anaconda | Anaconda turns your Sublime Text | Code Editor library

by DamnWidget Python Version: v2.3.0 License: GPL-3.0

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | anaconda Summary

anaconda is a Python library typically used in Editor, Code Editor applications. anaconda has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has high support. You can download it from GitHub.

Anaconda turns your Sublime Text 3 into a full featured Python IDE. Read the plugin documentation on Donations help keep this project alive. Donate today.

Support

Quality

Security

License

Reuse

Support

anaconda has a highly active ecosystem.

It has 2188 star(s) with 266 fork(s). There are 70 watchers for this library.

It had no major release in the last 12 months.

There are 173 open issues and 614 have been closed. On average issues are closed in 328 days. There are 6 open pull requests and 0 closed requests.

It has a negative sentiment in the developer community.

The latest version of anaconda is v2.3.0

Quality

anaconda has 0 bugs and 0 code smells.

Security

anaconda has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

anaconda code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

anaconda is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

anaconda releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 61408 lines of code, 4986 functions and 387 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Re - stem suffixes
Convert a string to a python token .
Computes the continued indentation .
Relation of r1
Return a list of parameters that can be executed on the given function .
Parses the comments .
Marks the regions as markers .
Tokenize tokens .
Computes the rank of a line with indentation .
Visits a part .

Get all kandi verified functions for this library.

anaconda Key Features

No Key Features are available at this moment for anaconda.

anaconda Examples and Code Snippets

Installation-Anaconda

Python

Lines of Code : 1

License : Permissive (MIT)

Copy

conda install pyg -c pyg

For Anaconda

Python

Lines of Code : 0

License : Permissive (MIT)

Copy

git clone https://github.com/3b1b/manim.git
cd manim
conda create -n manim python=3.8
conda activate manim
pip install -e .

Installation via Anaconda

Python

Lines of Code : 0

License : Permissive (MIT)

Copy

conda install pyg -c pyg

Community Discussions

Trending Discussions on anaconda

Why Python native on M1 Max is greatly slower than Python on old Intel i5?

ImportError: cannot import name 'safe_str_cmp' from 'werkzeug.security'

"SpecNotFound: Invalid name, try the format: user/package" in Creating new Conda env with yml file (Windows 10)

Pandas: Calculate time in minutes between 2 columns, excluding weekends, public holidays and taking business hours into account

In R, how to use reticulate to import mplsoccer

How to undo/redo changes inside the selected cell in Jupyter notebook?

Why is this task faster in Python than Julia?

Creating a module subclass in a Python extension

Cannot update spyder=5.1.5 on new anaconda install

How to force keras to use tensorflow GPU backend

QUESTION

Why Python native on M1 Max is greatly slower than Python on old Intel i5?

Asked 2022-Mar-29 at 03:35

I just got my new MacBook Pro with M1 Max chip and am setting up Python. I've tried several combinational settings to test speed - now I'm quite confused. First put my questions here:

Why python run natively on M1 Max is greatly (~100%) slower than on my old MacBook Pro 2016 with Intel i5?
On M1 Max, why there isn't significant speed difference between native run (by miniforge) and run via Rosetta (by anaconda) - which is supposed to be slower ~20%?
On M1 Max and native run, why there isn't significant speed difference between conda installed Numpy and TensorFlow installed Numpy - which is supposed to be faster?
On M1 Max, why run in PyCharm IDE is constantly slower ~20% than run from terminal, which doesn't happen on my old Intel Mac.

Evidence supporting my questions is as follows:

Here are the settings I've tried:

1. Python installed by

Miniforge-arm64, so that python is natively run on M1 Max Chip. (Check from Activity Monitor, Kind of python process is Apple).
Anaconda. Then python is run via Rosseta. (Check from Activity Monitor, Kind of python process is Intel).

2. Numpy installed by

conda install numpy: numpy from original conda-forge channel, or pre-installed with anaconda.
Apple-TensorFlow: with python installed by miniforge, I directly install tensorflow, and numpy will also be installed. It's said that, numpy installed in this way is optimized for Apple M1 and will be faster. Here is the installation commands:

...

ANSWER

Answered 2021-Dec-06 at 05:53

Possible Cause: Different BLAS Libraries

Since the benchmark is running linear algebra routines, what is likely being tested here are the BLAS implementations. A default Anaconda distribution for osx-64 platform is going to come with Intel's MKL implementation; the osx-arm64 platform only has the generic Netlib BLAS and the OpenBLAS implementation options.

For me (MacOS w/ Intel i9), I get the following benchmark results:

BLAS Implmentation Mean Timing (s) mkl 0.95932 blis 1.72059 openblas 2.17023 netlib 5.72782

So, I suspect the old MBP had MKL installed, and the M1 system is installing either Netlib or OpenBLAS. Maybe try figuring out whether Netlib or OpenBLAS are faster on M1, and keep the faster one.

