specifications

Fast

Grin31 mining on stock settings
2.60 G / s on RTX 2080Ti
1.65 G / s on RTX 2080
1.55 G / s on GTX 1080Ti
0.95 G / s on GTX 1070

Bminer 16.0.6 Grin29m mining on stock settings
8.32 G / s on GTX 2080Ti
5.18 G / s on GTX 2070
3.96 G / s on 2060
2.18 G / s on 1060
3.34 G / s on 1070
5.03 G / s on 1080ti
3.00 G / s on P104-4G
3.56 G / s on P104-8G
4.95 G / s on P102-10G

AE mining on stock settings:
11.8 Sol / s on GTX 2080Ti
8.90 Sol / s on GTX 2080
7.40 Sol / s on GTX 1080Ti
4.7 Sol / s on GTX 1070
3.4 Sol / s on GTX 1060 6G

Beam mining on stock settings
30 Sol / s on GTX 1080Ti
21 Sol / s on GTX 1070
12 Sol / s on GTX 1060 6G

Equihash mining on stock settings
735-745 Sol / s on GTX 1080Ti
450-460 Sol / s on GTX 1070
315-325 Sol / s on GTX 1060

Equihash 144.5 (Zhash) mining on stock settings
61 Sol / s on GTX 1080Ti
25 Sol / s on GTX 1060
Ethash mining on GTX 1080Ti stock settings (power: 250 W)

With OhGodAnETHlargementPill: 46.7 MH / s
Without OhGodAnETHlargementPill: 32.2 MH / s

Dual mining using automatic tuning (default) on GTX 1080Ti stock settings (power: 250 W)

With OhGodAnETHlargementPill:
ETH 46 MH / s and DCR 1000 MH / s
ETH 46 MH / s and XVG 1770 MH / s

Without OhGodAnETHlargementPill:
ETH 32 MH / s and DCR 2200 MH / s
ETH 32 MH / s and XVG 3750 MH / s

Bytom mining on stock settings:
4650 H / s on GTX 1080Ti
2850 H / s on GTX 1070
1800 H / s on GTX 1060 6G
Safe and reliable

SSL support
Automatic reconnection to recover from network failures.
Automatic restart when GPU freezes

Operation friendly

Comes with REST API to simplify deployment

Fast start

Depending on the coins you want to mine, find the appropriate script in the folder. For example, the corresponding script is mine_grin29.bat (on Windows) or mine_grin29.sh (on Linux) when mining Grin using the Cuckaroo29 algorithm.
Change the address and account information in the script.
Run the script and enjoy mining clear.png
Release Notes

16.2.9 (current)
Improve the performance of the Cuckaroo29z miner.

sql server – Complex rights structure for users/members and keeping it fast

We are working on a database that holds various information about 15.000 members in a complex structure. These members are managed/viewed by about 1.000 and we need a system to handled rights for these users. You are only allowed to view the members you have had connection with in the last 3 months or currently have one.

The problem we are facing is that it’s very slow to find out which members you are allowed to see, because of the various ways you can have a connection.

These members have parents(~2 per member), a location (1 or more of 500), a principal (1 or more of 100) and a hobby (1 or more of 100). All of these are separate tables.

There is a connection for these members in several tables

(fixedconnection) (~500.000 rows)
memberid, locationid, principalid, startdate, enddate, dayofweek

(fixedconnectionhobby) (~10.000.000 rows)
fixedconnectionid, hobbyid, startdate, enddate, dayofweek

(dailyconnection) (~10.000.000 rows)
memberid, locationid, principalid, hobbyid, date

(parents) (~30.000 rows)
member, parent

Then the actual users also have a rights structure to define what they can see. There are companies and for each company you can select zero, one or multiple locations, principals and or hobbies. If nothing is selected, you can see all.

Each company has departments, where you can select a subset of the chosen locations for the company. If nothing is selected, you can see what the company can see. If something is selected, you can only see those.

Each dapartment has users connected and these users login.

These users have various lists they want to see and select one item to view the details, like:

  • Show me all the dailyconnections
  • Show me all the members
  • Show me all the locations
  • Show me all the hobbies

We need a way to determine in SQL which records we are allowed to show. At the moment we use a combination of joins and union all to combine all the various options to get a list of ids for a specific type. For example all the member ids we can view. We can use this in the query to view the member list.

Obviously this will make the queries quite slow, even with proper indexing, because you are constantly juggling around milions of connections, just to show a single member.

We tried to use caching and get a single table with all the members you can see, per user, but since there are constant modifications to the members and their connections, it changes often who you can see.

My question: How would you handle a structure like this, to prevent users from seeing members they shouldnt see, and keeping it fast.