ShadowClone allows you to distribute your long running tasks dynamically across thousands of serverless functions and gives you the results within seconds where it would have taken hours to complete

Last update: Jan 6, 2023

Related tags

Overview

ShadowClone

ShadowClone allows you to distribute your long running tasks dynamically across thousands of serverless functions and gives you the results within seconds where it would have taken hours to complete.

You can make full use of the Free Tiers provided by cloud providers and supercharge your mundane cli tools with shadow clone jutsu (Naruto style)!

Installation

Please visit the wiki for installation and intial configuration instructions

Usage

⚡ python shadowclone.py -h
usage: shadowclone.py [-h] -i INPUT [-s SPLITNUM] [-o OUTPUT] -c COMMAND

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
  -s SPLITNUM, --split SPLITNUM
                        Number of lines per chunk of file
  -o OUTPUT, --output OUTPUT
  -c COMMAND, --command COMMAND
                        command to execute

How it works

We create a container image during the initial setup and register it as a runtime for our function in AWS/GCP/Azure whatever. When you execute ShadowClone on your computer, instances of that container are activated automatically and are only active for the duration of its execution. How many instances to activate is dynamically decided at runtime depending on the size of the input file provided and the split factor. The input is then split into chunks and equally distributed between all the instances to execute in parallel. For example, if your input file has 10,000 lines and you set the split factor to 100 lines, then it will be split into 100 chunks of 100 lines each and 100 instances will be run in parallel!

Features

Extremely fast
No need to maintain a VPS (or a fleet of it :))
Costs almost nothing per month
- Compatible with free tiers of most cloud services
Cloud agnostic
- Same script works with AWS, GCP, Azure etc.
Supports upto 1000 parallel invocations
Dynamically decide the number of invocations
Run any tool in parallel on the cloud
Pipe output to other tools

Comparison

This tool was inspired by the awesome Axiom and Fleex projects and goes beyond the concept of VPS for running the tools by using serverless functions and containers.

Features	Axiom/Fleex	ShadowClone
Instances	10-100s*	1000s
Cost	Per instance/per minute	Mostly Free**
Startup Time	4-5 minutes	2-3 seconds
Idle Cost	$++	Free
On Demand Scalability	No	∞

*Most cloud providers do not allow spinning up too many instances by default, so you are limited to around 10-15 instances at max. You have to make a request to the support to increase this number.

** AWS & Azure allow 1 million invocations per month for free. Google allows 2 million invocations per month for free. You will be charged only if you go above these limits

Demo

DNS Bruteforcing using a 43mb file - 34 seconds

Running httpx on 94K subdomains in 1 min

References

Lithops documentation

Free Tiers

Cloud Provider	Free Allowance	Link
Google Functions	2 Million invocations, 400,000 GB-seconds per month	Google Cloud Free Program
AWS Lambda	1 Million invocations, Up to 3.2 million seconds of compute time per month	Free Cloud Computing Services - AWS Free Tier
Azure Functions	1 Million invocations	Microsoft Azure Free Services

Obviously, you can make any number of function invocations per month. The table above only shows how many invocations are free.

Similar Tools

Disclaimer

This tool is designed as a proof-of-concept implementation and it's usage is intended for educational purpose only. Usage for attacking targets without prior mutual consent is illegal. It's the end user's responsibility to obey all applicable local, state and federal laws. Developers assume no liability and are not responsible for any misuse or damage caused by this program.

Comments

ARM64

Any where to specify ARM64 in AWS Lambda via Lithops?

Aside from that, modifying the Dockerfile to --plathform=linux/amd64 doesn't seem to make it work on a M1 MacBook.

opened by vysecurity 3

Function stuck in pending state

It worked at the first go.

