pyfaker | generating pseudo-random data | Generator Utils library

 by   hayd Python Version: 0.1dev License: MIT

kandi X-RAY | pyfaker Summary

kandi X-RAY | pyfaker Summary

pyfaker is a Python library typically used in Generator, Generator Utils applications. pyfaker has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install pyfaker' or download it from GitHub, PyPI.

A python library for generating pseudo-random (but "realistic") data.
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            kandi-support Support

              pyfaker has a low active ecosystem.
              It has 14 star(s) with 4 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 0 open issues and 2 have been closed. On average issues are closed in 134 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of pyfaker is 0.1dev

            kandi-Quality Quality

              pyfaker has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              pyfaker 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

              pyfaker 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, examples and code snippets are available.
              It has 350 lines of code, 55 functions and 9 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pyfaker and discovered the below as its top functions. This is intended to give you an instant insight into pyfaker implemented functionality, and help decide if they suit your requirements.
            • Save a list of langs
            • Convert a JSON object to plain text
            • Get yaml file
            • Return the current working path
            • Parse a regular expression
            • Build a string from a parsed state
            • Handles a given state
            • Generate a lorem sentence
            • Generate a random Lorem sentence
            • Try to find a state in value
            • Handles a repeat
            • Return a list of available locale names
            • Handle groups
            Get all kandi verified functions for this library.

            pyfaker Key Features

            No Key Features are available at this moment for pyfaker.

            pyfaker Examples and Code Snippets

            Usage
            Pythondot img1Lines of Code : 42dot img1License : Permissive (MIT)
            copy iconCopy
            In [1]: from pyfaker import Fake
            
            In [2]: fake = Fake(lang_code='en')
            
            In [3]: fake.Address.street_address()
            Out[3]: u'72449 Ward Shore'
            
            In [4]: fake.Address.street_address()
            Out[4]: u'7954 Waelchi Mall'
            
            In [5]: fake.Company.bs()
            Out[5]: u'whiteboa  
            Creating random classes
            Pythondot img2Lines of Code : 10dot img2License : Permissive (MIT)
            copy iconCopy
            class Person:
                def __init__(self, fake=Fake()):
                    self.name = fake.Name.name()
                    self.phone_number = fake.PhoneNumber.formats()
            
            p = Person()
            
            # access the attributes
            p.name
            p.phone_number
              
            How to install
            Pythondot img3Lines of Code : 1dot img3License : Permissive (MIT)
            copy iconCopy
            pip install pyfaker
              

            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 pyfaker

            The easiest way is to install via pip:.

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            Please create a github issue, if you can fix whatever it: pull-requests are much appreciated! :).
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            pip install pyfaker

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