codetools | using api | REST library

 by   tinyfool Python Version: Current License: BSD-2-Clause

kandi X-RAY | codetools Summary

kandi X-RAY | codetools Summary

codetools is a Python library typically used in Web Services, REST applications. codetools has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

using api to help manage codes (like count all codes lines etc.).

            kandi-support Support

              codetools has a low active ecosystem.
              It has 8 star(s) with 0 fork(s). There are 2 watchers for this library.
              It had no major release in the last 6 months.
              codetools has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of codetools is current.

            kandi-Quality Quality

              codetools has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              codetools is licensed under the BSD-2-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              codetools releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              It has 45 lines of code, 2 functions and 1 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed codetools and discovered the below as its top functions. This is intended to give you an instant insight into codetools implemented functionality, and help decide if they suit your requirements.
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            codetools Key Features

            No Key Features are available at this moment for codetools.

            codetools Examples and Code Snippets

            No Code Snippets are available at this moment for codetools.

            Community Discussions


            mlr3 AutoFSelector glmnet: Error in (if(cv)glmnet::cv.glmnet else glmnet::glmnet)(x = data, y = target, :# x should be a matrix with 2 or more columns
            Asked 2022-Jan-24 at 18:05

            I am a beginner on mlr3 and am facing problems while running AutoFSelector learner associated to glmnet on a classification task containing >2000 numeric variables. I reproduce this error while using the simpler mlr3 predefined task Sonar. For note, I am using R version 4.1.2 (2021-11-01)on macOS Monterey 12.1. All required packages have been loaded on CRAN.



            Answered 2022-Jan-24 at 18:05

            This is a problem specific to glmnet. glmnet requires at least two features to fit a model, but in at least one configuration (the first ones in a sequential forward search) you only have one feature.

            There are two possibilities to solve this:

            1. Open an issue in mlr3fselect and request a new argument min_features (there already is max_features) to be able to start the search with 2 or more features.
            2. Augment the base learner with a fallback which gets fitted if the base learner fails. Here is fallback to a simple logistic regression:



            Error while predicting a GAM model using tidymodels
            Asked 2022-Jan-12 at 23:47

            WHAT I WANT: I'm trying to fit a GAM model for classification using tidymodels on a given data.

            SO FAR: I'm able to fit a logit model.



            Answered 2022-Jan-12 at 23:47

            This problem has been fixed in the developmental version of {parsnip} (>0.1.7). You can install it by running remotes::install_github("tidymodels/parsnip").



            "Error occurred while GetObject. S3 Error Code: PermanentRedirect. S3 Error Message: The bucket is in this region: us-east-1
            Asked 2021-Nov-28 at 16:53

            I try to follow this workshop, every thing well but when I try to create the lambda usinging cloudformation I got an error:



            Answered 2021-Nov-28 at 16:53

            First things first, Lambda and S3 need to be in the same region.

            Secondly, it looks like you're not the bucket owner (you haven't created the bucket yourself by looking at the template).

            This means, the bucket you're using to retrieve the Lambda source code from is (I suppose coming from the workshop), and they decided to create that bucket in the region us-east-1. Enforcing you to also deploy your stack in the region us-east-1 (if you want to follow the workshop).

            But what if you really wanted to deploy this stack to eu-west-1?

            That would mean you need to create a bucket in region eu-west-1 with and copy the objects from the workshop bucket into your newly created bucket and update your CloudFormation template to point and retrive the Lambda source code from your newly created bucket (note you might need to name the bucket differently as bucket names are globally shared).

            I hope this is a bit clear.



            no applicable method for 'prep' applied to an object of class
            Asked 2021-Nov-07 at 21:41

            I am building a custom recipes function and getting an error when I try to prep() the recipe. I get the following error:



            Answered 2021-Nov-07 at 21:41

            @importFrom recipes prep bake had to be added to the .R file



            SVM prediction running fine in my computer but not in R Connect
            Asked 2021-Aug-06 at 04:41

            I’m creating a Shiny app that uses the caret package to do some SVM free-text analysis.

            The app runs fine without any error in my computer. I’m using R x64 4.0.4 and R studio 1.3.1093

            I’m deploying app to an internal enterprise server

            This app is deployed in the server and started.
            But when I reach the line where I run the train function:



            Answered 2021-Aug-05 at 01:15

            Errors like this in Shiny apps are almost always a result of missing packages, which the logs confirm.

            Turns out in this case I think the missing package is kernlab, which I only found by reading the documentation given here: It's a suggested package, not imported, so the command suggested in the comments by heds1 would sort this out.



            passing a list of variables to recipe in tidymodels causes model error
            Asked 2021-Jul-05 at 15:56

            I have a simple recipe to train a model. My categorical variables are changing over time and sometimes I want a numerical to be treated as categorical (postal code) , so I define a list prior to recipe containing them. (just for the sake of the argument, the list is much longer)

            recipe worked ok, and then trained my model (3 folds) but an error is raised.