Then I've added some other tooling to the Dockerfile and used this command to rebuild the Docker:

lithops runtime build sc-runtime -f Dockerfile

Since then, I'm not able anymore to run the program. Even Lithops test fails me:

lithops test
2022-01-24 10:46:09,925 [INFO] lithops.config -- Lithops v2.5.8
2022-01-24 10:46:10,081 [INFO] lithops.storage.backends.aws_s3.aws_s3 -- S3 client created - Region: eu-west-3
2022-01-24 10:46:10,124 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- AWS Lambda client created - Region: eu-west-3
2022-01-24 10:46:10,125 [INFO] lithops.invokers -- ExecutorID d5971d-0 | JobID A000 - Selected Runtime: python38 - 512MB
2022-01-24 10:46:10,218 [INFO] lithops.invokers -- Runtime python38 with 512MB is not yet installed
2022-01-24 10:46:10,311 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating default lambda layer for runtime python38
Traceback (most recent call last):
  File "/root/tools/ShadowClone/test/bin/lithops", line 8, in <module>
    sys.exit(lithops_cli())
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/click/core.py", line 1128, in __call__
    return self.main(*args, **kwargs)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/click/core.py", line 1053, in main
    rv = self.invoke(ctx)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/click/core.py", line 1659, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/click/core.py", line 1395, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/scripts/cli.py", line 168, in test_function
    fexec.call_async(hello, username)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/executors.py", line 205, in call_async
    runtime_meta = self.invoker.select_runtime(job_id, runtime_memory)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/invokers.py", line 121, in select_runtime
    runtime_meta = self.compute_handler.create_runtime(self.runtime_name, runtime_memory, runtime_timeout)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/serverless/serverless.py", line 73, in create_runtime
    return self.backend.create_runtime(runtime_name, memory, timeout=timeout)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 413, in create_runtime
    layer_arn = self._create_layer(runtime_name)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 200, in _create_layer
    response = self.lambda_client.invoke(
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/botocore/client.py", line 391, in _api_call
    return self._make_api_call(operation_name, kwargs)
  File "/root/tools/ShadowClone/test/lib/python3.8/site-packages/botocore/client.py", line 719, in _make_api_call
    raise error_class(parsed_response, operation_name)
botocore.errorfactory.ResourceConflictException: An error occurred (ResourceConflictException) when calling the Invoke operation: The operation cannot be performed at this time. The function is currently in the following state: Pending

Already tried:

Remove runtime reference in config.py
Remove lambda function manually in console
Remove S3 bucket and create a new one and add new one in config
Changing AWS region

Would really appreciate some guidance in how to proceed when editing the Dockerfile

opened by ghost 2

deploy error

(env) root@zyz:~/ShadowClone# lithops runtime create recon --memory 512 --timeout 800
2022-12-06 00:33:19,115 [INFO] lithops.config -- Lithops v2.5.8
2022-12-06 00:33:19,115 [DEBUG] lithops.config -- Loading configuration from /root/.lithops/config
2022-12-06 00:33:19,133 [DEBUG] lithops.config -- Loading Serverless backend module: aws_lambda
2022-12-06 00:33:19,192 [DEBUG] lithops.config -- Loading Storage backend module: aws_s3
2022-12-06 00:33:19,193 [INFO] lithops.scripts.cli -- Creating new lithops runtime: recon
2022-12-06 00:33:19,193 [DEBUG] lithops.storage.backends.aws_s3.aws_s3 -- Creating S3 client
2022-12-06 00:33:19,290 [INFO] lithops.storage.backends.aws_s3.aws_s3 -- S3 client created - Region: ap-southeast-1
2022-12-06 00:33:19,290 [DEBUG] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating AWS Lambda client
2022-12-06 00:33:19,290 [DEBUG] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating Boto3 AWS Session and Lambda Client
2022-12-06 00:33:20,206 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- AWS Lambda client created - Region: ap-southeast-1
2022-12-06 00:33:20,207 [DEBUG] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating new Lithops lambda function: lithops_v2-5-8_gzmx_recon_512MB
Traceback (most recent call last):
  File "/root/ShadowClone/env/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 371, in create_runtime
    response = self.ecr_client.describe_images(repositoryName=repo_name)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/botocore/client.py", line 530, in _api_call
    return self._make_api_call(operation_name, kwargs)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/botocore/client.py", line 960, in _make_api_call
    raise error_class(parsed_response, operation_name)
botocore.errorfactory.RepositoryNotFoundException: An error occurred (RepositoryNotFoundException) when calling the DescribeImages operation: The repository with name 'lithops_v2-5-8_gzmx/recon' does not exist in the registry with id '866113468777'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/root/ShadowClone/env/bin/lithops", line 8, in <module>
    sys.exit(lithops_cli())
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 760, in invoke
    return __callback(*args, **kwargs)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/lithops/scripts/cli.py", line 434, in create
    runtime_meta = compute_handler.create_runtime(name, mem, timeout=to)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/lithops/serverless/serverless.py", line 73, in create_runtime
    return self.backend.create_runtime(runtime_name, memory, timeout=timeout)
  File "/root/ShadowClone/env/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 376, in create_runtime
    raise Exception('Runtime {} is not deployed to ECR'.format(runtime_name))
Exception: Runtime recon is not deployed to ECR

