devdocs | API Documentation Browser | Frontend Framework library

 by   freeCodeCamp Ruby Version: Current License: MPL-2.0

kandi X-RAY | devdocs Summary

kandi X-RAY | devdocs Summary

devdocs is a Ruby library typically used in User Interface, Frontend Framework, React, Electron applications. devdocs has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has medium support. You can download it from GitHub.

API Documentation Browser

            kandi-support Support

              devdocs has a medium active ecosystem.
              It has 31623 star(s) with 2139 fork(s). There are 631 watchers for this library.
              It had no major release in the last 6 months.
              There are 135 open issues and 948 have been closed. On average issues are closed in 126 days. There are 25 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of devdocs is current.

            kandi-Quality Quality

              devdocs has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              devdocs is licensed under the MPL-2.0 License. This license is Weak Copyleft.
              Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

            kandi-Reuse Reuse

              devdocs releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.
              It has 36196 lines of code, 1558 functions and 834 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed devdocs and discovered the below as its top functions. This is intended to give you an instant insight into devdocs implemented functionality, and help decide if they suit your requirements.
            • Runs the image .
            • Build a page
            • Takes an absolute path and returns the url that matches the url .
            • Builds the navigation links
            • Sort the number of strings
            • Fetch the url for the user
            • Returns a hash of options .
            • Returns the relative path relative to the destination directory
            • Normalize a path .
            • Return the diff of the given object
            Get all kandi verified functions for this library.

            devdocs Key Features

            No Key Features are available at this moment for devdocs.

            devdocs Examples and Code Snippets

            No Code Snippets are available at this moment for devdocs.

            Community Discussions


            Tensorflow rotate with random uniform take 1 positional argument but 2 were given
            Asked 2022-Apr-04 at 07:24

            I have the following code that uses tensorflow to calculate a custom average loss when the image is consistently rotated:



            Answered 2022-Apr-01 at 08:58

            The error might be coming from using TF tensors. As stated in the docs you linked regarding random_rotation:

            Performs a random rotation of a Numpy image tensor.

            Meaning you cannot use TF tensors with this operation. If you are in eager execution mode you can use tensor.numpy():



            Azure DevOps AzureFunctionApp@1 not installing python dependencies
            Asked 2022-Mar-21 at 16:40

            Using the Azure Devops task with current setup :



            Answered 2022-Mar-21 at 16:40

            Maybe you will have to use python 3.9 and the latest ubuntu agent in the pipeline




            Why I can't import torch windows
            Asked 2022-Mar-21 at 14:44

            I installed python 3.8.0, numpy 1.22.3, pytorch 1.11.0 . and I tried this code:import torch. But I'm getting this error:



            Answered 2022-Mar-21 at 14:44

            ** From the PyCharm Python Console you can digit ctrl+alt+S to access at the Project:pythonProject > Python Interpreter. Down in the page, you should see a + button to access to all available packages. Please, here search for torch and install it. Now try:**



            How can I resolve Python module import problems stemming from the failed import of NumPy C-extensions for running Spark/Python code on a MacBook Pro?
            Asked 2022-Mar-12 at 22:12

            When I try to run the (simplified/illustrative) Spark/Python script shown below in the Mac Terminal (Bash), errors occur if imports are used for numpy, pandas, or The sample Python code shown here runs well when using the 'Section 1' imports listed below (when they include from pyspark.sql import SparkSession), but fails when any of the 'Section 2' imports are used. The full error message is shown below; part of it reads: '' (mach-o file, but is an incompatible architecture (have 'arm64', need 'x86_64'). Apparently, there was a problem importing NumPy 'c-extensions' to some of the computing nodes. Is there a way to resolve the error so a variety of and other imports will function normally? [Spoiler alert: It turns out there is! See the solution below!]

            The problem could stem from one or more potential causes, I believe: (1) improper setting of the environment variables (e.g., PATH), (2) an incorrect SparkSession setting in the code, (3) an omitted but necessary Python module import, (4) improper integration of related downloads (in this case, Spark 3.2.1 (spark-3.2.1-bin-hadoop2.7), Scala (2.12.15), Java (1.8.0_321), sbt (1.6.2), Python 3.10.1, and NumPy 1.22.2) in the local development environment (a 2021 MacBook Pro (Apple M1 Max) running macOS Monterey version 12.2.1), or (5) perhaps a hardware/software incompatibility.

            Please note that the existing combination of code (in more complex forms), plus software and hardware runs fine to import and process data and display Spark dataframes, etc., using Terminal--as long as the imports are restricted to basic versions of pyspark.sql. Other imports seem to cause problems, and probably shouldn't.

            The sample code (a simple but working program only intended to illustrate the problem):



            Answered 2022-Mar-12 at 22:10

            Solved it. The errors experienced while trying to import numpy c-extensions involved the challenge of ensuring each computing node had the environment it needed to execute the target script ( It turns out this can be accomplished by zipping the necessary modules (in this case, only numpy) into a tarball (.tar.gz) for use in a 'spark-submit' command to execute the Python script. The approach I used involved leveraging conda-forge/miniforge to 'pack' the required dependencies into a file. (It felt like a hack, but it worked.)

            The following websites were helpful for developing a solution:

            1. Hyukjin Kwon's blog, "How to Manage Python Dependencies in PySpark"
            2. "Python Package Management: Using Conda":
            3. Alex Ziskind's video "python environment setup on Apple Silicon | M1, M1 Pro/Max with Conda-forge":
            4. conda-forge/miniforge on GitHub: (for Apple chips, use the Miniforge3-MacOSX-arm64 download for OS X (arm64, Apple Silicon).