Specifying BLAS Implementation

Here are specifically the different environments I tested:

Source https://stackoverflow.com/questions/70240506

QUESTION

ImportError: cannot import name 'safe_str_cmp' from 'werkzeug.security'

Asked 2022-Mar-28 at 21:19

any ideas why this error?

my project was working fine, i copied it to an external drive and onto my laptop to work on the road, it worked fine. i copied back to my desktop and had a load of issues with invalid interpreters etc, so i made a new project and copied just the scripts in, made a new requirements.txt and installed all the packages, but when i run i get this error

...

ANSWER

Answered 2022-Mar-28 at 21:19

Werkzeug released v2.1.0 today, removing werkzeug.security.safe_str_cmp.

You can probably resolve this issue by pinning Werkzeug~=2.0.0 in your requirements.txt file (or similar).

Source https://stackoverflow.com/questions/71652965

QUESTION

"SpecNotFound: Invalid name, try the format: user/package" in Creating new Conda env with yml file (Windows 10)

Asked 2022-Mar-28 at 09:48

I'm trying to Create New conda environment by 'Anaconda Prompt' usnig yml File in Windows 10.
So here is the steps i made through:

1. using cd command i changed the directory to dir which my yml file located. (suppose my yml file is in c:/Users//.jupyter )
2. Then i used conda env create -f Python 310.yml command to create new conda env.

and what i got is:

SpecNotFound: Invalid name, try the format: user/package

Now I don't know how can I solve this problem and exactly what is the meaning of this error.

Appendix

my Python 310.yml file contains these stuff:

...

ANSWER

Answered 2021-Dec-03 at 13:59

issue solved by changing contents of Python 310.yml and renaming yml file to Python310.yml. Here is the final .yml file content:

Source https://stackoverflow.com/questions/69482678

QUESTION

Pandas: Calculate time in minutes between 2 columns, excluding weekends, public holidays and taking business hours into account

Asked 2022-Mar-24 at 14:16

I have the below issue and I feel I'm just a few steps away from solving it, but I'm not experienced enough just yet. I've used business-duration for this. I've looked through other similar answers to this and tried many methods, but this is the closest I have gotten (Using this answer). I'm using Anaconda and Spyder, which is the only method I have on my work laptop at the moment. I can't install some of the custom Business days functions into anaconda.

I have a large dataset (~200k rows) which I need to solve this for:

...

ANSWER

Answered 2022-Mar-24 at 14:16

Use:

Source https://stackoverflow.com/questions/71602636

QUESTION

In R, how to use reticulate to import mplsoccer

Asked 2022-Mar-23 at 20:33

I'm trying to import a python package (mplsoccer) via reticulate package but I can't: reticulate::py_install('mplsoccer')

This is the message I get:

...

ANSWER

Answered 2022-Mar-23 at 20:33

This isn't available through Conda, but is on PyPI. Try instead:

Source https://stackoverflow.com/questions/71588728

QUESTION

How to undo/redo changes inside the selected cell in Jupyter notebook?

Asked 2022-Feb-22 at 14:01

I am using Jupyter notebook (from anaconda Jupyter lab) on Windows 10 and tried to undo/redo changes in the selected cell. However, I can only undo/redo changes in the whole notebook.

For example, I edited cell#1 then cell#2. Say I want to undo changes in cell#1, so I go to cell#1 and press control+z, it will however undo the change in cell#2.

My friend using Mac doesn't have this issue. Are there any settings for this? I searched online and didn't find anyone who has the same problem. It is so weird!

...

ANSWER

Answered 2021-Oct-14 at 20:04

This global undo/redo is a new feature that enables Real Time Collaboration which was added in JupyterLab 3.1. It is indeed sub-optimal for many use cases.

JupyterLab 3.2 allows to disable notebook-wide history tracking (see issue 10791 nad PR 10949), but with a caveat: when moving cells you may loose the undo history, which is why the setting is marked as experimental (it requires more work to be exposed or enabled by a default). To get the selective undo/redo please add:

Source https://stackoverflow.com/questions/68763795

QUESTION

Why is this task faster in Python than Julia?

Asked 2022-Feb-05 at 08:27

I ran the following code in RStudio:

...

ANSWER

Answered 2022-Feb-04 at 14:54

It depends on what you want to test (i.e. if you want to test looping or just want the result fast). I assume you want the result fast and in a clean code, in which case I would write this operation in the following way in Julia:

Source https://stackoverflow.com/questions/70987896

QUESTION

Creating a module subclass in a Python extension

Asked 2022-Jan-06 at 17:50

I am trying to create a Python extension module with multi-phase initialization, following the advice I got from a previous question. PEP 489 suggests that it is preferable for the Py_mod_create function to return a module subclass, which presumably means a subclass of PyModule, but I cannot figure out how to do this. In all my attempts, the module segfaults when it is imported. It works fine if Py_mod_create returns some other object, (one which is not a subclass of PyModule), but I am not sure if this will cause problems in future, since isinstance(mymodule, types.ModuleType) returns false in this case.