I thought the problem was with the "role" but I have adjusted what you gave on the wiki and it still has an error

opened by kepangada 1

pickle_db

Hi, what can I put for Pickle_db or where can I find the bucket-hash.db?

python shadowclone.py -i /home/kali/range.txt --split 100 -o test.txt -c "/go/bin/httpx -l {INPUT}" 2022-10-11 23:07:27,214 [INFO] Splitting input file into chunks of 100 lines 2022-10-11 23:07:27,219 [INFO] Uploading chunks to storage Traceback (most recent call last): File "/home/kali/Tools/ShadowClone/shadowclone.py", line 128, in db.dump() # save the db to file File "/usr/local/lib/python3.10/dist-packages/pickledb.py", line 92, in dump json.dump(self.db, open(self.loco, 'wt')) FileNotFoundError: [Errno 2] No such file or directory: ''

in config.py I have the following line:

PICKLE_DB=""

FYI, it has same errors on running the RUN go install -... /nuclei@latest but I skipped nuclei installation. Thank you!

opened by georgebecerescu 1
Error when running build command

Hi!

I've been trying to setup the tool on my Debian 10 box and getting the error when running the command:

lithops runtime build sc-runtime -f ~/tools/ShadowClone/Dockerfile

Error snapshot:

Python version : Python 3.10.6

opened by sumgr0 1
error output when running

Hello @fyoorer @vysecurity

I managed to configure this tool with the steps mentioned, but when running the output only shows $HOME is not defined. What really happened?

opened by marz-hunter 1

Rate limit error while running command

Any solution for this ?

(env) kkkk:ShadowClone:% python shadowclone.py -i subdomains.txt --split 300 -o httpxresults.txt -c "/go/bin/httpx -l {INPUT} -t 100"                                                                   <main ✗>
2022-10-20 04:52:29,805 [INFO] Splitting input file into chunks of 300 lines
2022-10-20 04:52:29,869 [INFO] Uploading chunks to storage
2022-10-20 04:52:29,886 [INFO] lithops.config -- Lithops v2.5.8
2022-10-20 04:52:29,928 [INFO] lithops.storage.backends.aws_s3.aws_s3 -- S3 client created - Region: us-east-1
2022-10-20 04:52:30,062 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- AWS Lambda client created - Region: us-east-1
2022-10-20 04:52:30,064 [INFO] lithops.invokers -- ExecutorID 85b642-0 | JobID M000 - Selected Runtime: lithops_v2-5-8_7vdl/sc-runtime1 - 512MB
2022-10-20 04:52:37,246 [INFO] lithops.invokers -- ExecutorID 85b642-0 | JobID M000 - Starting function invocation: execute_command() - Total: 167 activations
exception calling callback for <Future at 0x7fedac13f9d0 state=finished raised Exception>
Traceback (most recent call last):
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 328, in _invoke_callbacks
    callback(self)
  File "/home/op/env/lib/python3.8/site-packages/lithops/invokers.py", line 439, in _callback
    future.result()
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 437, in result
    return self.__get_result()
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 389, in __get_result
    raise self._exception
  File "/usr/lib/python3.8/concurrent/futures/thread.py", line 57, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/op/env/lib/python3.8/site-packages/lithops/invokers.py", line 370, in _invoke_task
    activation_id = self.compute_handler.invoke(payload)
  File "/home/op/env/lib/python3.8/site-packages/lithops/serverless/serverless.py", line 59, in invoke
    return self.backend.invoke(runtime_name, runtime_memory, job_payload)
  File "/home/op/env/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 577, in invoke
    raise Exception('Error {}: {}'.format(r.status_code, r.text))
Exception: Error 429: {"Reason":"CallerRateLimitExceeded","Type":"User","message":"Rate exceeded"}
exception calling callback for <Future at 0x7fed5f95ceb0 state=finished raised Exception>
Traceback (most recent call last):
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 328, in _invoke_callbacks
    callback(self)
  File "/home/op/env/lib/python3.8/site-packages/lithops/invokers.py", line 439, in _callback
    future.result()
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 437, in result
    return self.__get_result()
  File "/usr/lib/python3.8/concurrent/futures/_base.py", line 389, in __get_result
    raise self._exception
  File "/usr/lib/python3.8/concurrent/futures/thread.py", line 57, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/op/env/lib/python3.8/site-packages/lithops/invokers.py", line 370, in _invoke_task
    activation_id = self.compute_handler.invoke(payload)
  File "/home/op/env/lib/python3.8/site-packages/lithops/serverless/serverless.py", line 59, in invoke
    return self.backend.invoke(runtime_name, runtime_memory, job_payload)
  File "/home/op/env/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 577, in invoke
    raise Exception('Error {}: {}'.format(r.status_code, r.text))
Exception: Error 429: {"Reason":"CallerRateLimitExceeded","Type":"User","message":"Rate exceeded"}
exception calling callback for <Future at 0x7fedac1ae2b0 state=finished raised Exception>