            Steps for implementing a solution:

            1. Install conda-forge/miniforge on your computer (in my case, a MacBook Pro with Apple silicon), following Alex's recommendations. You do not yet need to activate any conda environment on your computer. During installation, I recommend these settings:



            NumPy setup / import issue in lambda function
            Asked 2022-Feb-12 at 23:12

            Runtime python 3.7 w/ compatible runtime 3.7

            I keep getting Import error when trying to test API in lambda function



            Answered 2022-Feb-12 at 23:12

            Based on the comments.

            The solution was to use Numpy layer provided by AWS.



            Unable to import Pandas on - Python
            Asked 2022-Feb-10 at 03:15

            I'm unable to import pandas with import pandas as pd on replit. I've already installed the package with pip install pandas and it can be seen in packages. I've successfully imported it to other projects on replit. Every time I try importing it into my code on this project, it gives me the following error:



            Answered 2022-Feb-10 at 03:15

            You don't need to use pip to install packages on -- and in fact, you shouldn't! Using Nix derivations not only works better (as you're using their OS distro the way it's designed), but also keeps their storage costs low, by allowing packages to be used from a read-only, hash-addressed, shared store.

            Binaries built for other distributions might assume that there will be libraries in /lib, /usr/lib, or the like, but that's not how NixOS works: Libraries will be in a path like /nix/store/--/lib, and those paths get embedded into the executables that use those libraries.

            The easiest thing to do here is to create a new bash repl, but to add a Python interpreter to it. (I suggest this instead of using a Python repl because the way they have their Python REPLs set up adds a bunch of extra tools that need to be reconfigured; a bash repl keeps it simple).

            • Create a new bash repl.
            • Click on the three-dots menu.
            • Select "Show Hidden Files".
            • Open the file named replit.nix
            • Edit the file by adding a Python interpreter with pandas, as follows:



            Numpy from alpine package repo fails to import c-extensions
            Asked 2022-Feb-05 at 18:50

            I am making a docker image that needs pandas and numpy but the installation via pip takes around 20 mins which is too long for my use case. I then opt to install pandas and numpy from alpine package repo but it seems to fail to import numpy correctly.

            Here is my Dockerfile:



            Answered 2021-Sep-28 at 11:25

            I know it's been a while since this was asked, and you might've found a solution, or moved on from Alpine to a different distro. But I ran into the same issue, and this was the first thing that popped up on my search. So, after spending a couple of hours and finding a solution, I think it's worthwhile to document it here.

            The issue is (obviously) with numpy and pandas packages. I used pre-built wheels from the community repo and ran into the same issue as you. So, evidently, the build process itself is introducing the issue. Specifically, if you look, e.g., under numpy/core at the install location (/usr/lib/python3.9/site-packages), you'll find that all the C-extensions have .cpython-39-x86_64-linux-musl in their name. So, for instance, the module you're having trouble with, numpy.core._multiarray_umath, is named, and not just Dropping the .cpython-39-x86_64-linux-musl from those filenames fixed the issue (edit: see addendum for details).

            The following line can be added to your Dockerfile after installing py3-pandas and py3-numpy to fix it:



            What is a "closure" in Julia?
            Asked 2022-Feb-03 at 18:34

            I am learning how to write a Maximum Likelihood implementation in Julia and currently, I am following this material (highly recommended btw!). So the thing is I do not fully understand what a closure is in Julia nor when should I actually use it. Even after reading the official documentation the concept still remain a bit obscure to me.

            For instance, in the tutorial, I mentioned the author defines the log-likelihood function as:



            Answered 2022-Feb-03 at 18:34

            In the context you ask about you can think that closure is a function that references to some variables that are defined in its outer scope (for other cases see the answer by @phipsgabler). Here is a minimal example:



            How does the methods function work in Julia?
            Asked 2022-Jan-22 at 03:48

            The methods function returns the method table of a function as also mentioned here. I am looking for an explanation on how the function works.

            Consider the following example in Julia 1.7:



            Answered 2022-Jan-22 at 03:48

            Ah, so to be a bit technical this is really more accurately a question about how type annotations, dispatch, optional arguments, and keyword arguments work in Julia; the methods function just gives you some insight into that process, but it's not the methods function that makes those decisions. To answer your individual questions

            It is not quite clear to me why there is no method f(::Int64, ::Float64) (hence the error).

            There is no method for this because you you can only omit optional normal (non-keyword) arguments contiguously from the last normal (non-keyword) argument. Consider the following case:



            Import c-modules from embedded Python interpreter (pybind11) in a shared object raises an undefined symbol exception
            Asked 2021-Dec-17 at 09:08

            Update (1): The same problem can be seen with some compiled stdlib modules. This is not related to numpy (I'm removing the numpy tag and numpy from the title)

            I'm writing a shared object (that is a plugin for a software) that contains an embedded python interpreter. The shared object launches an interpreter and the interpreter imports a python module to be executed. If the imported module includes numpy, I get an undefined symbol error. The actual undefined symbol error changes in function of the python version or numpy version, but it is always a struct of the PyExc_* family.

            I've simplified the issue to this mimimum example (it comprises actually two files):



            Answered 2021-Dec-17 at 09:08

            I've found a solution. Knowing that it was not tied to numpy halped quite a lot to switch the focus on the real problem: symbol missing. Taking the suggestion from this answer and in particular this point:

            Solve a problem. Load the library found in step 1 by dlopen first (use RTLD_GLOBAL there as well).

            I've modified the minimum example as follows:


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


            No vulnerabilities reported

            Install devdocs

            Unless you wish to contribute to the project, we recommend using the hosted version at It's up-to-date and works offline out-of-the-box. DevDocs is made of two pieces: a Ruby scraper that generates the documentation and metadata, and a JavaScript app powered by a small Sinatra app.


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