markovify | A simple , extensible Markov chain generator | Natural Language Processing library

 by   jsvine Python Version: 0.9.4 License: MIT

kandi X-RAY | markovify Summary

kandi X-RAY | markovify Summary

markovify is a Python library typically used in Telecommunications, Media, Media, Entertainment, Artificial Intelligence, Natural Language Processing applications. markovify has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install markovify' or download it from GitHub, PyPI.

Markovify is a simple, extensible Markov chain generator. Right now, its primary use is for building Markov models of large corpora of text and generating random sentences from that. However, in theory, it could be used for other applications.

            kandi-support Support

              markovify has a medium active ecosystem.
              It has 3131 star(s) with 341 fork(s). There are 69 watchers for this library.
              It had no major release in the last 12 months.
              There are 10 open issues and 64 have been closed. On average issues are closed in 121 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of markovify is 0.9.4

            kandi-Quality Quality

              markovify has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              markovify is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              markovify releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              markovify saves you 275 person hours of effort in developing the same functionality from scratch.
              It has 750 lines of code, 78 functions and 11 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed markovify and discovered the below as its top functions. This is intended to give you an instant insight into markovify implemented functionality, and help decide if they suit your requirements.
            • Generate a list of sentences from text
            • Check if a string is an abbreviation
            • Determine if the word is an English sentence
            • Split text into sentences
            • Combine multiple models
            • Create a State from a JSON object
            • Create a document from a chain
            • Compile the chain
            • Calculates the sum of an iterable
            • Compile the next dict
            • Create an instance from a JSON string
            • Create a chain from a dictionary
            • Compute the initial state of the model
            Get all kandi verified functions for this library.

            markovify Key Features

            No Key Features are available at this moment for markovify.

            markovify Examples and Code Snippets

            Save iteration's result from Markov Chain Python
            Pythondot img1Lines of Code : 12dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def f():
                result = [] 
                for i in range(300): # Generate 300 sentences 
                return result
            sentences = f()
            def f():
                return [text_model.mak
            In python, is there a way to remove all text following the last instance of a delimiter?
            Pythondot img2Lines of Code : 6dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            txt = 'some.text.with.dots'
            all_but_last = txt.rsplit('.', 1)[0]
            How to know where to join by space in spaCy NLP output
            Pythondot img3Lines of Code : 4dot img3License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            [bool(token.whitespace_) for token in nlp("don't")]
            [False, False]
            how to automate multiple file generation in Python
            Pythondot img4Lines of Code : 5dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            for nr in range(100):
                with open("file{:04}.txt".format(nr), "w") as f:
                    for i in range(10): #10 lines of fake sentences.
                        f.write(text_model.make_sentence() + "\n")
            Python, markov chains and reading large json files
            Pythondot img5Lines of Code : 12dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def get_filenames(path):
                for root, dirs, files in os.walk(path):
                    for file in files:
                        if file.endswith(".json"):
                             yield os.path.join(root, file)
            def build_it(path):
                for file in get_filenames(path)
            copy iconCopy
                def word_split(self, sentence):
                    words = re.split(self.word_split_pattern, sentence)
                    words = [w for w in words if len(w) > 0]
                    words = [" :: ".join(tag) for tag in nltk.pos_tag(words)]
                    words = words.enc
            Programming a discord bot in python, ran into the error "string index out of range"
            Pythondot img7Lines of Code : 4dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            words = re.split(self.word_split_pattern, sentence)
            words = [w for w in words if len(w) > 0]
            Making a discord bot, but keep getting "missing 1 required positional argument: 'self'"
            Pythondot img8Lines of Code : 4dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            text_model = POSifiedText(text, state_size=1)
            Pip not installing Python modules to proper directory
            Pythondot img9Lines of Code : 7dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            $ python --version 
            Python 2.7.10
            $ command -v python
            $ /Library/Frameworks/Python.framework/Versions/3.5/bin/python -c 'import markovify'

            Community Discussions

            Trending Discussions on markovify


            Save iteration's result from Markov Chain Python
            Asked 2020-Jun-08 at 21:40

            In the context of Natural language Generation (NLG), I want to generate 300 sentences with Python's library "Markovify" base on the principle of Makov Chain. My input file which containing text is "SD".

            First, I was able to print all the iteration's (=300) results (texts) with the following code :



            Answered 2020-Jun-08 at 21:40

            The result = [] must be before the for loop, or you initialise it every iteration:


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


            No vulnerabilities reported

            Install markovify

            You can install using 'pip install markovify' or download it from GitHub, PyPI.
            You can use markovify like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            pip install markovify

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            gh repo clone jsvine/markovify

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