pcfg_cracker | Probabilistic Context Free Grammar password guess | Generator Utils library

 by   lakiw Python Version: 4.0-rc3 License: No License

kandi X-RAY | pcfg_cracker Summary

kandi X-RAY | pcfg_cracker Summary

pcfg_cracker is a Python library typically used in Generator, Generator Utils applications. pcfg_cracker has no vulnerabilities, it has build file available and it has low support. However pcfg_cracker has 1 bugs. You can download it from GitHub.

PCFG = Probabilistic Context Free Grammar. PCFG = Pretty Cool Fuzzy Guesser. In short: A collection of tools to perform research into how humans generate passwords. These can be used to crack password hashes, but also create synthetic passwords (honeywords), or help develop better password strength algorithms.
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            kandi-support Support

              pcfg_cracker has a low active ecosystem.
              It has 247 star(s) with 52 fork(s). There are 17 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 5 open issues and 18 have been closed. On average issues are closed in 181 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of pcfg_cracker is 4.0-rc3

            kandi-Quality Quality

              pcfg_cracker has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 122 code smells.

            kandi-Security Security

              pcfg_cracker has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              pcfg_cracker code analysis shows 0 unresolved vulnerabilities.
              There are 24 security hotspots that need review.

            kandi-License License

              pcfg_cracker does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              pcfg_cracker releases are available to install and integrate.
              Build file is available. You can build the component from source.
              Installation instructions are available. Examples and code snippets are not available.
              pcfg_cracker saves you 1771 person hours of effort in developing the same functionality from scratch.
              It has 3918 lines of code, 240 functions and 61 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pcfg_cracker and discovered the below as its top functions. This is intended to give you an instant insight into pcfg_cracker implemented functionality, and help decide if they suit your requirements.
            • Run the Trainer
            • Count the number of letters in the input string
            • Return the alphabet of the alphabet
            • Apply smoothing
            • Write data to the writer
            • Start the session
            • Return the guesses for the given pt
            • Saves the current configuration file
            • Recursive function to find the guesses for the current transition
            • Create a list of rule folders
            • Generate l33t tree
            • Simple monte carlo wrapper
            • Runs v41
            • Saves the data to a file
            • Create a save config parser
            • Detect l33t
            • Run l33t test
            • Creates a multi - word multiword detector
            • Parse command line arguments
            • Detect file encoding
            • Gets the next guess from the parse tree
            • Write data to file
            • Load the grammar
            • Load a configuration file
            • Create a PRINCE wordlist
            • Handle keypress events
            • Load the grammar rules
            Get all kandi verified functions for this library.

            pcfg_cracker Key Features

            No Key Features are available at this moment for pcfg_cracker.

            pcfg_cracker Examples and Code Snippets

            No Code Snippets are available at this moment for pcfg_cracker.

            Community Discussions

            QUESTION

            How can I make an object with an interface like a random number generator, but that actually generates a specified sequence?
            Asked 2022-Mar-31 at 13:47

            I'd like to construct an object that works like a random number generator, but generates numbers in a specified sequence.

            ...

            ANSWER

            Answered 2022-Mar-29 at 00:47

            You can call next() with a generator or iterator as an argument to withdraw exactly one element from it. Saving the generator to a variable beforehand allows you to do this multiple times.

            Source https://stackoverflow.com/questions/71655179

            QUESTION

            Translating async generator into sync one
            Asked 2022-Mar-23 at 02:39

            Imagine we have an original API that returns a generator (it really is a mechanisms that brings pages/chunks of results from a server while the providing a simple generator to the user, and lets him iterate over these results one by one. For simplicity:

            ...

            ANSWER

            Answered 2022-Mar-23 at 02:39

            For the reason that asyncio is contagious, it's hard to write elegant code to integrate asyncio code into the old codes. For the scenario above, the flowing code is a little better, but I don't think it's elegant enough.

            Source https://stackoverflow.com/questions/71580727

            QUESTION

            Return generator instead of list from df.to_dict()
            Asked 2022-Feb-25 at 22:32

            I am working on a large Pandas DataFrame which needs to be converted into dictionaries before being processed by another API.

            The required dictionaries can be generated by calling the .to_dict(orient='records') method. As stated in the docs, the returned value depends on the orient option:

            Returns: dict, list or collections.abc.Mapping

            Return a collections.abc.Mapping object representing the DataFrame. The resulting transformation depends on the orient parameter.

            For my case, passing orient='records', a list of dictionaries is returned. When dealing with lists, the complete memory required to store the list items, is reserved/allocated. As my dataframe can get rather large, this might lead to memory issues especially as the code might be executed on lower spec target systems.

            I could certainly circumvent this issue by processing the dataframe chunk-wise and generate the list of dictionaries for each chunk which is then passed to the API. Furthermore, calling iter(df.to_dict(orient='records')) would return the desired generator, but would not reduce the required memory footprint as the list is created intermediately.

            Is there a way to directly return a generator expression from df.to_dict(orient='records') instead of a list in order to reduce the memory footprint?

            ...

            ANSWER

            Answered 2022-Feb-25 at 22:32

            There is not a way to get a generator directly from to_dict(orient='records'). However, it is possible to modify the to_dict source code to be a generator instead of returning a list comprehension:

            Source https://stackoverflow.com/questions/71272151

            QUESTION

            python call generator function from other function
            Asked 2022-Feb-19 at 16:06

            For the below code

            ...