opened by b1bek 1

FFUF Example Usage?

Hi there,

Do you have an FFUF example usage? I kept getting errors parsing params for example:

python3 shadowclone.py -i input.txt -o output.txt -s 1 -c "cat {INPUT} | xargs -I @ -c '/go/bin/ffuf -u @ -w wordlist.txt -mc 200'"

opened by vysecurity 3

Could not execute the runtime

Using AWS Runtime.

python3 shadowbrute.py -d REDACTED -w subdomain_wordlist.txt
2022-01-24 16:47:39,414 [INFO] File with same name already exists in the bucket, skipping upload
2022-01-24 16:47:39,414 [ERROR] Could not execute the runtime.

Could not execute the runtime. How can I debug?

opened by vysecurity 10

getting error while running this command lithops runtime build sc-runtime -f Dockerfile

2022-01-24 14:04:46,069 [INFO] lithops.config -- Lithops v2.5.8 2022-01-24 14:04:46,069 [DEBUG] lithops.config -- Loading configuration from /root/.lithops/config 2022-01-24 14:04:46,139 [DEBUG] lithops.config -- Loading Serverless backend module: aws_lambda 2022-01-24 14:04:46,240 [DEBUG] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating AWS Lambda client 2022-01-24 14:04:46,240 [DEBUG] lithops.serverless.backends.aws_lambda.aws_lambda -- Creating Boto3 AWS Session and Lambda Client 2022-01-24 14:04:47,588 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- AWS Lambda client created - Region: us-east-1 2022-01-24 14:04:47,589 [INFO] lithops.serverless.backends.aws_lambda.aws_lambda -- Going to create runtime -d for AWS Lambda 2022-01-24 14:04:47,590 [DEBUG] lithops.utils -- Creating function handler zip in lithops_lambda.zip Traceback (most recent call last): File "/home/cherry/Desktop/ShadowClone/env/bin/lithops", line 8, in sys.exit(lithops_cli()) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1128, in call return self.main(*args, **kwargs) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1053, in main rv = self.invoke(ctx) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1659, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1659, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 1395, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/core.py", line 754, in invoke return __callback(*args, **kwargs) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/click/decorators.py", line 26, in new_func return f(get_current_context(), *args, **kwargs) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/lithops/scripts/cli.py", line 465, in build compute_handler.build_runtime(name, file, ctx.args) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/lithops/serverless/serverless.py", line 66, in build_runtime self.backend.build_runtime(runtime_name, file, extra_args) File "/home/cherry/Desktop/ShadowClone/env/lib/python3.8/site-packages/lithops/serverless/backends/aws_lambda/aws_lambda.py", line 319, in build_runtime subprocess.check_call(cmd.split()) File "/usr/lib/python3.8/subprocess.py", line 359, in check_call retcode = call(*popenargs, **kwargs) File "/usr/lib/python3.8/subprocess.py", line 340, in call with Popen(*popenargs, **kwargs) as p: File "/usr/lib/python3.8/subprocess.py", line 858, in init self._execute_child(args, executable, preexec_fn, close_fds, File "/usr/lib/python3.8/subprocess.py", line 1704, in _execute_child raise child_exception_type(errno_num, err_msg, err_filename) FileNotFoundError: [Errno 2] No such file or directory: 'None'

opened by falcon319 8

Owner

GitHub

Instagram Story View Bot Unencrypted Story Views is a helpful tool that allows thousands of people to watch your posts. It is completely free, source is visible for anyone to modify Type your username, wait for the bot to Automate the Task.

