Raspberry Pi2 with Ubuntu Sever and Drupal?

I decided to celebrate 25th B-day of Linux by putting the latest Ubuntu 16.04 on my Raspberry Pi 2 and setting up a webserver.
This is how I did it:

  1. First, get Ubuntu armf image and prepare memory card
  2. # get image
    wget http://cdimage.ubuntu.com/ubuntu/releases/16.04/release/ubuntu-16.04-preinstalled-server-armhf+raspi2.img.xz
    # make sure your SD card is on sdb ie by df -h
    xzcat ubuntu-16.04-preinstalled-server-armhf+raspi2.img.xz | sudo dd of=/dev/sdb
  3. Configure new user & setup Drupal8 webserver
  4. # create new user & change hostname
    sudo adduser USERNAME && sudo usermod -a -G sudo USERNAME
    # edit /etc/hostname and add ` newHostname` to /etc/hosts
    sudo reboot
    # generate locales
    sudo locale-gen en_US.UTF-8
    sudo dpkg-reconfigure locales
    # install software
    sudo apt install htop apache2 mysql-server libapache2-mod-php php-mysql php-sqlite3 php-curl php-xml php-gd git sqlite3 emacs-nox

My first impressions?
sudo apt is veeery slow. At first, I thought it’s due to old SD card I’ve been using, but it’s also true for newer SD card.
Some packages are missing (ie. git-lfs), but you can get them using some workarounds.

But everything just works!
You can check the mirror of https://ngschool.eu/ running on RPi2 here.
Maybe it’s not speed devil, but it stable and uses almost no energy 🙂


Inspired by Ubuntu’s Insights.

Reducing the size of large git repository

The github repository of #NGSchool website has grown to over 5GB. I wanted to reduce the size & simplify this repository, but this task turned out to quite complicated. Instead, I have decided to leave current repo as is (and probably removed it soon) and start new repo for existing version. I could do that, as I don’t care about version earlier than the one I’m currently using. This is short how-to:

  1. Push all changes and remove .git folder
  2. git push origin master
    rm -rI .git
  3. Rename existing repo
  4. Settings > Repository name > RENAME

  5. Start new repository using old repo name
  6. Don’t need to create any files as all already exists.

  7. Init your local repo and add new remote
  8. git init
    git remote add origin git@github.com:USER/REPO
  9. Commit changes and push
  10. git add --all . && git commit -m "fresh" && git push origin master

Doing so, my new repo size is below 1GB, which is much better compared to 5GB previously.

Convert xls table into abstract book PDF

I had to generate Abstract book for #NGSchool2016 (). I had spreadsheet generated by Google Forms with all necessary information. I could copy-paste all entries and format it later on, but I found LaTeX more robust for the task.
As I had already LaTeX template, the only missing part was conversion of .xls to .tex. Thus I have written simple script, xls2tex.py, that generate .tex file based on table from .xls file.
This script, among many other things, convert utf into LaTeX escape characters.

xls2tex.py depends on xlrd and utf8tolatex (from pylatexenc/latexencode, but this is given as single file)

# install dependencies
sudo apt-get install python-xlrd
# generate tex

# generate pdf

Output pdf.

Github push fails due to large files

Lately, I have had lots of problems with pushing large files to github. I am maintaining compilation of materials and software deposited by other people, so cannot control the size of files… and this makes push to fail often.

git push
remote: error: GH001: Large files detected. You may want to try Git Large File Storage - https://git-lfs.github.com.
remote: error: Trace: 6f0f7f66995a394598595375954732db
remote: error: See http://git.io/iEPt8g for more information.
remote: error: File chip_seq/reads/sox2_chip.fastq.gz is 109.69 MB; this exceeds GitHub's file size limit of 100.00 MB

To remove large files from commit, execute

git filter-branch -f --index-filter 'git rm --cached --ignore-unmatch chip_seq/reads/sox2_chip.fastq.gz'
git push

To add large files using git-lfs, execute

# tract by git lfs files larger than 50MB, skipping those in .git folder
find . -type f -size +50M ! -iwholename "*.git*" | rev | cut -f1 -d'/' | rev | xargs git lfs track
git add --all . && git commit -m "final" && git push origin