            ANSWER

            Answered 2022-Feb-19 at 15:58

            The problem is you call next on all values every time you call switchAction, since you define the dict over and over again. A solution to your problem can be as follows:

            Source https://stackoverflow.com/questions/71186546

            QUESTION

            Mixing yield and return. `yield [cand]; return` vs `return [[cand]]`. Why do they lead to different output?
            Asked 2022-Feb-17 at 20:53

            Why does

            ...

            ANSWER

            Answered 2022-Feb-17 at 20:53

            In a generator function, return just defines the value associated with the StopIteration exception implicitly raised to indicate an iterator is exhausted. It's not produced during iteration, and most iterating constructs (e.g. for loops) intentionally ignore the StopIteration exception (it means the loop is over, you don't care if someone attached random garbage to a message that just means "we're done").

            For example, try:

            Source https://stackoverflow.com/questions/71164795

            QUESTION

            Python Ruler Sequence Generator
            Asked 2022-Jan-29 at 16:12

            I have been struggling for a long time to figure how to define a generator function of a ruler sequence in Python, that follows the rules that the first number of the sequence (starting with 1) shows up once, the next two numbers will show up twice, next three numbers will show up three times, etc.

            So what I am trying to get is 1, 2, 2, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 7 etc.

            I understand that the way to do this is to have two separate count generators (itertools.count(1)) and then for every number in one generator yield number from the other generator:

            ...

            ANSWER

            Answered 2022-Jan-28 at 18:43

            QUESTION

            Are generators with context managers an anti-pattern?
            Asked 2022-Jan-17 at 17:17

            I'm wondering about code like this:

            ...

            ANSWER

            Answered 2022-Jan-17 at 14:48

            There are two answers to your question :

            • the absolutist : indeed, the context managers will not serve their role, the GC will have to clean the mess that should not have happened
            • the pragmatic : true, but is it actually a problem ? Your file handle will get released a few milliseconds later, what's the bother ? Does it have a measurable impact on production, or is it just bikeshedding ?

            I'm not an expert to Python alt implementations' differences (see this page for PyPy's example), but I posit that this lifetime problem will not occur in 99% of cases. If you happen to hit in prod, then yes, you should address it (either with your proposal, or a mix of generator with context manager) otherwise, why bother ? I mean it in a kind way : your point is strictly valid, but irrelevant to most cases.

            Source https://stackoverflow.com/questions/70729329

            QUESTION

            Python: Generate a unique batch from given dataset
            Asked 2021-Nov-27 at 06:30

            I'm applying a CNN to classify a given dataset.

            My function:

            ...

            ANSWER

            Answered 2021-Nov-25 at 17:50

            As @jodag suggests, using DataLoaders is a good idea.

            I have a snippet of that I use for some of my CNN in Pytorch

            Source https://stackoverflow.com/questions/70114892

            QUESTION

            Can I get the current value of generator in JavaScript?
            Asked 2021-Nov-06 at 22:06

            Let's say I want to rotate class names for my button on click. Clicked once becomes button-green, twice - button-yellow, thrice - button-red. And then it repeats, so fourth click makes it button-green again.

            I know other techniques how to do it, I'm not asking for implementation advice. I made up this example to understand something about generators in JavaScript.

            Here's my code with generator:

            ...

            ANSWER

            Answered 2021-Nov-06 at 19:59

            JavaScript "native" APIs generally are willing to create new objects with wild abandon. Conserving memory is generally not, by any appearances, a fundamental goal of the language committee.

            It would be quite simple to create a general facility to wrap the result of invoking a generator in an object that delegates the .next() method to the actual result object, but also saves each returned value as a .current() value (or whatever works for your application). Having a .current() is useful, for such purposes as a lexical analyzer for a programming language. The basic generator API, however, does not make provisions for that.

            Source https://stackoverflow.com/questions/69867197

            QUESTION

            Continue to other generators once a generator has been exhausted in a list of generators?
            Asked 2021-Oct-29 at 19:08

            I have a list of generators in a function alternate_all(*args) that alternates between each generator in the list to print their first item, second item, ..., etc. until all generators are exhausted.

            My code works until a generator is exhausted and once the StopIteration occurs, it stops printing, when I want it to continue with the rest of the generators and ignore the exhausted one:

            ...

            ANSWER

            Answered 2021-Oct-29 at 19:08

            See Kaya's answer, it is much better.

            Source https://stackoverflow.com/questions/69748145

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install pcfg_cracker

            Python3 is the only hard requirement for these tools
            It is highly recommended that you install the chardet python3 library for training. While not required, it performs character encoding autodetection of the training passwords. To install it:
            Download the source from https://pypi.python.org/pypi/chardet
            Or install it using pip3 install chardet

            Support

            If you notice any bugs, or if you have a feature you would like to see added, please open an issue on this github page. I also accept pull requests, though ideally please link a pull request to an issue so that I can more easily review it, ask questions, and better understand the changes you are making.
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            gh repo clone lakiw/pcfg_cracker

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            git@github.com:lakiw/pcfg_cracker.git

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