Ιnstagram Story Viewer Bot Usage I made this script under 10 minutes, the idea is to get Unlimited Story Views by Looping the "Submit Button" Update x

4 Oct 28, 2021

Unencrypted Story View Botter is a helpful tool that allows thousands of people to watch your posts.

8 Aug 5, 2022

An alternative to OpenFaaS nats-queue-worker for long-running functions

OpenFaas Job Worker OpenFaas Job Worker is a fork of project : OSCAR Worker - https://github.com/grycap/oscar-worker Thanks to Sebástian Risco @srisco

1 Jan 7, 2022

This project checks the weather in the next 12 hours and sends an SMS to your phone number if it's going to rain to remind you to take your umbrella.

RainAlert-Request-Twilio This project checks the weather in the next 12 hours and sends an SMS to your phone number if it's going to rain to remind yo

9 Apr 15, 2022

If you are in allot of groups or channel and you would like to leave them at once use this

Telegram-auto-leave-groups If you are in allot of groups or channel and you would like to leave them at once use this USER GUIDE ?? Insert your telegr

4 Jan 3, 2023

GitHub action to deploy serverless functions to YandexCloud

YandexCloud serverless function deploy action Deploy new serverless function version (including function creation if it does not exist). Inputs yc_acc

4 Apr 10, 2022

A smart tool to backup members 📈 So you even after a raid/ ban you can easily restore them in seconds 🎲

?? Discord-backer ?? A open-source Discord member backup and restore tool for your server. This can help you get all your members in 5 Seconds back af

29 Dec 21, 2022

Want to play What Would Rather on your Server? Invite the bot now!😏

What is this Bot? ?? What You Would Rather? is a Guessing game where you guess one thing. Long Description short Take this example: You typed r!rather

2 Nov 17, 2021

Easy & powerful bot to check if your all Telegram bots are working or not. This bot status bot updates every 45 minutes & runs for 24x7 hours.

PowerfulBotStatus-IDN-C-X Easy & powerful bot to check if your all Telegram bots are working or not. This bot status bot updates every 45 minutes & ru

5 Oct 6, 2022

Checks if Minecraft accounts are available, or taken.

MCNameChecker Checks validity of Minecraft IGN's. Using async to make it even faster. Has rate-limit detections and Proxy support Usage Q. How do I us

5 Apr 22, 2022

Prime Mega is a modular bot running on python3 with autobots theme and have a lot features.

PRIME MEGA Prime Mega is a modular bot running on python3 with autobots theme and have a lot features. Easiest Way To Deploy On Heroku This Bot is Cre

45 Dec 15, 2022

A modular bot running on python3 with anime theme and have a lot features

STINKY ROBOT Emiko Robot is a modular bot running on python3 with anime theme and have a lot features. Easiest Way To Deploy On Heroku This Bot is Cre

3 Jan 21, 2022

Okaeri Robot: a modular bot running on python3 with anime theme and have a lot features

OKAERI ROBOT Okaeri Robot is a modular bot running on python3 with anime theme a

2 Jan 19, 2022

Kanata Bot - a modular bot running on python3 with anime theme and have a lot features

Kanata Bot Kanata Bot is a modular bot running on python3 with anime theme and have a lot features. Easiest Way To Deploy On Heroku This Bot is Create

2 Jan 16, 2022

Automatically render tens of thousands of unique NFT images individually as png's.

Blend_My_NFTs Description This project is a work in progress (as of Oct 24th, 2021) and will eventually be an add on to Blender. Blend_My_NFTs is bing

894 Dec 29, 2022

To dynamically change the split direction in I3/Sway so as to split new windows automatically based on the width and height of the focused window

To dynamically change the split direction in I3/Sway so as to split new windows automatically based on the width and height of the focused window Insp

6 Mar 11, 2022