            Answered 2021-Jul-05 at 15:56

            You definitely were passing the vector of variables correctly to the recipe -- no problem there!

            You were running into other problems with your model fitting. An xgboost model requires all predictors to be numeric, so if you convert something like zip code to factors, you need to then use step_dummy(). If you have something of high cardinality like zip codes, you probably will need to handle new levels or unknown levels as well.



            tidymodel recipe and `step_lag()`: Error when using `predict()`
            Asked 2020-Oct-19 at 19:49

            This may be a usage misunderstanding, but I expect the following toy example to work. I want to have a lagged predictor in my recipe, but once I include it in the recipe, and try to predict on the same data using a workflow with the recipe, it doesn't recognize the column foo and cannot compute its lag.

            Now, I can get this to work if I:

            1. Pull the fit out of the workflow that has been fit.
            2. Independently prep and bake the data I want to fit.

            Which I code after the failed workflow fit, and it succeeds. According to the documentation, I should be able to put a workflow fit in the predict slot:

            I am probably fundamentally misunderstanding how workflow is supposed to operate. I have what I consider a workaround, but I do not understand why the failed statement isn't working in the way the workaround is. I expected the failed workflow construct to work under the covers like the workaround I have.

            In short, if work_df is a dataframe, the_rec is a recipe based off work_df, rf_mod is a model, and you create the workflow rf_workflow, then should I expect the predict() function to work identically in the two predict() calls below?



            Answered 2020-Oct-19 at 19:49

            The reason you are experiencing an error is that you have created a predictor variable from the outcome. When it comes time to predict on new data, the outcome is not available; we are predicting the outcome for new data, not assuming that it is there already.

            This is a fairly strong assumption of the tidymodels framework, for either modeling or preprocessing, to protect against information leakage. You can read about this a bit more here.

            It's possible you already know about these resources, but if you are working with time series models, I'd suggest checking out these resources:



            renv 0.12.0 was loaded from project library, but renv 0.11.0 is recorded in lockfile
            Asked 2020-Sep-15 at 22:47

            Upon opening a project on rstudio i have the following Warning:



            Answered 2020-Sep-15 at 22:47

            I think this is ultimately a small bug in renv. Here's my guess at what's happening:

            1. While this project has been initialized as an renv project, it does not have a lockfile for some reason. (Perhaps renv::activate() was called to initialize renv without explicitly creating a lockfile?)

            2. The project has an renv autoloader; this is from a script at renv/activate.R. That script is configured to load renv 0.11.0.

            3. When the project is loaded, renv finds that renv 0.12.0 is installed in the project library, not the expected version 0.11.0. This causes the warning to be emitted. (Perhaps renv was updated in that project previously?)

            So, ultimately, the warning is misleading here -- the request for renv 0.11.0 comes directly from the autoloader, not from the lockfile (which does not exist). As for why the lockfile does not exist, I'm not sure -- but it most likely implies the project was initialized via renv::activate(), and not by renv::init().

            All that said -- you can safely re-generate the lockfile via renv::snapshot().



            Tidymodels tune_grid: "Can't subset columns that don't exist" when not using formula
            Asked 2020-Jul-22 at 00:14

            I've put together a data preprocessing recipe for the recent coffee dataset featured on TidyTuesday. My intention is to generate a workflow, and then from there tune a hyperparameter. I'm specifically interesting in manually declaring predictors and outcomes through the various update_role() functions, rather than using a formula, since I have some great plans for this style of variable selection (it's a really great idea!).

            The example below produces a recipe that works just fine with prep and bake(coffee_test). It even works if I deselect the outcome column, eg. coffee_recipe %>% bake(select(coffee_test, -cupper_points)). However, when I run the workflow through tune_grid I get the errors as shown. It looks like tune_grid can't find the variables that don't have the "predictor" role, even though bake does just fine.

            Now, if I instead do things the normal way with a formula and step_rm the variables I don't care about, then things mostly work --- I get a few warnings for rows with missing country_of_origin values, which I find strange since I should be imputing those. It's entirely possible I've misunderstood the purpose of roles and how to use them.



            Answered 2020-Jul-22 at 00:14

            The error here occurs because on step_string2factor() during tuning, the recipe starts trying to handle variables that don't have any roles, like species and owner.

            Try setting the role for all of your nominal variables before picking out the outcomes and predictors.



            Cannot use include_graphics to insert png in Rmarkdown (error: file is not in PNG format)
            Asked 2020-May-11 at 07:01

            This error is very strange. When I knitr the doc, I got the following error:



            Answered 2020-May-11 at 04:17

            I think that the issue might be where your Rmd is located. The working directory automatically gets changed to that location when knitting. You could either change the root directory (Setting work directory in knitr using opts_chunk$set(root.dir = ...) doesn't work), or simply use paths that first go "up" to the main directory of your R project ("../figure.png").


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


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            Install codetools

            You can download it from GitHub.
            You can use codetools 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.


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