Tag Archives: raspberry pi

The Code Club International movement

Post Syndicated from Katherine Leadbetter original https://www.raspberrypi.org/blog/code-club-international/

Over the past few years, Code Club has made strides toward world domination! There are now more than 10,000 Code Clubs running in 125 countries. More than 140,000 kids have taken part in our clubs in places as diverse as the northernmost tip of Canada and the favelas of Rio de Janeiro.

In the first video from our Code Club International network, we find out about Code Clubs around the world from the people supporting these communities.

Global communities

Code Club currently has official local partners in twelve countries. Our passionate and motivated partner organisations are responsible for championing their countries’ Code Clubs. In March we brought the partners together for the first time, and they shared what it means to be part of the Code Club community:

You can help Code Club make a difference around the world

We invited our international Code Club partners to join us in London and discuss why we think Code Club is so special. Whether you’re a seasoned pro, a budding educator, or simply want to give back to your local community, there’s a place for you among our incredible Code Club volunteers.

Of course, Code Clubs aren’t restricted to countries with official partner communities – they can be started anywhere in the world! Code Clubs are up and running in a number of unexpected places, from Kosovo to Kazakhstan.

Code Club International

Code Club partners gathered together at the International Meetup

The geographical spread of Code Clubs means we hear of clubs overcoming a range of different challenges. One club in Zambia, run by volunteer Mwiza Simbeye, started as a way to get kids off the streets of Lusaka and teach them useful skills. Many children attending had hardly used a computer before writing their first line of code at the club. And it’s making a difference! As Mwiza told us, ‘you only need to see the light shine in the eyes of [Code Club] participants to see how much they enjoy these sessions.’

Code Club International

Student Joyce codes in Scratch at her Code Club in Nunavut, Canada

In the Nunavut region of Canada, Talia Metuq was first introduced to coding at a Code Club. In an area comprised of 25 Inuit communities that are inaccessible via roads and currently combating severe social and economic deprivation, computer science was not on the school timetable. Code Club, along with club volunteer Ryan Oliver, is starting to change that. After graduating from Code Club, Talia went on to study 3D modelling in Vancouver. She has now returned to Nunavut and is helping inspire more children to pursue digital making.

Start a Code Club

Code Clubs are volunteer-led extra-curricular coding clubs for children age 9 to 13. Children that attend learn to code games, animations, and websites using the projects we provide. Working with volunteers and with other children in their club, they grow their digital skillset.

You can run a Code Club anywhere if you have a venue, volunteers, and kids ready to learn coding. Help us achieve our goal of having a Code Club in every community in the world!

To find out how to start a Code Club outside of the UK, you can visit the Code Club International website. If you are in the UK, head to the Code Club UK website for more information.

Code Club International

Help the Code Club International community grow

On the Code Club site, we currently have projects in 28 languages, allowing more young people than ever to learn programming in their native language. But that’s not enough! We are always on the lookout for volunteers to translate projects and resources. If you are proficient in translating from English and would like to help, please visit the website to find out more.

We are also looking for official local partners in Italy and Germany to join our international network – if you know of, or are a part of an enthusiastic non-profit organisation who might be interested to join us, you can learn more here.

The post The Code Club International movement appeared first on Raspberry Pi.

mkosi — A Tool for Generating OS Images

Post Syndicated from Lennart Poettering original http://0pointer.net/blog/mkosi-a-tool-for-generating-os-images.html

Introducing mkosi

After blogging about
casync
I realized I never blogged about the
mkosi tool that combines nicely
with it. mkosi has been around for a while already, and its time to
make it a bit better known. mkosi stands for Make Operating System
Image
, and is a tool for precisely that: generating an OS tree or
image that can be booted.

Yes, there are many tools like mkosi, and a number of them are quite
well known and popular. But mkosi has a number of features that I
think make it interesting for a variety of use-cases that other tools
don’t cover that well.

What is mkosi?

What are those use-cases, and what does mkosi precisely set apart?
mkosi is definitely a tool with a focus on developer’s needs for
building OS images, for testing and debugging, but also for generating
production images with cryptographic protection. A typical use-case
would be to add a mkosi.default file to an existing project (for
example, one written in C or Python), and thus making it easy to
generate an OS image for it. mkosi will put together the image with
development headers and tools, compile your code in it, run your test
suite, then throw away the image again, and build a new one, this time
without development headers and tools, and install your build
artifacts in it. This final image is then “production-ready”, and only
contains your built program and the minimal set of packages you
configured otherwise. Such an image could then be deployed with
casync (or any other tool of course) to be delivered to your set of
servers, or IoT devices or whatever you are building.

mkosi is supposed to be legacy-free: the focus is clearly on
today’s technology, not yesteryear’s. Specifically this means that
we’ll generate GPT partition tables, not MBR/DOS ones. When you tell
mkosi to generate a bootable image for you, it will make it bootable
on EFI, not on legacy BIOS. The GPT images generated follow
specifications such as the Discoverable Partitions
Specification
,
so that /etc/fstab can remain unpopulated and tools such as
systemd-nspawn can automatically dissect the image and boot from
them.

So, let’s have a look on the specific images it can generate:

  1. Raw GPT disk image, with ext4 as root
  2. Raw GPT disk image, with btrfs as root
  3. Raw GPT disk image, with a read-only squashfs as root
  4. A plain directory on disk containing the OS tree directly (this is useful for creating generic container images)
  5. A btrfs subvolume on disk, similar to the plain directory
  6. A tarball of a plain directory

When any of the GPT choices above are selected, a couple of additional
options are available:

  1. A swap partition may be added in
  2. The system may be made bootable on EFI systems
  3. Separate partitions for /home and /srv may be added in
  4. The root, /home and /srv partitions may be optionally encrypted with LUKS
  5. The root partition may be protected using dm-verity, thus making offline attacks on the generated system hard
  6. If the image is made bootable, the dm-verity root hash is automatically added to the kernel command line, and the kernel together with its initial RAM disk and the kernel command line is optionally cryptographically signed for UEFI SecureBoot

Note that mkosi is distribution-agnostic. It currently can build
images based on the following Linux distributions:

  1. Fedora
  2. Debian
  3. Ubuntu
  4. ArchLinux
  5. openSUSE

Note though that not all distributions are supported at the same
feature level currently. Also, as mkosi is based on dnf
--installroot
, debootstrap, pacstrap and zypper, and those
packages are not packaged universally on all distributions, you might
not be able to build images for all those distributions on arbitrary
host distributions. For example, Fedora doesn’t package zypper,
hence you cannot build an openSUSE image easily on Fedora, but you can
still build Fedora (obviously…), Debian, Ubuntu and ArchLinux images
on it just fine.

The GPT images are put together in a way that they aren’t just
compatible with UEFI systems, but also with VM and container managers
(that is, at least the smart ones, i.e. VM managers that know UEFI,
and container managers that grok GPT disk images) to a large
degree. In fact, the idea is that you can use mkosi to build a
single GPT image that may be used to:

  1. Boot on bare-metal boxes
  2. Boot in a VM
  3. Boot in a systemd-nspawn container
  4. Directly run a systemd service off, using systemd’s RootImage= unit file setting

Note that in all four cases the dm-verity data is automatically used
if available to ensure the image is not tempered with (yes, you read
that right, systemd-nspawn and systemd’s RootImage= setting
automatically do dm-verity these days if the image has it.)

Mode of Operation

The simplest usage of mkosi is by simply invoking it without
parameters (as root):

# mkosi

Without any configuration this will create a GPT disk image for you,
will call it image.raw and drop it in the current directory. The
distribution used will be the same one as your host runs.

Of course in most cases you want more control about how the image is
put together, i.e. select package sets, select the distribution, size
partitions and so on. Most of that you can actually specify on the
command line, but it is recommended to instead create a couple of
mkosi.$SOMETHING files and directories in some directory. Then,
simply change to that directory and run mkosi without any further
arguments. The tool will then look in the current working directory
for these files and directories and make use of them (similar to how
make looks for a Makefile…). Every single file/directory is
optional, but if they exist they are honored. Here’s a list of the
files/directories mkosi currently looks for:

  1. mkosi.default — This is the main configuration file, here you
    can configure what kind of image you want, which distribution, which
    packages and so on.

  2. mkosi.extra/ — If this directory exists, then mkosi will copy
    everything inside it into the images built. You can place arbitrary
    directory hierarchies in here, and they’ll be copied over whatever is
    already in the image, after it was put together by the distribution’s
    package manager. This is the best way to drop additional static files
    into the image, or override distribution-supplied ones.

  3. mkosi.build — This executable file is supposed to be a build
    script. When it exists, mkosi will build two images, one after the
    other in the mode already mentioned above: the first version is the
    build image, and may include various build-time dependencies such as
    a compiler or development headers. The build script is also copied
    into it, and then run inside it. The script should then build
    whatever shall be built and place the result in $DESTDIR (don’t
    worry, popular build tools such as Automake or Meson all honor
    $DESTDIR anyway, so there’s not much to do here explicitly). It may
    also run a test suite, or anything else you like. After the script
    finished, the build image is removed again, and a second image (the
    final image) is built. This time, no development packages are
    included, and the build script is not copied into the image again —
    however, the build artifacts from the first run (i.e. those placed in
    $DESTDIR) are copied into the image.

  4. mkosi.postinst — If this executable script exists, it is invoked
    inside the image (inside a systemd-nspawn invocation) and can
    adjust the image as it likes at a very late point in the image
    preparation. If mkosi.build exists, i.e. the dual-phased
    development build process used, then this script will be invoked
    twice: once inside the build image and once inside the final
    image. The first parameter passed to the script clarifies which phase
    it is run in.

  5. mkosi.nspawn — If this file exists, it should contain a
    container configuration file for systemd-nspawn (see
    systemd.nspawn(5)
    for details), which shall be shipped along with the final image and
    shall be included in the check-sum calculations (see below).

  6. mkosi.cache/ — If this directory exists, it is used as package
    cache directory for the builds. This directory is effectively bind
    mounted into the image at build time, in order to speed up building
    images. The package installers of the various distributions will
    place their package files here, so that subsequent runs can reuse
    them.

  7. mkosi.passphrase — If this file exists, it should contain a
    pass-phrase to use for the LUKS encryption (if that’s enabled for the
    image built). This file should not be readable to other users.

  8. mkosi.secure-boot.crt and mkosi.secure-boot.key should be an
    X.509 key pair to use for signing the kernel and initrd for UEFI
    SecureBoot, if that’s enabled.

How to use it

So, let’s come back to our most trivial example, without any of the
mkosi.$SOMETHING files around:

# mkosi

As mentioned, this will create a build file image.raw in the current
directory. How do we use it? Of course, we could dd it onto some USB
stick and boot it on a bare-metal device. However, it’s much simpler
to first run it in a container for testing:

# systemd-nspawn -bi image.raw

And there you go: the image should boot up, and just work for you.

Now, let’s make things more interesting. Let’s still not use any of
the mkosi.$SOMETHING files around:

# mkosi -t raw_btrfs --bootable -o foobar.raw
# systemd-nspawn -bi foobar.raw

This is similar as the above, but we made three changes: it’s no
longer GPT + ext4, but GPT + btrfs. Moreover, the system is made
bootable on UEFI systems, and finally, the output is now called
foobar.raw.

Because this system is bootable on UEFI systems, we can run it in KVM:

qemu-kvm -m 512 -smp 2 -bios /usr/share/edk2/ovmf/OVMF_CODE.fd -drive format=raw,file=foobar.raw

This will look very similar to the systemd-nspawn invocation, except
that this uses full VM virtualization rather than container
virtualization. (Note that the way to run a UEFI qemu/kvm instance
appears to change all the time and is different on the various
distributions. It’s quite annoying, and I can’t really tell you what
the right qemu command line is to make this work on your system.)

Of course, it’s not all raw GPT disk images with mkosi. Let’s try
a plain directory image:

# mkosi -d fedora -t directory -o quux
# systemd-nspawn -bD quux

Of course, if you generate the image as plain directory you can’t boot
it on bare-metal just like that, nor run it in a VM.

A more complex command line is the following:

# mkosi -d fedora -t raw_squashfs --checksum --xz --package=openssh-clients --package=emacs

In this mode we explicitly pick Fedora as the distribution to use, ask
mkosi to generate a compressed GPT image with a root squashfs,
compress the result with xz, and generate a SHA256SUMS file with
the hashes of the generated artifacts. The package will contain the
SSH client as well as everybody’s favorite editor.

Now, let’s make use of the various mkosi.$SOMETHING files. Let’s
say we are working on some Automake-based project and want to make it
easy to generate a disk image off the development tree with the
version you are hacking on. Create a configuration file:

# cat > mkosi.default <<EOF
[Distribution]
Distribution=fedora
Release=24

[Output]
Format=raw_btrfs
Bootable=yes

[Packages]
# The packages to appear in both the build and the final image
Packages=openssh-clients httpd
# The packages to appear in the build image, but absent from the final image
BuildPackages=make gcc libcurl-devel
EOF

And let’s add a build script:

# cat > mkosi.build <<EOF
#!/bin/sh
cd $SRCDIR
./autogen.sh
./configure --prefix=/usr
make -j `nproc`
make install
EOF
# chmod +x mkosi.build

And with all that in place we can now build our project into a disk image, simply by typing:

# mkosi

Let’s try it out:

# systemd-nspawn -bi image.raw

Of course, if you do this you’ll notice that building an image like
this can be quite slow. And slow build times are actively hurtful to
your productivity as a developer. Hence let’s make things a bit
faster. First, let’s make use of a package cache shared between runs:

# mkdir mkosi.chache

Building images now should already be substantially faster (and
generate less network traffic) as the packages will now be downloaded
only once and reused. However, you’ll notice that unpacking all those
packages and the rest of the work is still quite slow. But mkosi can
help you with that. Simply use mkosi‘s incremental build feature. In
this mode mkosi will make a copy of the build and final images
immediately before dropping in your build sources or artifacts, so
that building an image becomes a lot quicker: instead of always
starting totally from scratch a build will now reuse everything it can
reuse from a previous run, and immediately begin with building your
sources rather than the build image to build your sources in. To
enable the incremental build feature use -i:

# mkosi -i

Note that if you use this option, the package list is not updated
anymore from your distribution’s servers, as the cached copy is made
after all packages are installed, and hence until you actually delete
the cached copy the distribution’s network servers aren’t contacted
again and no RPMs or DEBs are downloaded. This means the distribution
you use becomes “frozen in time” this way. (Which might be a bad
thing, but also a good thing, as it makes things kinda reproducible.)

Of course, if you run mkosi a couple of times you’ll notice that it
won’t overwrite the generated image when it already exists. You can
either delete the file yourself first (rm image.raw) or let mkosi
do it for you right before building a new image, with mkosi -f. You
can also tell mkosi to not only remove any such pre-existing images,
but also remove any cached copies of the incremental feature, by using
-f twice.

I wrote mkosi originally in order to test systemd, and quickly
generate a disk image of various distributions with the most current
systemd version from git, without all that affecting my host system. I
regularly use mkosi for that today, in incremental mode. The two
commands I use most in that context are:

# mkosi -if && systemd-nspawn -bi image.raw

And sometimes:

# mkosi -iff && systemd-nspawn -bi image.raw

The latter I use only if I want to regenerate everything based on the
very newest set of RPMs provided by Fedora, instead of a cached
snapshot of it.

BTW, the mkosi files for systemd are included in the systemd git
tree:
mkosi.default
and
mkosi.build. This
way, any developer who wants to quickly test something with current
systemd git, or wants to prepare a patch based on it and test it can
check out the systemd repository and simply run mkosi in it and a
few minutes later he has a bootable image he can test in
systemd-nspawn or KVM. casync has similar files:
mkosi.default,
mkosi.build.

Random Interesting Features

  1. As mentioned already, mkosi will generate dm-verity enabled
    disk images if you ask for it. For that use the --verity switch on
    the command line or Verity= setting in mkosi.default. Of course,
    dm-verity implies that the root volume is read-only. In this mode
    the top-level dm-verity hash will be placed along-side the output
    disk image in a file named the same way, but with the .roothash
    suffix. If the image is to be created bootable, the root hash is also
    included on the kernel command line in the roothash= parameter,
    which current systemd versions can use to both find and activate the
    root partition in a dm-verity protected way. BTW: it’s a good idea
    to combine this dm-verity mode with the raw_squashfs image mode,
    to generate a genuinely protected, compressed image suitable for
    running in your IoT device.

  2. As indicated above, mkosi can automatically create a check-sum
    file SHA256SUMS for you (--checksum) covering all the files it
    outputs (which could be the image file itself, a matching .nspawn
    file using the mkosi.nspawn file mentioned above, as well as the
    .roothash file for the dm-verity root hash.) It can then
    optionally sign this with gpg (--sign). Note that systemd‘s
    machinectl pull-tar and machinectl pull-raw command can download
    these files and the SHA256SUMS file automatically and verify things
    on download. With other words: what mkosi outputs is perfectly
    ready for downloads using these two systemd commands.

  3. As mentioned, mkosi is big on supporting UEFI SecureBoot. To
    make use of that, place your X.509 key pair in two files
    mkosi.secureboot.crt and mkosi.secureboot.key, and set
    SecureBoot= or --secure-boot. If so, mkosi will sign the
    kernel/initrd/kernel command line combination during the build. Of
    course, if you use this mode, you should also use
    Verity=/--verity=, otherwise the setup makes only partial
    sense. Note that mkosi will not help you with actually enrolling
    the keys you use in your UEFI BIOS.

  4. mkosi has minimal support for GIT checkouts: when it recognizes
    it is run in a git checkout and you use the mkosi.build script
    stuff, the source tree will be copied into the build image, but will
    all files excluded by .gitignore removed.

  5. There’s support for encryption in place. Use --encrypt= or
    Encrypt=. Note that the UEFI ESP is never encrypted though, and the
    root partition only if explicitly requested. The /home and /srv
    partitions are unconditionally encrypted if that’s enabled.

  6. Images may be built with all documentation removed.

  7. The password for the root user and additional kernel command line
    arguments may be configured for the image to generate.

Minimum Requirements

Current mkosi requires Python 3.5, and has a number of dependencies,
listed in the
README. Most
notably you need a somewhat recent systemd version to make use of its
full feature set: systemd 233. Older versions are already packaged for
various distributions, but much of what I describe above is only
available in the most recent release mkosi 3.

The UEFI SecureBoot support requires sbsign which currently isn’t
available in Fedora, but there’s a
COPR
.

Future

It is my intention to continue turning mkosi into a tool suitable
for:

  1. Testing and debugging projects
  2. Building images for secure devices
  3. Building portable service images
  4. Building images for secure VMs and containers

One of the biggest goals I have for the future is to teach mkosi and
systemd/sd-boot native support for A/B IoT style partition
setups. The idea is that the combination of systemd, casync and
mkosi provides generic building blocks for building secure,
auto-updating devices in a generic way from, even though all pieces
may be used individually, too.

FAQ

  1. Why are you reinventing the wheel again? This is exactly like
    $SOMEOTHERPROJECT!
    — Well, to my knowledge there’s no tool that
    integrates this nicely with your project’s development tree, and can
    do dm-verity and UEFI SecureBoot and all that stuff for you. So
    nope, I don’t think this exactly like $SOMEOTHERPROJECT, thank you
    very much.

  2. What about creating MBR/DOS partition images? — That’s really
    out of focus to me. This is an exercise in figuring out how generic
    OSes and devices in the future should be built and an attempt to
    commoditize OS image building. And no, the future doesn’t speak MBR,
    sorry. That said, I’d be quite interested in adding support for
    booting on Raspberry Pi, possibly using a hybrid approach, i.e. using
    a GPT disk label, but arranging things in a way that the Raspberry Pi
    boot protocol (which is built around DOS partition tables), can still
    work.

  3. Is this portable? — Well, depends what you mean by
    portable. No, this tool runs on Linux only, and as it uses
    systemd-nspawn during the build process it doesn’t run on
    non-systemd systems either. But then again, you should be able to
    create images for any architecture you like with it, but of course if
    you want the image bootable on bare-metal systems only systems doing
    UEFI are supported (but systemd-nspawn should still work fine on
    them).

  4. Where can I get this stuff? — Try
    GitHub. And some distributions
    carry packaged versions, but I think none of them the current v3
    yet.

  5. Is this a systemd project? — Yes, it’s hosted under the
    systemd GitHub umbrella. And yes,
    during run-time systemd-nspawn in a current version is required. But
    no, the code-bases are separate otherwise, already because systemd
    is a C project, and mkosi Python.

  6. Requiring systemd 233 is a pretty steep requirement, no?
    Yes, but the feature we need kind of matters (systemd-nspawn‘s
    --overlay= switch), and again, this isn’t supposed to be a tool for
    legacy systems.

  7. Can I run the resulting images in LXC or Docker? — Humm, I am
    not an LXC nor Docker guy. If you select directory or subvolume
    as image type, LXC should be able to boot the generated images just
    fine, but I didn’t try. Last time I looked, Docker doesn’t permit
    running proper init systems as PID 1 inside the container, as they
    define their own run-time without intention to emulate a proper
    system. Hence, no I don’t think it will work, at least not with an
    unpatched Docker version. That said, again, don’t ask me questions
    about Docker, it’s not precisely my area of expertise, and quite
    frankly I am not a fan. To my knowledge neither LXC nor Docker are
    able to run containers directly off GPT disk images, hence the
    various raw_xyz image types are definitely not compatible with
    either. That means if you want to generate a single raw disk image
    that can be booted unmodified both in a container and on bare-metal,
    then systemd-nspawn is the container manager to go for
    (specifically, its -i/--image= switch).

Should you care? Is this a tool for you?

Well, that’s up to you really.

If you hack on some complex project and need a quick way to compile
and run your project on a specific current Linux distribution, then
mkosi is an excellent way to do that. Simply drop the mkosi.default
and mkosi.build files in your git tree and everything will be
easy. (And of course, as indicated above: if the project you are
hacking on happens to be called systemd or casync be aware that
those files are already part of the git tree — you can just use them.)

If you hack on some embedded or IoT device, then mkosi is a great
choice too, as it will make it reasonably easy to generate secure
images that are protected against offline modification, by using
dm-verity and UEFI SecureBoot.

If you are an administrator and need a nice way to build images for a
VM or systemd-nspawn container, or a portable service then mkosi
is an excellent choice too.

If you care about legacy computers, old distributions, non-systemd
init systems, old VM managers, Docker, … then no, mkosi is not for
you, but there are plenty of well-established alternatives around that
cover that nicely.

And never forget: mkosi is an Open Source project. We are happy to
accept your patches and other contributions.

Oh, and one unrelated last thing: don’t forget to submit your talk
proposal

and/or buy a ticket for
All Systems Go! 2017 in Berlin — the
conference where things like systemd, casync and mkosi are
discussed, along with a variety of other Linux userspace projects used
for building systems.

Scratch 2.0: all-new features for your Raspberry Pi

Post Syndicated from Rik Cross original https://www.raspberrypi.org/blog/scratch-2-raspberry-pi/

We’re very excited to announce that Scratch 2.0 is now available as an offline app for the Raspberry Pi! This new version of Scratch allows you to control the Pi’s GPIO (General Purpose Input and Output) pins, and offers a host of other exciting new features.

Offline accessibility

The most recent update to Raspbian includes the app, which makes Scratch 2.0 available offline on the Raspberry Pi. This is great news for clubs and classrooms, where children can now use Raspberry Pis instead of connected laptops or desktops to explore block-based programming and physical computing.

Controlling GPIO with Scratch 2.0

As with Scratch 1.4, Scratch 2.0 on the Raspberry Pi allows you to create code to control and respond to components connected to the Pi’s GPIO pins. This means that your Scratch projects can light LEDs, sound buzzers and use input from buttons and a range of sensors to control the behaviour of sprites. Interacting with GPIO pins in Scratch 2.0 is easier than ever before, as text-based broadcast instructions have been replaced with custom blocks for setting pin output and getting current pin state.

Scratch 2.0 GPIO blocks

To add GPIO functionality, first click ‘More Blocks’ and then ‘Add an Extension’. You should then select the ‘Pi GPIO’ extension option and click OK.

Scratch 2.0 GPIO extension

In the ‘More Blocks’ section you should now see the additional blocks for controlling and responding to your Pi GPIO pins. To give an example, the entire code for repeatedly flashing an LED connected to GPIO pin 2.0 is now:

Flashing an LED with Scratch 2.0

To react to a button connected to GPIO pin 2.0, simply set the pin as input, and use the ‘gpio (x) is high?’ block to check the button’s state. In the example below, the Scratch cat will say “Pressed” only when the button is being held down.

Responding to a button press on Scractch 2.0

Cloning sprites

Scratch 2.0 also offers some additional features and improvements over Scratch 1.4. One of the main new features of Scratch 2.0 is the ability to create clones of sprites. Clones are instances of a particular sprite that inherit all of the scripts of the main sprite.

The scripts below show how cloned sprites are used — in this case to allow the Scratch cat to throw a clone of an apple sprite whenever the space key is pressed. Each apple sprite clone then follows its ‘when i start as clone’ script.

Cloning sprites with Scratch 2.0

The cloning functionality avoids the need to create multiple copies of a sprite, for example multiple enemies in a game or multiple snowflakes in an animation.

Custom blocks

Scratch 2.0 also allows the creation of custom blocks, allowing code to be encapsulated and used (possibly multiple times) in a project. The code below shows a simple custom block called ‘jump’, which is used to make a sprite jump whenever it is clicked.

Custom 'jump' block on Scratch 2.0

These custom blocks can also optionally include parameters, allowing further generalisation and reuse of code blocks. Here’s another example of a custom block that draws a shape. This time, however, the custom block includes parameters for specifying the number of sides of the shape, as well as the length of each side.

Custom shape-drawing block with Scratch 2.0

The custom block can now be used with different numbers provided, allowing lots of different shapes to be drawn.

Drawing shapes with Scratch 2.0

Peripheral interaction

Another feature of Scratch 2.0 is the addition of code blocks to allow easy interaction with a webcam or a microphone. This opens up a whole new world of possibilities, and for some examples of projects that make use of this new functionality see Clap-O-Meter which uses the microphone to control a noise level meter, and a Keepie Uppies game that uses video motion to control a football. You can use the Raspberry Pi or USB cameras to detect motion in your Scratch 2.0 projects.

Other new features include a vector image editor and a sound editor, as well as lots of new sprites, costumes and backdrops.

Update your Raspberry Pi for Scratch 2.0

Scratch 2.0 is available in the latest Raspbian release, under the ‘Programming’ menu. We’ve put together a guide for getting started with Scratch 2.0 on the Raspberry Pi online (note that GPIO functionality is only available via the desktop version). You can also try out Scratch 2.0 on the Pi by having a go at a project from the Code Club projects site.

As always, we love to see the projects you create using the Raspberry Pi. Once you’ve upgraded to Scratch 2.0, tell us about your projects via Twitter, Instagram and Facebook, or by leaving us a comment below.

The post Scratch 2.0: all-new features for your Raspberry Pi appeared first on Raspberry Pi.

Introducing the Raspberry Pi Integrator Programme

Post Syndicated from Roger Thornton original https://www.raspberrypi.org/blog/raspberry-pi-integrator-programme/

An ever-growing number of companies take advantage of Raspberry Pi technology and use our boards as part of their end products. Raspberry Pis are now essential components of everything from washing machines to underwater exploration vehicles. We love seeing these commercial applications, and are committed to helping bring Raspberry Pi-powered products to market. With this in mind, we are excited to announce our new Raspberry Pi Integrator Programme!

Raspberry Pi Integrator Programme

Product compliance testing

Whenever a company wants to sell a product on a market, it first has to prove that selling it is safe and legal. Compliance requirements vary between different products; rules that would apply to a complicated machine like a car will, naturally, not be the same as those that apply to a pair of trainers (although there is some overlap in the Venn diagram of rules).

Raspberry Pi Integrator Programme

Regions of the world within each of which products have to be separately tested

Different countries usually have slightly different sets of regulations, and testing has to be conducted at an accredited facility for the region the company intends to sell the product in. Companies have to put a vast amount of work into getting their product through compliance testing and certification to meet country-specific requirements. This is especially taxing for smaller enterprises.

Making testing easier

Raspberry Pi has assisted various companies that use Pi technology in their end products through this testing and certification process, and over time it has become clear that we can do even more to help. This realisation led us to work with our compliance testing and certification partner UL to create a system that simplifies and speeds up compliance processes. Thus we have started the Raspberry Pi Integrator Programme, designed to help anyone get their Raspberry Pi-based product tested and on the market quickly and efficiently.

The Raspberry Pi Integrator Programme

The programme provides access to the same test engineers who worked on our Raspberry Pis during their compliance testing. It connects the user to a dedicated team at UL who assess and test the user’s product, facilitated by their in-depth knowledge of Raspberry Pi. The team at UL work closely with the Raspberry Pi engineering team, so any unexpected issues that may arise during testing can be resolved quickly. Through the programme, UL will streamline the testing and certification process, which will in turn decrease the amount of time necessary to launch the product. Our Integrator Programme is openly available, it comes with no added cost beyond the usual testing fees at UL, and there are companies already taking advantage of it.

Get your product on the market more quickly

We have put the Integrator Programme in place in the hope of eliminating the burden of navigating complicated compliance issues and making it easier for companies to bring new, exciting products to consumers. With simplified testing, companies and individuals can get products to market in less time and with lower overhead costs.

The programme is now up and running, and ready to accept new clients. UL and Raspberry Pi hope that it will be an incredibly useful tool for creators of Raspberry Pi-powered commercial products. For more information, please email [email protected].

Powered by Raspberry Pi

As a producer of a Pi-based device, you can also apply to use our ‘Powered by Raspberry Pi’ logo on your product and its packaging. Doing so indicates to customers that a portion of their payment supports the educational work of the Raspberry Pi Foundation.

Powered by Pi Logo

You’ll find more information about the ‘Powered by Raspberry Pi’ logo and our simple approval process for using it here.

The post Introducing the Raspberry Pi Integrator Programme appeared first on Raspberry Pi.

A Raspbian desktop update with some new programming tools

Post Syndicated from Simon Long original https://www.raspberrypi.org/blog/a-raspbian-desktop-update-with-some-new-programming-tools/

Today we’ve released another update to the Raspbian desktop. In addition to the usual small tweaks and bug fixes, the big new changes are the inclusion of an offline version of Scratch 2.0, and of Thonny (a user-friendly IDE for Python which is excellent for beginners). We’ll look at all the changes in this post, but let’s start with the biggest…

Scratch 2.0 for Raspbian

Scratch is one of the most popular pieces of software on Raspberry Pi. This is largely due to the way it makes programming accessible – while it is simple to learn, it covers many of the concepts that are used in more advanced languages. Scratch really does provide a great introduction to programming for all ages.

Raspbian ships with the original version of Scratch, which is now at version 1.4. A few years ago, though, the Scratch team at the MIT Media Lab introduced the new and improved Scratch version 2.0, and ever since we’ve had numerous requests to offer it on the Pi.

There was, however, a problem with this. The original version of Scratch was written in a language called Squeak, which could run on the Pi in a Squeak interpreter. Scratch 2.0, however, was written in Flash, and was designed to run from a remote site in a web browser. While this made Scratch 2.0 a cross-platform application, which you could run without installing any Scratch software, it also meant that you had to be able to run Flash on your computer, and that you needed to be connected to the internet to program in Scratch.

We worked with Adobe to include the Pepper Flash plugin in Raspbian, which enables Flash sites to run in the Chromium browser. This addressed the first of these problems, so the Scratch 2.0 website has been available on Pi for a while. However, it still needed an internet connection to run, which wasn’t ideal in many circumstances. We’ve been working with the Scratch team to get an offline version of Scratch 2.0 running on Pi.

Screenshot of Scratch on Raspbian

The Scratch team had created a website to enable developers to create hardware and software extensions for Scratch 2.0; this provided a version of the Flash code for the Scratch editor which could be modified to run locally rather than over the internet. We combined this with a program called Electron, which effectively wraps up a local web page into a standalone application. We ended up with the Scratch 2.0 application that you can find in the Programming section of the main menu.

Physical computing with Scratch 2.0

We didn’t stop there though. We know that people want to use Scratch for physical computing, and it has always been a bit awkward to access GPIO pins from Scratch. In our Scratch 2.0 application, therefore, there is a custom extension which allows the user to control the Pi’s GPIO pins without difficulty. Simply click on ‘More Blocks’, choose ‘Add an Extension’, and select ‘Pi GPIO’. This loads two new blocks, one to read and one to write the state of a GPIO pin.

Screenshot of new Raspbian iteration of Scratch 2, featuring GPIO pin control blocks.

The Scratch team kindly allowed us to include all the sprites, backdrops, and sounds from the online version of Scratch 2.0. You can also use the Raspberry Pi Camera Module to create new sprites and backgrounds.

This first release works well, although it can be slow for some operations; this is largely unavoidable for Flash code running under Electron. Bear in mind that you will need to have the Pepper Flash plugin installed (which it is by default on standard Raspbian images). As Pepper Flash is only compatible with the processor in the Pi 2.0 and Pi 3, it is unfortunately not possible to run Scratch 2.0 on the Pi Zero or the original models of the Pi.

We hope that this makes Scratch 2.0 a more practical proposition for many users than it has been to date. Do let us know if you hit any problems, though!

Thonny: a more user-friendly IDE for Python

One of the paths from Scratch to ‘real’ programming is through Python. We know that the transition can be awkward, and this isn’t helped by the tools available for learning Python. It’s fair to say that IDLE, the Python IDE, isn’t the most popular piece of software ever written…

Earlier this year, we reviewed every Python IDE that we could find that would run on a Raspberry Pi, in an attempt to see if there was something better out there than IDLE. We wanted to find something that was easier for beginners to use but still useful for experienced Python programmers. We found one program, Thonny, which stood head and shoulders above all the rest. It’s a really user-friendly IDE, which still offers useful professional features like single-stepping of code and inspection of variables.

Screenshot of Thonny IDE in Raspbian

Thonny was created at the University of Tartu in Estonia; we’ve been working with Aivar Annamaa, the lead developer, on getting it into Raspbian. The original version of Thonny works well on the Pi, but because the GUI is written using Python’s default GUI toolkit, Tkinter, the appearance clashes with the rest of the Raspbian desktop, most of which is written using the GTK toolkit. We made some changes to bring things like fonts and graphics into line with the appearance of our other apps, and Aivar very kindly took that work and converted it into a theme package that could be applied to Thonny.

Due to the limitations of working within Tkinter, the result isn’t exactly like a native GTK application, but it’s pretty close. It’s probably good enough for anyone who isn’t a picky UI obsessive like me, anyway! Have a look at the Thonny webpage to see some more details of all the cool features it offers. We hope that having a more usable environment will help to ease the transition from graphical languages like Scratch into ‘proper’ languages like Python.

New icons

Other than these two new packages, this release is mostly bug fixes and small version bumps. One thing you might notice, though, is that we’ve made some tweaks to our custom icon set. We wondered if the icons might look better with slightly thinner outlines. We tried it, and they did: we hope you prefer them too.

Downloading the new image

You can either download a new image from the Downloads page, or you can use apt to update:

sudo apt-get update
sudo apt-get dist-upgrade

To install Scratch 2.0:

sudo apt-get install scratch2

To install Thonny:

sudo apt-get install python3-thonny

One more thing…

Before Christmas, we released an experimental version of the desktop running on Debian for x86-based computers. We were slightly taken aback by how popular it turned out to be! This made us realise that this was something we were going to need to support going forward. We’ve decided we’re going to try to make all new desktop releases for both Pi and x86 from now on.

The version of this we released last year was a live image that could run from a USB stick. Many people asked if we could make it permanently installable, so this version includes an installer. This uses the standard Debian install process, so it ought to work on most machines. I should stress, though, that we haven’t been able to test on every type of hardware, so there may be issues on some computers. Please be sure to back up your hard drive before installing it. Unlike the live image, this will erase and reformat your hard drive, and you will lose anything that is already on it!

You can still boot the image as a live image if you don’t want to install it, and it will create a persistence partition on the USB stick so you can save data. Just select ‘Run with persistence’ from the boot menu. To install, choose either ‘Install’ or ‘Graphical install’ from the same menu. The Debian installer will then walk you through the install process.

You can download the latest x86 image (which includes both Scratch 2.0 and Thonny) from here or here for a torrent file.

One final thing

This version of the desktop is based on Debian Jessie. Some of you will be aware that a new stable version of Debian (called Stretch) was released last week. Rest assured – we have been working on porting everything across to Stretch for some time now, and we will have a Stretch release ready some time over the summer.

The post A Raspbian desktop update with some new programming tools appeared first on Raspberry Pi.

CoderDojo Coolest Projects 2017

Post Syndicated from Ben Nuttall original https://www.raspberrypi.org/blog/coderdojo-coolest-projects-2017/

When I heard we were merging with CoderDojo, I was delighted. CoderDojo is a wonderful organisation with a spectacular community, and it’s going to be great to join forces with the team and work towards our common goal: making a difference to the lives of young people by making technology accessible to them.

You may remember that last year Philip and I went along to Coolest Projects, CoderDojo’s annual event at which their global community showcase their best makes. It was awesome! This year a whole bunch of us from the Raspberry Pi Foundation attended Coolest Projects with our new Irish colleagues, and as expected, the projects on show were as cool as can be.

Coolest Projects 2017 attendee

Crowd at Coolest Projects 2017

This year’s coolest projects!

Young maker Benjamin demoed his brilliant RGB LED table tennis ball display for us, and showed off his brilliant project tutorial website codemakerbuddy.com, which he built with Python and Flask. [Click on any of the images to enlarge them.]

Coolest Projects 2017 LED ping-pong ball display
Coolest Projects 2017 Benjamin and Oly

Next up, Aimee showed us a recipes app she’d made with the MIT App Inventor. It was a really impressive and well thought-out project.

Coolest Projects 2017 Aimee's cook book
Coolest Projects 2017 Aimee's setup

This very successful OpenCV face detection program with hardware installed in a teddy bear was great as well:

Coolest Projects 2017 face detection bear
Coolest Projects 2017 face detection interface
Coolest Projects 2017 face detection database

Helen’s and Oly’s favourite project involved…live bees!

Coolest Projects 2017 live bees

BEEEEEEEEEEES!

Its creator, 12-year-old Amy, said she wanted to do something to help the Earth. Her project uses various sensors to record data on the bee population in the hive. An adjacent monitor displays the data in a web interface:

Coolest Projects 2017 Aimee's bees

Coolest robots

I enjoyed seeing lots of GPIO Zero projects out in the wild, including this robotic lawnmower made by Kevin and Zach:

Raspberry Pi Lawnmower

Kevin and Zach’s Raspberry Pi lawnmower project with Python and GPIO Zero, showed at CoderDojo Coolest Projects 2017

Philip’s favourite make was a Pi-powered robot you can control with your mind! According to the maker, Laura, it worked really well with Philip because he has no hair.

Philip Colligan on Twitter

This is extraordinary. Laura from @CoderDojo Romania has programmed a mind controlled robot using @Raspberry_Pi @coolestprojects

And here are some pictures of even more cool robots we saw:

Coolest Projects 2017 coolest robot no.1
Coolest Projects 2017 coolest robot no.2
Coolest Projects 2017 coolest robot no.3

Games, toys, activities

Oly and I were massively impressed with the work of Mogamad, Daniel, and Basheerah, who programmed a (borrowed) Amazon Echo to make a voice-controlled text-adventure game using Java and the Alexa API. They’ve inspired me to try something similar using the AIY projects kit and adventurelib!

Coolest Projects 2017 Mogamad, Daniel, Basheerah, Oly
Coolest Projects 2017 Alexa text-based game

Christopher Hill did a brilliant job with his Home Alone LEGO house. He used sensors to trigger lights and sounds to make it look like someone’s at home, like in the film. I should have taken a video – seeing it in action was great!

Coolest Projects 2017 Lego home alone house
Coolest Projects 2017 Lego home alone innards
Coolest Projects 2017 Lego home alone innards closeup

Meanwhile, the Northern Ireland Raspberry Jam group ran a DOTS board activity, which turned their area into a conductive paint hazard zone.

Coolest Projects 2017 NI Jam DOTS activity 1
Coolest Projects 2017 NI Jam DOTS activity 2
Coolest Projects 2017 NI Jam DOTS activity 3
Coolest Projects 2017 NI Jam DOTS activity 4
Coolest Projects 2017 NI Jam DOTS activity 5
Coolest Projects 2017 NI Jam DOTS activity 6

Creativity and ingenuity

We really enjoyed seeing so many young people collaborating, experimenting, and taking full advantage of the opportunity to make real projects. And we loved how huge the range of technologies in use was: people employed all manner of hardware and software to bring their ideas to life.

Philip Colligan on Twitter

Wow! Look at that room full of awesome young people. @coolestprojects #coolestprojects @CoderDojo

Congratulations to the Coolest Projects 2017 prize winners, and to all participants. Here are some of the teams that won in the different categories:

Coolest Projects 2017 winning team 1
Coolest Projects 2017 winning team 2
Coolest Projects 2017 winning team 3

Take a look at the gallery of all winners over on Flickr.

The wow factor

Raspberry Pi co-founder and Foundation trustee Pete Lomas came along to the event as well. Here’s what he had to say:

It’s hard to describe the scale of the event, and photos just don’t do it justice. The first thing that hit me was the sheer excitement of the CoderDojo ninjas [the children attending Dojos]. Everyone was setting up for their time with the project judges, and their pure delight at being able to show off their creations was evident in both halls. Time and time again I saw the ninjas apply their creativity to help save the planet or make someone’s life better, and it’s truly exciting that we are going to help that continue and expand.

Even after 8 hours, enthusiasm wasn’t flagging – the awards ceremony was just brilliant, with ninjas high-fiving the winners on the way to the stage. This speaks volumes about the ethos and vision of the CoderDojo founders, where everyone is a winner just by being part of a community of worldwide friends. It was a brilliant introduction, and if this weekend was anything to go by, our merger certainly is a marriage made in Heaven.

Join this awesome community!

If all this inspires you as much as it did us, consider looking for a CoderDojo near you – and sign up as a volunteer! There’s plenty of time for young people to build up skills and start working on a project for next year’s event. Check out coolestprojects.com for more information.

The post CoderDojo Coolest Projects 2017 appeared first on Raspberry Pi.

Is your product “Powered by Raspberry Pi”?

Post Syndicated from Mike Buffham original https://www.raspberrypi.org/blog/powered-by-raspberry-pi/

One of the most exciting things for us about the growth of the Raspberry Pi community has been the number of companies that have grown up around the platform, and who have chosen to embed our products into their own. While many of these design-ins have been “silent”, a number of people have asked us for a standardised way to indicate that a product contains a Raspberry Pi or a Raspberry Pi Compute Module.

Powered by Raspberry Pi Logo

At the end of last year, we introduced a “Powered by Raspberry Pi” logo to meet this need. It is now included in our trademark rules and brand guidelines, which you can find on our website. Below we’re showing an early example of a “Powered by Raspberry Pi”-branded device, the KUNBUS Revolution Pi industrial PC. It has already made it onto the market, and we think it will inspire you to include our logo on the packaging of your own product.

KUNBUS RevPi
Powered by Raspberry Pi logo on RevPi

Using the “Powered by Raspberry Pi” brand

Adding the “Powered by Raspberry Pi” logo to your packaging design is a great way to remind your customers that a portion of the sale price of your product goes to the Raspberry Pi Foundation and supports our educational work.

As with all things Raspberry Pi, our rules for using this brand are fairly straightforward: the only thing you need to do is to fill out this simple application form. Once you have submitted it, we will review your details and get back to you as soon as possible.

When we approve your application, we will require that you use one of the official “Powered by Raspberry Pi” logos and that you ensure it is at least 30 mm wide. We are more than happy to help you if you have any design queries related to this – just contact us at [email protected]

The post Is your product “Powered by Raspberry Pi”? appeared first on Raspberry Pi.

Shelfchecker Smart Shelf: build a home library system

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/smart-shelf-home-library/

Are you tired of friends borrowing your books and never returning them? Maybe you’re sure you own 1984 but can’t seem to locate it? Do you find a strange satisfaction in using the supermarket self-checkout simply because of the barcode beep? With the ShelfChecker smart shelf from maker Annelynn described on Instructables, you can be your own librarian and never misplace your books again! Beep!

Shelfchecker smart shelf annelynn Raspberry Pi

Harry Potter and the Aesthetically Pleasing Smart Shelf

The ShelfChecker smart shelf

Annelynn built her smart shelf utilising a barcode scanner, LDR light sensors, a Raspberry Pi, plus a few other peripherals and some Python scripts. She has created a fully integrated library checkout system with accompanying NeoPixel location notification for your favourite books.

This build allows you to issue your book-borrowing friends their own IDs and catalogue their usage of your treasured library. On top of that, you’ll be able to use LED NeoPixels to highlight your favourite books, registering their removal and return via light sensor tracking.

Using light sensors for book cataloguing

Once Annelynn had built the shelf, she drilled holes to fit the eight LDRs that would guard her favourite books, and separated them with corner brackets to prevent confusion.

Shelfchecker smart shelf annelynn Raspberry Pi

Corner brackets keep the books in place without confusion between their respective light sensors

Due to the limitations of the MCP3008 Adafruit microchip, the smart shelf can only keep track of eight of your favourite books. But this limitation won’t stop you from cataloguing your entire home library; it simply means you get to pick your ultimate favourites that will occupy the prime real estate on your wall.

Obviously, the light sensors sense light. So when you remove or insert a book, light floods or is blocked from that book’s sensor. The sensor sends this information to the Raspberry Pi. In response, an Arduino controls the NeoPixel strip along the ‘favourites’ shelf to indicate the book’s status.

Shelfchecker smart shelf annelynn Raspberry Pi

The book you are looking for is temporarily unavailable

Code your own library

While keeping a close eye on your favourite books, the system also allows creation of a complete library catalogue system with the help of a MySQL database. Users of the library can log into the system with a barcode scanner, and take out or return books recorded in the database guided by an LCD screen attached to the Pi.

Shelfchecker smart shelf annelynn Raspberry Pi

Beep!

I won’t go into an extensive how-to on creating MySQL databases here on the blog, because my glamourous assistant Janina has pulled up these MySQL tutorials to help you get started. Annelynn’s Github scripts are also packed with useful comments to keep you on track.

Raspberry Pi and books

We love books and libraries. And considering the growing number of Code Clubs and makespaces into libraries across the world, and the host of book-based Pi builds we’ve come across, the love seems to be mutual.

We’ve seen the Raspberry Pi introduced into the Wordery bookseller warehouse, a Pi-powered page-by-page book scanner by Jonathon Duerig, and these brilliant text-to-speech and page turner projects that use our Pis!

Did I say we love books? In fact we love them so much that members of our team have even written a few.*

If you’ve set up any sort of digital making event in a library, have in some way incorporated Raspberry Pi into your own personal book collection, or even managed to recreate the events of your favourite story using digital making, make sure to let us know in the comments below.

* Shameless plug**

Fancy adding some Pi to your home library? Check out these publications from the Raspberry Pi staff:

A Beginner’s Guide to Coding by Marc Scott

Adventures in Raspberry Pi by Carrie Anne Philbin

Getting Started with Raspberry Pi by Matt Richardson

Raspberry Pi User Guide by Eben Upton

The MagPi Magazine, Essentials Guides and Project Books

Make Your Own Game and Build Your Own Website by CoderDojo

** Shameless Pug

 

The post Shelfchecker Smart Shelf: build a home library system appeared first on Raspberry Pi.

Mira, tiny robot of joyful delight

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/mira-robot-alonso-martinez/

The staff of Pi Towers are currently melting into puddles while making ‘Aaaawwwwwww’ noises as Mira, the adorable little Pi-controlled robot made by Pixar 3D artist Alonso Martinez, steals their hearts.

Mira the robot playing peek-a-boo

If you want to get updates on Mira’s progress, sign up for the mailing list! http://eepurl.com/bteigD Mira is a desk companion that makes your life better one smile at a time. This project explores human robot interactivity and emotional intelligence. Currently Mira uses face tracking to interact with the users and loves playing the game “peek-a-boo”.

Introducing Mira

Honestly, I can’t type words – I am but a puddle! If I could type at all, I would only produce a stream of affectionate fragments. Imagine walking into a room full of kittens. What you would sound like is what I’d type.

No! I can do this. I’m a professional. I write for a living! I can…

SHE BLINKS OHMYAAAARGH!!!

Mira Alonso Martinez Raspberry Pi

Weebl & Bob meets South Park’s Ike Broflovski in an adorable 3D-printed bundle of ‘Aaawwwww’

Introducing Mira (I promise I can do this)

Right. I’ve had a nap and a drink. I’ve composed myself. I am up for this challenge. As long as I don’t look directly at her, I’ll be fine!

Here I go.

As one of the many über-talented 3D artists at Pixar, Alonso Martinez knows a thing or two about bringing adorable-looking characters to life on screen. However, his work left him wondering:

In movies you see really amazing things happening but you actually can’t interact with them – what would it be like if you could interact with characters?

So with the help of his friends Aaron Nathan and Vijay Sundaram, Alonso set out to bring the concept of animation to the physical world by building a “character” that reacts to her environment. His experiments with robotics started with Gertie, a ball-like robot reminiscent of his time spent animating bouncing balls when he was learning his trade. From there, he moved on to Mira.

Mira Alonso Martinez

Many, many of the views of this Tested YouTube video have come from me. So many.

Mira swivels to follow a person’s face, plays games such as peekaboo, shows surprise when you finger-shoot her, and giggles when you give her a kiss.

Mira’s inner workings

To get Mira to turn her head in three dimensions, Alonso took inspiration from the Microsoft Sidewinder Pro joystick he had as a kid. He purchased one on eBay, took it apart to understand how it works, and replicated its mechanism for Mira’s Raspberry Pi-powered innards.

Mira Alonso Martinez

Alonso used the smallest components he could find so that they would fit inside Mira’s tiny body.

Mira’s axis of 3D-printed parts moves via tiny Power HD DSM44 servos, while a camera and OpenCV handle face-tracking, and a single NeoPixel provides a range of colours to indicate her emotions. As for the blinking eyes? Two OLED screens boasting acrylic domes fit within the few millimeters between all the other moving parts.

More on Mira, including her history and how she works, can be found in this wonderful video released by Tested this week.

Pixar Artist’s 3D-Printed Animated Robots!

We’re gushing with grins and delight at the sight of these adorable animated robots created by artist Alonso Martinez. Sean chats with Alonso to learn how he designed and engineered his family of robots, using processes like 3D printing, mold-making, and silicone casting. They’re amazing!

You can also sign up for Alonso’s newsletter here to stay up-to-date about this little robot. Hopefully one of these newsletters will explain how to buy or build your own Mira, as I for one am desperate to see her adorable little face on my desk every day for the rest of my life.

The post Mira, tiny robot of joyful delight appeared first on Raspberry Pi.

BackMap, the haptic navigation system

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/backmap-haptic/

At this year’s TechCrunch Disrupt NY hackathon, one team presented BackMap, a haptic feedback system which helps visually impaired people to navigate cities and venues. It is assisted by a Raspberry Pi and integrated into a backpack.

Good vibrations with BackMap

The team, including Shashank Sharma, wrote an iOS phone app in Swift, Apple’s open-source programming language. To convert between addresses and geolocations, they used the Esri APIs offered by PubNub. So far, so standard. However, they then configured their BackMap setup so that the user can input their destination via the app, and then follow the route without having to look at a screen or listen to directions. Instead, vibrating motors have been integrated into the straps of a backpack and hooked up to a Raspberry Pi. Whenever the user needs to turn left or right, the Pi makes the respective motor vibrate.

Disrupt NY 2017 Hackathon | Part 1

Disrupt NY 2017 Hackathon presentations filmed live on May 15th, 2017. Preceding the Disrupt Conference is Hackathon weekend on May 13-14, where developers and engineers descend from all over the world to take part in a 24-hour hacking endurance test.

BackMap can also be adapted for indoor navigation by receiving signals from beacons. This could be used to direct users to toilet facilities or exhibition booths at conferences. The team hopes to upgrade the BackMap device to use a wristband format in the future.

Accessible Pi

Here at Pi Towers, we are always glad to see Pi builds for people with disabilities: we’ve seen Sanskriti and Aman’s Braille teacher Mudra, the audio e-reader Valdema by Finnish non-profit Kolibre, and Myrijam and Paul’s award-winning, eye-movement-controlled wheelchair, to name but a few.

Our mission is to bring the power of coding and digital making to everyone, and we are lucky to be part of a diverse community of makers and educators who have often worked proactively to make events and resources accessible to as many people as possible. There is, for example, the autism- and Tourette’s syndrome-friendly South London Raspberry Jam, organised by Femi Owolade-Coombes and his mum Grace. The Raspberry VI website is a portal to all things Pi for visually impaired and blind people. Deaf digital makers may find Jim Roberts’ video tutorials, which are signed in ASL, useful. And anyone can contribute subtitles in any language to our YouTube channel.

If you create or use accessible tutorials, or run a Jam, Code Club, or CoderDojo that is designed to be friendly to people who are neuroatypical or have a disability, let us know how to find your resource or event in the comments!

The post BackMap, the haptic navigation system appeared first on Raspberry Pi.

Making Waves: print out sound waves with the Raspberry Pi

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/printed-sound-wave/

For fun, Eunice Lee, Matthew Zhang, and Bomani McClendon have worked together to create Waves, an audiovisual project that records people’s spoken responses to personal questions and prints them in the form of a sound wave as a gift for being truthful.

Waves

Waves is a Raspberry Pi project centered around transforming the transience of the spoken word into something concrete and physical. In our setup, a user presses a button corresponding to an intimate question (ex: what’s your motto?) and answers it into a microphone while pressing down on the button.

What are you grateful for?

“I’m grateful for finishing this project,” admits maker Eunice Lee as she presses a button and speaks into the microphone that is part of the Waves project build. After a brief moment, her confession appears on receipt paper as a waveform, and she grins toward the camera, happy with the final piece.

Eunice testing Waves

Waves is a Raspberry Pi project centered around transforming the transience of the spoken word into something concrete and physical. In our setup, a user presses a button corresponding to an intimate question (ex: what’s your motto?) and answers it into a microphone while pressing down on the button.

Sound wave machine

Alongside a Raspberry Pi 3, the Waves device is comprised of four tactile buttons, a standard USB microphone, and a thermal receipt printer. This type of printer has become easily available for the maker movement from suppliers such as Adafruit and Pimoroni.

Eunice Lee, Matthew Zhang, Bomani McClendon - Sound Wave Raspberry Pi

Definitely more fun than a polygraph test

The trio designed four colour-coded cards that represent four questions, each of which has a matching button on the breadboard. Press the button that belongs to the question to be answered, and Python code directs the Pi to record audio via the microphone. Releasing the button stops the audio recording. “Once the recording has been saved, the script viz.py is launched,” explains Lee. “This script takes the audio file and, using Python matplotlib magic, turns it into a nice little waveform image.”

From there, the Raspberry Pi instructs the thermal printer to produce a printout of the sound wave image along with the question.

Making for fun

Eunice, Bomani, and Matt, students of design and computer science at Northwestern University in Illinois, built Waves as a side project. They wanted to make something at the intersection of art and technology and were motivated by the pure joy of creating.

Eunice Lee, Matthew Zhang, Bomani McClendon - Sound Wave Raspberry Pi

Making makes people happy

They have noted improvements that can be made to increase the scope of their sound wave project. We hope to see many more interesting builds from these three, and in the meantime we invite you all to look up their code on Eunice’s GitHub to create your own Waves at home.

The post Making Waves: print out sound waves with the Raspberry Pi appeared first on Raspberry Pi.

Estefannie’s GPS-Controlled GoPro Photo Taker

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/estefannie-gopro-selfie/

Are you tired of having to take selfies physically? Do you only use your GoPro for the occasional beach vacation? Are you maybe even wondering what to do with the load of velcro you bought on a whim? Then we have good news for you: Estefannie‘s back to help you out with her Personal Automated GPS-Controlled Portable Photo Taker…PAGCPPT for short…or pagsssspt, if you like.

RASPBERRY PI + GPS CONTROLLED PHOTO TAKER

Hey World! Do you like vacation pictures but don’t like taking them? Make your own Personal Automated GPS Controlled Portable Photo Taker! The code, components, and instructions are in my Hackster.io account: https://www.hackster.io/estefanniegg/automated-gps-controlled-photo-taker-3fc84c For this build, I decided to put together a backpack to take pictures of me when I am close to places that like.

The Personal Automated GPS-Controlled Portable Photo Taker

Try saying that five times in a row.

Go on. I’ll wait.

Using a Raspberry Pi 3, a GPS module, a power pack, and a GoPro plus GoPro Stick, Estefannie created the PAGCPPT as a means of automatically taking selfies at pre-specified tourist attractions across London.

Estefannie Explains it All Raspberry Pi GPS GoPro Camera

There’s pie in my backpack too…but it’s a bit messy

With velcro and hot glue, she secured the tech in place on (and inside) a backpack. Then it was simply a case of programming her set up to take pictures while she walked around the city.

Estefannie Explains it All Raspberry Pi GPS GoPro Camera

Making the GoPro…go

Estefannie made use of a GoPro API library to connect her GoPro to the Raspberry Pi via WiFi. With the help of this library, she wrote a Python script that made the GoPro take a photograph whenever her GPS module placed her within a ten-metre radius of a pre-selected landmark such as Tower Bridge, Abbey Road, or Platform 9 3/4.

Estefannie Explains it All Raspberry Pi GPS GoPro Camera

“Accio selfie.”

The full script, as well as details regarding the components she used for the project, can be found on her hackster.io page here.

Estefannie Explains it All

You’ll have noticed that we’ve covered Estefannie once or twice before on the Raspberry Pi blog. We love project videos that convey a sense of ‘Oh hey, I can totally build one of those!’, and hers always tick that box. They are imaginative, interesting, quirky, and to be totally honest with you, I’ve been waiting for this particular video since she hinted at it on her visit to Pi Towers in May. I got the inside scoop, yo!

What’s better than taking pictures? Not taking pictures. But STILL having pictures. I made a personal automated GPS controlled Portable Photo Taker ⚡ NEW VIDEO ALERT⚡ Link in bio.

1,351 Likes, 70 Comments – Estefannie Explains It All (@estefanniegg) on Instagram: “What’s better than taking pictures? Not taking pictures. But STILL having pictures. I made a…”

Make sure to follow her on YouTube and Instagram for more maker content and random shenanigans. And if you have your own maker social media channel, YouTube account, blog, etc, this is your chance to share it for the world to see in the comments below!

The post Estefannie’s GPS-Controlled GoPro Photo Taker appeared first on Raspberry Pi.

A rather dandy Pi-assisted Draisine

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/dandy-draisine/

It’s time to swap pedal power for relaxed strides with the Raspberry Pi-assisted Draisine from bicyle-modding pro Prof. Holger Hermanns.

Raspberry PI-powered Dandy Horse Draisine

So dandy…

A Draisine…

If you have children yourself or have seen them in the wild on occasion, you may be aware of how much they like balance bikes – bicycle frames without pedals, propelled by striding while sitting on the seat. It’s a nice way for children to take the first steps (bah-dum tss) towards learning to ride a bicycle. However, between 1817, when the balance bike (also known as a draisine or Dandy Horse) was invented by Karl von Drais, and the introduction of the pedal bike around 1860, this vehicle was the new, fun, and exciting way to travel for everyone.

Raspberry PI-powered Dandy Horse Draisine

We can’t wait for the inevitable IKEA flatpack release

Having previously worked on wireless braking systems for bicycles, Prof. Hermanns is experienced in adding tech to two wheels. Now, he and his team of computer scientists at Germany’s Saarland University have updated the balance bike for the 21st century: they built the Draisine 200.0 to explore pedal-free, power-assisted movement as part of the European Research Council-funded POWVER project.

With this draisine, his team have created a beautiful, fully functional final build that would look rather fetching here on the bicycle-flooded streets of Cambridge.

The frame of the bike, except for the wheel bearings and the various screws, is made of Okoumé wood, which looks somewhat rose, has fine nerves (which means that it is easy to mill) and seems to have excellent weather resistance.

Draisine 200.0

Uploaded by ecomento.tv on 2017-06-08.

…with added Pi!

Within the wooden body of the draisine lies a array of electrical components, including a 200-watt rear hub motor, a battery, an accelerometer, a magnetic sensor, and a Raspberry Pi. Checking the accelerometer and reading wheel-embedded sensors 150 times per second (wow!), the Pi activates the hub motor to assist the draisine, which allows it to reach speeds of up to 16mph (25km/h – wow again!).

Raspberry PI-powered Dandy Horse Draisine

The inner workings of the Draisine 200.0

More detailed information on the Draisine 200.0 build can be found here. Hermanns’s team also plan to release the code for the project once confirmation of no licence infringement has been given.

Take to the road

We’ve seen a variety of bicycle-oriented Pi builds that improve safety and help with navigation. But as for electricity-assisted Pi bikes, this one may be the first, and it’s such a snazzy one at that!

If you’d like to see more cycle-based projects using the Raspberry Pi, check out Matt’s Smart Bike Light, David’s bike computer, and, for the fun of it, the Pi-powered bicycle beer dispenser we covered last month.