Following the docs on subclassing built-in types, I set tp_base to PyModule_Type, and my tp_init function calls PyModule_Type.tp_init. The docs also suggest that my structure should contain the superclass structure at the beginning, which in this case is PyModuleObject. This structure is not in the public Python header files, (it is defined in moduleobject.c in the Python sources), so for now I copied and paste the definitions of the PyModuleObject fields at the start of my structure. The complete code looks like this:

...

ANSWER

Answered 2022-Jan-06 at 17:50

After some tests I could build a custom module type by copying parts of code from moduleobject.c

Your problem is that your code does create an instance of a subclass of module, but never initializes it and gets random values in key members. Additionaly, modules are expected to be gc collectables, so you have to create your custom module with PyObject_GC_New.

The following code replaces your initial testmod_create function with a full initialization of the module:

Source https://stackoverflow.com/questions/70608438

QUESTION

Cannot update spyder=5.1.5 on new anaconda install

Asked 2021-Nov-15 at 08:33

I installed anaconda and spyder came with the installation. Spyder 4.2.5 came with the installation and I got a pop up notification that spyder=5.1.5 is available. I tried

conda update anaconda

conda install spyder=5.1.5

and gets an error:

Solving environment: failed with initial frozen solve. Retrying with flexible solve.

I tried letting it run for more than 8 hours, but I had to cancel it because I got tired.

Tried

conda install anaconda spyder=5.1.5

and gets another error:

`Solving environment: failed with initial frozen solve. Retrying with flexible solve. Collecting package metadata (repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve.

PackagesNotFoundError: The following packages are not available from current channels:

ananconda

Current channels:

To search for alternate channels that may provide the conda package you're looking for, navigate to

...

ANSWER

Answered 2021-Oct-26 at 06:01

(Spyder maintainer here) Our regular instructions to update Spyder don't work in this case because there are some incompatible dependencies between Spyder 5.0.5 and 5.1.5.

To workaround this problem, you need to close Spyder and run the following commands in the Anaconda Prompt (or your system terminal on Linux or macOS):

Source https://stackoverflow.com/questions/69704561

QUESTION

How to force keras to use tensorflow GPU backend

Asked 2021-Oct-08 at 16:10

I know this is one of the popular questions, but none of the solutions worked for me, so far.

I'm running a legacy code that is written in tensorflow v1.13.1 and keras v2.2.4. I cannot modify the code to run latest tensorflow version. Since keras has now been merged into tensorflow, I'm facing problems installing the specific versions of tensorflow and keras via pip. I found that anaconda has option to install keras and tensorflow with the above version. So, I installed it with

...

ANSWER

Answered 2021-Oct-08 at 08:03

Let me start off with the assumption you're using an NVIDIA GPU. It's most likely due to you either not having CUDA installed or having the wrong version. Although, do double check to make sure you also have the latest NVIDIA drivers. If you look at this list you can see that tensorflow_gpu-1.13.1 uses CUDA version 10.0 and CudNN 7.4. To install those through anaconda use the following command.

Source https://stackoverflow.com/questions/69491795

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

Vulnerabilities

No vulnerabilities reported

Install anaconda

Anaconda works out of the box but there are multitude of options and features that you can tune and adapt to your own style or needs.
Powerful IDE
Advanced Configuration
Run Tests using Anaconda
Linting theme customization
Using Vagrant Environments

Support

This section lists some common issues faced by users, along with workarounds. Work-around: You have to update your Package Control version to the version 2.0 or better. Your Sublime Text can't find the interpreter that you set in your configuration, by default, anaconda sets this as python so it will get your configured Python interpreter in your PATH (if any). Work-around: Add a Python interpreter (named python) to your PATH or set a right full path to your python interpreter as parameter of python_interpreter settings option, for example /usr/local/bin/python3.4. Sublime Text 3's default Python package cancels the auto-completion when some words are detected (for example def or class). This list of words includes import. Work-around: Create a new Python directory in your Packages directory and copy the contents of the file Completion Rules.tmPreferences there with the same name. Delete your Sublime Text Cache file Cache/Python/Completion Rules.tmPreferences.cache. NOTE: The cache path can be obtained from the Sublime TExt 3 console using the code sublime.cache_path(). SublimeCodeIntel interferes with anaconda's auto-completion. Work-around: Consider disabling SublimeCodeIntel for Python views or disabling/removing it completely when using anaconda.

Find more information at: