GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Already on GitHub? Sign in to your account. Added arm64 test support in travis-ci. Modified environment creation by using archiconda instead of miniconda as miniconda is not supported in arm64 currently.
But looks like some old changes got mixed with this PR. And also, I don't think we need most of the if statements that you have. I'd start this PR from zero, you shouldn't need much more than the new build in. I guess they were tests, but in any case, we don't want this. If so can you fix merge conflicts and address comments?Install Anaconda on Ubuntu 16.04
Hi WillAydI am working on it. I will let you know once I am done. Hi WillAyd and datapythonista. I have removed archiconda and updated it to miniforge. It does not require sudo permissions to run conda commands as it is similar to miniconda. By this we can remove all the unwanted code as suggested previously. So, I have removed the same for arm64 platform. We surely don't want different pytest calls.
Thanks for the feedback. All flags are not supported for pytest command in arm So, I have removed these flags for arm64 jobs.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Have a question about this project?
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But I want to see the bit version. If we can not install miniconda3 to aarch64, I like to work and contribute to achieve it for conda. I don't think Anaconda the company officially supports an aarch64 build. To my knowledge, it is a work in progress. A few people at conda-forge including myself are working on making conda installable on aarch You are working for that.
That's great. I will see the code. What is archiconda and c4aarch64 channel? You mean Slack or IRC channel on free node server? So, it might be a good timing for conda to provide the aarch64 installer. My personal motivation is that I want to install some bioconda packages to aarch64 environment. I think adding multi arch environment like aarch64 to your CI development environment is easy with the container image.
Here is the example of Travis CI of my repository. Potentially, currently there aren't many packages built. We are kinda stuck on numpy and generally the larger scientific stack due to the need to ensure that we aren't introducing bugs by compiling using emulated hardware. Regarding limited packages e.
Also I don't see why compiling numpy for aarch64 would be impossible It certainly is installable via pipGitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
Already on GitHub? Sign in to your account. A bit of a long shot here but i'm wondering if anyone has experience getting Anaconda working on an Nvidia Jetson tx1 or tx2? I understand it's a bit of an unusual requirement.
The distro is linux for tegra which looks to be ubuntu I thought that given its linux 64 running ubuntu that conda should run however at the end of running the bash script i get a lovely error. I'd love to tackle this, but it would be a non-trivial amount of work so we'd probably need a customer to pay for us to do it. If it does work please know that the packages in the repository for that platform are quite old and are not being updated. AArch64 can run armv7a just fine, but you aren't taking full advantage of the CPU far from it.
A proper Tegra port should be AAch64 only, use neon for floating point and should try to take advantage of Cuda where possible. Sorry, have not been able to look at this till now. Same for python 3 though would prefer to stick with 2 for now - 32 bit versions appear to be working! They would not work on the NVidia Jetson. Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.
Sign up. New issue. Jump to bottom. Conda on Nvidia Jetson tx1 tx2? Copy link Quote reply. This comment has been minimized. Sign in to view. Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment. Linked pull requests. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Already on GitHub? Sign in to your account. Hi, Did you ever think about building conda package for ARM architecture? Since Augustconda is officially supporting ARMv7l architecture.
It is possible to start ARM Docker container from an intel arch thanks to qemu-arm-static. It could be used to build every conda-forge packages for arm platform with travis-ci or circle-ci. There's a good chance that one will need to run such a Docker container in privileged mode.
There is no need to run container in privileged mode. But, with a minor modification on qemu, it is possible to embed it on the image and run the ARM image without anything special on the host. I wonder if, in this case, using the linaro tool chain to cross compile would be a good a option.
In background, they both use Qemu for the ARM emulation, so the overhead is the same. I'm totally up for this. I've suffered conda build on the RaspberryPi and it was a terrible experience conda build One idea I was toying with earlier was actually having another org for this.
It may sound a bit extreme, but this is something that one of the Homebrew devs did when they wanted to support Mac OS At least worth keeping in the back of our minds if nothing else. The problem of build time is really an issue we have to deal with.
Scaleway have great and cheap hardware, but I suppose that managing money and donations for build is out of the scope of conda-forge. Managing money is achievable e. NumFOCUSmanaging hardware is harder and the software infrastructure around it - it would ultimately take time away from other conda-forge activities.
I have long wanted a CI service where we can attach donated systems e. Hope that is ok. Thanks everyone for bring this up and providing interesting suggestions. Looking forward to seeing what others might contribute.
They are available on the rpi channel on Anaconda. I'll be adding docs, a README, proper license, etc and likely renaming this repo in the next week but wanted to give conda-forge folks a heads up.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again.
If nothing happens, download the GitHub extension for Visual Studio and try again. A collection of conda recipes for cross compiling libraries, python, and python extensions for iOS and Android. These recipes have been tested and confirmed working using enaml-native.
Visit anaconda. Currently all recipes are built for 2. Note: All libs and extensions are built as unstripped shared modules. Android strips libraries automatically. Only developers of packages should need to build recipes. End users should be able to simply install and use prebuilt versions. See the conda docs to get started. Otherwise all packages would need to be built from mac osx. Note: If using linux with an encrypted home directory you may have to build in a different root to avoid "path to long" errors.
Now that both python 2. In addition to specifying a build string, any requirements that have python extensions must filter by the build string since conda does not do this automatically at the moment. Failure to include python as a run requirement may cause conda to install the incorrect packages ie a 2. In order to make your package "installable" from other operating systems ie windows the recipe must use noarch:generic in the build parameters as follows.
This requires conda. The preferred method is to install miniconda3 from conda. Pure python packages can be installed with pip using the --target to tell it where to install.
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Hi I am trying to install Miniconda2 4. Everything starts fine till it installs:setuptools You appear to have downloaded the wrong package as indicated by the x86 in the file name. You appear to be trying to install the generic Linux installer. You need the arm version designed for the Pi 3's architecture. Miniconda3 Linux armv7l Python 3. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. Which Miniconda version should I use with Raspberry Pi 3?
Ask Question. Asked 4 years ago. Active 1 year, 10 months ago. Viewed 12k times. Is there already any version of Miniconda which I can run on the Pi3? Steve Robillard Randy Welt Randy Welt 1 1 gold badge 1 1 silver badge 3 3 bronze badges. Active Oldest Votes. This is the version needed for the Pi3: Miniconda3 Linux armv7l Python 3.
The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. In the Anaconda repositorythere are two types of installers:. Besides, for an installer file, Anaconda The difference is that miniconda is just shipping the repository management system. So when you install it there is just the management system without packages.
Whereas with Anaconda, it is like a distribution with some built in packages. Like with any Linux distribution, there are some releases which bundles lots of updates for the included packages. That is why there is a difference in version numbering.
If you only decide to upgrade Anaconda, you are updating a whole system. I use Miniconda myself. Anaconda is bloated. Many of the packages are never used and could still be easily installed if and when needed.
Note that Conda is the package manager e. A software distribution is a collection of packages, pre-built and pre-configured, that can be installed and used on a system. A package manager is a tool that automates the process of installing, updating, and removing packages.
Anaconda is a full distribution of the central software in the PyData ecosystem, and includes Python itself along with the binaries for several hundred third-party open-source projects. Miniconda is essentially an installer for an empty conda environment, containing only Conda, its dependencies, and Python.
Once Conda is installed, you can then install whatever package you need from scratch along with any desired version of Python. Strangely, it is not listed in their Old Package Lists. In Aprilthe Anaconda versioning jumped from 2. Version 4. Release notes for subsequent versions can be found here.