The Pi Towers hive mind is constantly discussing fun new ways for its active cycling community to use the Raspberry Pi, and we’d love to hear your ideas as well! So please do share them in the comments below.

The post A rather dandy Pi-assisted Draisine appeared first on Raspberry Pi.

Nintendo & BREIN Target Seller of ‘Pirate’ Retro Gaming System

Post Syndicated from Andy original https://torrentfreak.com/nintendo-brein-target-seller-of-pirate-retro-gaming-system-170610/

As millions of often younger gamers immerse themselves in the latest 3D romp-fests from the world’s leading games developers, huge numbers of people are reliving their youth through the wonders of emulation.

The majority of old gaming systems can be emulated on a decent PC these days, opening up the possibility of reanimating thousands of the greatest games to ever grace the planet. While that’s a great prospect, the good news doesn’t stop there. The games are all free – if you don’t mind pirating them.

While many people go the do-it-yourself route by downloading emulators and ROMs (the games) from the Internet, increasingly people are saving time by buying systems ready-made online. Some of these are hugely impressive, housed in full-size arcade machine cabinets and packing many thousands of games. They also have sizeable price tags to match, running in some cases to thousands of dollars. But there are other options.

The rise of affordable compact computers has opened up emulation and retro gaming to a whole new audience and inevitable some people have taken to selling these devices online with the games pre-bundled on SD cards. These systems can be obtained relatively cheaply but despite the games being old, companies like Nintendo still take a dim view of their sale.

That’s also the case in the Netherlands, where Nintendo and other companies are taking action against people involved in the sale of what are effectively pirate gaming systems. In a recent case, Dutch anti-piracy outfit BREIN took action against the operator of the Retrospeler (Retro Player) site, an outlet selling a ready-made retro gaming system.

Retro Player site (translated from Dutch)

As seen from the image above, for a little under 110 euros the player can buy a games machine with classics like Super Mario, Street Fighter, and Final Fantasy pre-installed. Add a TV via an HDMI lead and a joypad or two, and yesteryear gaming becomes reality today. Unfortunately, the fun didn’t last long and it was soon “Game Over” for Retro Player.

Speaking with TorrentFreak, BREIN chief Tim Kuik says that the system sold by Retro Player was based on the popular Raspberry Pi single-board computer. Although small and relatively cheap, the Pi is easily capable of running retro games via software such as RetroPie, but it’s unclear which product was installed on the version sold by Retro Player.

What is clear is that the device came pre-installed with a lot of games. The now-defunct Retro Player site listed 6,500 titles for a wide range of classic gaming systems, including Gameboy, Super Nintendo, Nintendo 64, Megadrive and Playstation. Kuik didn’t provide precise numbers but said that the machine came packaged with “a couple of thousand” titles.

BREIN says in this particular case it was acting on behalf of Nintendo, among others. However, it doesn’t appear that the case will be going to court. Like many other cases handled by the anti-piracy group, BREIN says it has reached a settlement with the operator of the Retro Player site for an unspecified amount.

The debate and controversy surrounding retro gaming and emulation is one that has been running for years. The thriving community sees little wrong with reanimating games for long-dead systems and giving them new life among a new audience. On the other hand, copyright holders such as Nintendo view their titles as their property, to be exploited in a time, place and manner of their choosing.

While that friction will continue for a long time to come, there will be few if any legal problems for those choosing to pursue their emulation fantasies in the privacy of their own home. Retro gaming is here to stay and as long as computing power continues to increase, the experience is only likely to improve.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Encased in amber: meet the epoxy-embedded Pi

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/epoxy-pi-resin-io/

The maker of one of our favourite projects from this year’s Maker Faire Bay Area took the idea of an ’embedded device’ and ran with it: Ronald McCollam has created a wireless, completely epoxy-encased Pi build – screen included!

Resin.io in resin epoxy-encased Raspberry Pi

*cue epic music theme* “Welcome…to resin in resin.”

Just encase…

Of course, this build is not meant to be a museum piece: Ronald embedded a Raspberry Pi 3 with built-in wireless LAN and Bluetooth to create a hands-on demonstration of the resin.io platform, for which he is a Solution Architect. Resin.io is useful for remotely controlling groups of Linux-based IoT devices. In this case, Ronald used it to connect to the encased Pi. And yes, he named his make Resin-in-resin – we salute you, sir!

resin.io in resin epoxy-encased Raspberry Pi

“Life uh…finds a way.”

Before he started the practical part of his project, he did his research to find a suitable resin. He found that epoxy types specifically designed for encasing electronics are very expensive. In the end, Ronald tried out a cheap type, usually employed to coat furniture, by encasing an LED. It worked perfectly, and he went ahead to use this resin for embedding the Pi.

Bubbleshooting epoxy

This was the first time Ronald had worked with resin, so he learned some essential things about casting. He advises other makers to mix the epoxy very, very slowly to minimize the formation of bubbles; to try their hands on some small-scale casting attempts first; and to make sure they’re using a large enough mold for casting. Another thing to keep in mind is that some components of the make will heat up and expand while the device is running.

His first version of an encased Pi was still connected to the outside world by its USB cable:

Ronald McCollam on Twitter

Updates don’t get more “hands off” than a Raspberry Pi encased in epoxy — @resin_io inside resin! Come ask me about it at @DockerCon!

Not satisfied with this, he went on to incorporate an inductive charging coil as a power source, so that the Pi could be totally insulated in epoxy. The Raspberry Pi Foundation’s Matt Richardson got a look the finished project at Maker Faire Bay Area:

MattRichardson🏳️‍🌈 on Twitter

If you’re at @makerfaire, you must check out what @resin_io is showing. A @Raspberry_Pi completely enclosed in resin. Completely wireless. https://t.co/djVjoLz3hI

MAGNETS!

The charging coil delivers enough power to keep the Pi running for several hours, but it doesn’t allow secure booting. After some head-scratching, Ronald came up with a cool solution to this problem: he added a battery and a magnetic reed switch. He explains:

[The] boot process is to use the magnetic switch to turn off the Pi, put it on the charger for a few minutes to allow the battery to charge up, then remove the magnet so the Pi boots.

Pi in resin controlled by resin.io

“God help us, we’re in the hands of engineers.”

He talks about his build on the resin.io blog, and has provided a detailed project log on Hackaday. For those of you who want to recreate this project at home, Ronald has even put together an Adafruit wishlist of the necessary components.

Does this resin-ate with you?

What’s especially great about Ronald’s posts is that they’re full of helpful tips about getting started with using epoxy resin in your digital making projects. So whether you’re keen to build your own wireless Pi, or just generally interested in embedding electronic components in resin, you’ll find his write-ups useful.

If you have experience in working with epoxy and electronic devices and want to share what you’ve learned, please do so in the comments!

The post Encased in amber: meet the epoxy-embedded Pi appeared first on Raspberry Pi.

Tweetponic lavender: nourishing nature with the Twitter API

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/tweetponic-lavender/

In a Manhattan gallery, there is an art installation that uses a Raspberry Pi to control the lights, nourishing an underground field of lavender. The twist: the Pi syncs the intensity of the lights to the activity of a dozen or so Twitter accounts belonging to media personalities and members of the US government.

In May 2017 I cultivated a piece of land in Midtown Manhattan nurtured by tweets.

204 Likes, 5 Comments – Martin Roth (@martinroth02) on Instagram: “In May 2017 I cultivated a piece of land in Midtown Manhattan nurtured by tweets.”

Turning tweets into cellulose

Artist Martin Roth has used the Raspberry Pi to access the accounts via the Twitter API, and to track their behaviour. This information is then relayed to the lights in real time. The more tweets, retweets, and likes there are on these accounts at a given moment, the brighter the lights become, and the better the lavender plants grow. Thus Twitter storms are converted into plant food, and ultimately into a pleasant lavender scent.

Until June 21st @ ACF (11 East 52nd Street)

39 Likes, 1 Comments – Martin Roth (@martinroth02) on Instagram: “Until June 21st @ ACF (11 East 52nd Street)”

Regarding his motivation to create the art installation, Martin Roth says:

[The] Twitter storm is something to be resisted. But I am using it in my exhibition as a force to create growth.

The piece, descriptively titled In May 2017 I cultivated a piece of land in Midtown Manhattan nurtured by tweets, is on show at the Austrian Cultural Forum, New York.

Using the Twitter API as part of digital making

We’ve seen a number of cool makes using the Twitter API. These often involve the posting of tweets in response to real-world inputs. Some of our favourites are the tweeting cat flap Flappy McFlapface, the tweeting dog Oliver Twitch, and of course Pi Towers resident Bert the plant. It’s interesting to see the concept turned on its head.

If you feel inspired by these projects, head on over to our resource introducing the Twitter API using Python. Or do you already have a project, in progress or finished, that uses the API? Let us know about it in the comments!

The post Tweetponic lavender: nourishing nature with the Twitter API appeared first on Raspberry Pi.

AWS Greengrass – Run AWS Lambda Functions on Connected Devices

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-greengrass-run-aws-lambda-functions-on-connected-devices/

I first told you about AWS Greengrass in the post that I published during re:Invent (AWS Greengrass – Ubiquitous Real-World Computing). We launched a limited preview of Greengrass at that time and invited you to sign up if you were interested.

As I noted at the time, many AWS customers want to collect and process data out in the field, where connectivity is often slow and sometimes either intermittent or unreliable. Greengrass allows them to extend the AWS programming model to small, simple, field-based devices. It builds on AWS IoT and AWS Lambda, and supports access to the ever-increasing variety of services that are available in the AWS Cloud.

Greengrass gives you access to compute, messaging, data caching, and syncing services that run in the field, and that do not depend on constant, high-bandwidth connectivity to an AWS Region. You can write Lambda functions in Python 2.7 and deploy them to your Greengrass devices from the cloud while using device shadows to maintain state. Your devices and peripherals can talk to each other using local messaging that does not pass through the cloud.

Now Generally Available
Today we are making Greengrass generally available in the US East (Northern Virginia) and US West (Oregon) Regions. During the preview, AWS customers were able to get hands-on experience with Greengrass and to start building applications and businesses around it. I’ll share a few of these early successes later in this post.

The Greengrass Core code runs on each device. It allows you to deploy and run Lambda applications on the device, supports local MQTT messaging across a secure network, and also ensures that conversations between devices and the cloud are made across secure connections. The Greengrass Core also supports secure, over-the-air software updates, including Lambda functions. It includes a message broker, a Lambda runtime, a Thing Shadows implementation, and a deployment agent. Greengrass Core and (optionally) other devices make up a Greengrass Group. The group includes configuration data, the list of devices and the identity of the Greengrass Core, a list of Lambda functions, and a set of subscriptions that define where the messages should go. All of this information is copied to the Greengrass core devices during the deployment process.

Your Lambda functions can use APIs in three distinct SDKs:

AWS SDK for Python – This SDK allows your code to interact with Amazon Simple Storage Service (S3), Amazon DynamoDB, Amazon Simple Queue Service (SQS), and other AWS services.

AWS IoT Device SDK – This SDK (available for Node.js, Python, Java, and C++) helps you to connect your hardware devices to AWS IoT. The C++ SDK has a few extra features including access to the Greengrass Discovery Service and support for root CA downloads.

AWS Greengrass Core SDK – This SDK provides APIs that allow local invocation of other Lambda functions, publish messages, and work with thing shadows.

You can run the Greengrass Core on x86 and ARM devices that have version 4.4.11 (or newer) of the Linux kernel, with the OverlayFS and user namespace features enabled. While most deployments of Greengrass will be targeted at specialized, industrial-grade hardware, you can also run the Greengrass Core on a Raspberry Pi or an EC2 instance for development and test purposes.

For this post, I used a Raspberry Pi attached to a BrickPi, connected to my home network via WiFi:

The Raspberry Pi, the BrickPi, the case, and all of the other parts are available in the BrickPi 3 Starter Kit. You will need some Linux command-line expertise and a decent amount of manual dexterity to put all of this together, but if I did it then you surely can.

Greengrass in Action
I can access Greengrass from the Console, API, or CLI. I’ll use the Console. The intro page of the Greengrass Console lets me define groups, add Greengrass Cores, and add devices to my groups:

I click on Get Started and then on Use easy creation:

Then I name my group:

And name my first Greengrass Core:

I’m ready to go, so I click on Create Group and Core:

This runs for a few seconds and then offers up my security resources (two keys and a certificate) for downloading, along with the Greengrass Core:

I download the security resources and put them in a safe place, and select and download the desired version of the Greengrass Core software (ARMv7l for my Raspberry Pi), and click on Finish.

Now I power up my Pi, and copy the security resources and the software to it (I put them in an S3 bucket and pulled them down with wget). Here’s my shell history at that point:

Following the directions in the user guide, I create a new user and group, run the rpi-update script, and install several packages including sqlite3 and openssl. After a couple of reboots, I am ready to proceed!

Next, still following the directions, I untar the Greengrass Core software and move the security resources to their final destination (/greengrass/configuration/certs), giving them generic names along the way. Here’s what the directory looks like:

The next step is to associate the core with an AWS IoT thing. I return to the Console, click through the group and the Greengrass Core, and find the Thing ARN:

I insert the names of the certificates and the Thing ARN into the config.json file, and also fill in the missing sections of the iotHost and ggHost:

I start the Greengrass demon (this was my second attempt; I had a typo in one of my path names the first time around):

After all of this pleasant time at the command line (taking me back to my Unix v7 and BSD 4.2 days), it is time to go visual once again! I visit my AWS IoT dashboard and see that my Greengrass Core is making connections to IoT:

I go to the Lambda Console and create a Lambda function using the Python 2.7 runtime (the IAM role does not matter here):

I publish the function in the usual way and, hop over to the Greengrass Console, click on my group, and choose to add a Lambda function:

Then I choose the version to deploy:

I also configure the function to be long-lived instead of on-demand:

My code will publish messages to AWS IoT, so I create a subscription by specifying the source and destination:

I set up a topic filter (hello/world) on the subscription as well:

I confirm my settings and save my subscription and I am just about ready to deploy my code. I revisit my group, click on Deployments, and choose Deploy from the Actions menu:

I choose Automatic detection to move forward:

Since this is my first deployment, I need to create a service-level role that gives Greengrass permission to access other AWS services. I simply click on Grant permission:

I can see the status of each deployment:

The code is now running on my Pi! It publishes messages to topic hello/world; I can see them by going to the IoT Console, clicking on Test, and subscribing to the topic:

And here are the messages:

With all of the setup work taken care of, I can do iterative development by uploading, publishing, and deploying new versions of my code. I plan to use the BrickPi to control some LEGO Technic motors and to publish data collected from some sensors. Stay tuned for that post!

Greengrass Pricing
You can run the Greengrass Core on three devices free for one year as part of the AWS Free Tier. At the next level (3 to 10,000 devices) two options are available:

  • Pay as You Go – $0.16 per month per device.
  • Annual Commitment – $1.49 per year per device, a 17.5% savings.

If you want to run the Greengrass Core on more than 10,000 devices or make a longer commitment, please get in touch with us; details on all pricing models are on the Greengrass Pricing page.

Jeff;

Storm Glass: simulate the weather at your desk

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/storm-glass/

Inspired by the tempescope, The Modern Inventor’s Storm Glass is a weather-simulating lamp that can recreate the weather of any location in the world, all thanks to the help of a Raspberry Pi Zero W.

The Modern Inventors Storm Glass

Image c/o The Modern Inventor

The lamp uses the Weather Underground API, which allows the Raspberry Pi to access current and predicted weather conditions across the globe. Some may argue “Why do I need a recreation of the weather if I can look out my window?”, but I think the idea of observing tomorrow’s weather today, or keeping an eye on conditions in another location, say your favourite holiday destination, is pretty sweet.

Building a Storm Glass

The Modern Inventor, whose name I haven’t found out yet so I’ll call him TMI, designed and 3D printed the base and cap for the lamp. The glass bottle that sits between the two is one of those fancy mineral water bottles you’ve seen in the supermarket but never could justify buying before.

The base holds the Pi, as well as a speaker, a microphone, and various other components such as a Speaker Bonnet and NeoPixel Ring from Adafruit.

The Modern Inventors Storm Glass

Image c/o The Modern Inventor

“The rain maker is a tiny 5V centrifuge pump I got online, which pumps water along some glass tubing and into the lid where the rain falls from”, TMI explains on his Instructables project page. “The cloud generator is a USB-powered ultrasonic diffuser/humidifier. I just pulled out the guts and got rid of the rest. Make sure to keep the electronics which create the ultrasonic signal that drives the diffuser.”

The Modern Inventor's Storm Glass

Image c/o The Modern Inventor

With the tech in place, TMI (yes, I do appreciate the irony of using TMI as a designator for someone about whom I lack information) used hot glue like his life depended on it, bringing the whole build together into one slick-looking lamp.

Coding the storm

TMI set up the Storm Glass to pull data about weather conditions in a designated location via the Weather Underground API and recreate these within the lamp. He also installed Alexa Voice Service in it, giving the lamp a secondary function as a home automation device.

The Modern Inventor's Storm Glass

Image c/o The Modern Inventor

Code for the Storm Glass, alongside a far more detailed explanation of the build process, can be found on TMI’s project page. He says the total cost of this make comes to less than $80.

Create your own weather device

If you’d like to start using weather APIs to track conditions at home or abroad, we have a whole host of free Raspberry Pi resources for you to try your hand on: begin by learning how to fetch weather data using the RESTful API or using Scratch and the OpenWeatherMap to create visual representations of weather across the globe. You could even create a ‘Dress for the weather’ indicator so you’re never caught without a coat, an umbrella, or sunscreen again!

However you use the weather in your digital making projects, we’d love to see what you’ve been up to in the comments below.

The post Storm Glass: simulate the weather at your desk appeared first on Raspberry Pi.

Raspberry Pi Looper-Synth-Drum…thing

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/raspberry-pi-looper/

To replace his iPad for live performance, Colorado-based musician Toby Hendricks built a looper, complete with an impressive internal sound library, all running on a Raspberry Pi.

Raspberry Pi Looper/synth/drum thing

Check out the guts here: https://youtu.be/mCOHFyI3Eoo My first venture into raspberry pi stuff. Running a custom pure data patch I’ve been working on for a couple years on a Raspberry Pi 3. This project took a couple months and I’m still tweaking stuff here and there but it’s pretty much complete, it even survived it’s first live show!

Toby’s build is a pretty mean piece of kit, as this video attests. Not only does it have a multitude of uses, but the final build is beautiful. Do make sure to watch to the end of the video for a wonderful demonstration of the kit.

Inside the Raspberry Pi looper

Alongside the Raspberry Pi and Behringer U-Control sound card, Toby used Pure Data, a multimedia visual programming language, and a Teensy 3.6 processor to complete the build. Together, these allow for playback of a plethora of sounds, which can either be internally stored, or externally introduced via audio connectors along the back.

This guy is finally taking shape. DIY looper/fx box/sample player/synth. #teensy #arduino #raspberrypi #puredata

98 Likes, 6 Comments – otem rellik (@otem_rellik) on Instagram: “This guy is finally taking shape. DIY looper/fx box/sample player/synth. #teensy #arduino…”

Delay, reverb, distortion, and more are controlled by sliders along one side, while pre-installed effects are selected and played via some rather beautiful SparkFun buttons on the other. Loop buttons, volume controls, and a repurposed Nintendo DS screen complete the interface.

Raspberry Pi Looper Guts

Thought I’d do a quick overview of the guts of my pi project. Seems like many folks have been interested in seeing what the internals look like.

Code for the looper can be found on Toby’s GitHub here. Make sure to continue to follow him via YouTube and Instagram for updates on the build, including these fancy new buttons.

Casting my own urethane knobs and drum pads from 3D printed molds! #3dprinted #urethanecasting #diy

61 Likes, 4 Comments – otem rellik (@otem_rellik) on Instagram: “Casting my own urethane knobs and drum pads from 3D printed molds! #3dprinted #urethanecasting #diy”

I got the music in me

If you want to get musical with a Raspberry Pi, but the thought of recreating Toby’s build is a little daunting, never fear! Our free GPIO Music Box resource will help get you started. And projects such as Mike Horne’s fabulous Raspberry Pi music box should help inspire you to take your build further.

Raspberry Pi Looper post image of Mike Horne's music box

Mike’s music box boasts wonderful flashy buttons and turny knobs for ultimate musical satisfaction!

If you use a Raspberry Pi in any sort of musical adventure, be sure to share your project in the comments below!

 

 

The post Raspberry Pi Looper-Synth-Drum…thing appeared first on Raspberry Pi.