Make sure that your file are smaller than 2GB, otherwise your push will fail again 😉

Then, to before pull in another machine, make sure to install git-lfs

git lfs install
git pull

Malformed column reporting and joining in BASH by paste or awk

I’ve spent some hours trying to figure out, why the heck my scripts using awk and paste are returning malformed output. Simply, lines were wrongly pasted together, some columns were missing, while some were malformed… and in case of awk, trying to print columns in unsorted order (ie. column #3 before column #2 awk '{print $3,$2}') was producing malformed output.
After some time, I have realised it was due to windows-like new line escape \r\n, instead of standard Linux-like \n (of course I got this file from third party using Windows…).

Below, you can find more details.

# first, let's create dummy files containing 4 lines and 5 columns, each line ending with \r\n
python -c "with open('wrong.tsv','w') as out: out.write(''.join('line%s\t%s\r\n'%(i, '\t'.join('column%s'%j for j in range(1,5))) for i in range(1,4)))"
# and ending just with \n
python -c "with open('correct.tsv','w') as out: out.write(''.join('line%s\t%s\n'%(i, '\t'.join('column%s'%j for j in range(1,5))) for i in range(1,4)))"

# now let's paste wrong and correct files
paste wrong.tsv wrong.tsv
line1	line1n1	column1	column2	column3	column4
line2	line2n1	column1	column2	column3	column4
line3	line3n1	column1	column2	column3	column4

paste correct.tsv correct.tsv
line1	column1	column2	column3	column4	line1	column1	column2	column3	column4
line2	column1	column2	column3	column4	line2	column1	column2	column3	column4
line3	column1	column2	column3	column4	line3	column1	column2	column3	column4

# can you see the difference?

Simply, \r is interpreted as return to the beginning of the line in Unix, thus pasting lines containing such character will fail.
In order to convert files containing \r\n into Unix style \n, simply execute:

# replaces file and creates backup: inputfile.bak
sed -i.bak 's/\r$//' inputfile

# creates outputfile with correct formatting
tr -d '\r' < inputfile > outputfile

You can read more on new-line escape characters at Wikipedia.

Running Jupyter as public service

Some time ago, I’ve written about setting up IPython as a public service. Today, I’ll write about setting up Jupyter, IPython descendant, that beside Python supports tons of other languages and frameworks.

Jupyter notebook will be running in separate user, so your personal files are safe, but not as system service. Therefore, you will need to restart it upon system reboot. I recommend running it in SCREEN session, so you can easily login into the server and check the Jupyter state.

  1. Install & setup Jupyter
  2. #
    sudo apt-get install build-essential python-dev
    sudo pip install jupyter
    # create new user
    sudo adduser jupyter
    # login as new user
    su jupyter
    # make sure to add `unset XDG_RUNTIME_DIR` to ~/.bashrc
    # otherwise you'll encounter: OSError: [Errno 13] Permission denied: '/run/user/1003/jupyter'
    echo 'unset XDG_RUNTIME_DIR' >> ~/.bashrc
    source ~/.bashrc
    # generate ssl certificates
    mkdir ~/.ssl
    openssl req -x509 -nodes -days 999 -newkey rsa:1024 -keyout ~/.ssl/mykey.key -out ~/.ssl/mycert.pem
    # generate config
    jupyter notebook --generate-config
    # generate pass and checksum
    ipython -c "from IPython.lib import passwd; passwd()"
    # enter your password twice, save it and copy password hash
    ## Out[1]: 'sha1:[your hashed password here]'
    # add to ~/.jupyter/jupyter_notebook_config.py
    c.NotebookApp.ip = '*'
    c.NotebookApp.open_browser = False
    c.NotebookApp.port = 8881
    c.NotebookApp.password = u'sha1:[your hashed password here]'
    c.NotebookApp.certfile = u'/home/jupyter/.ssl/mycert.pem'
    c.NotebookApp.keyfile = u'/home/jupyter/.ssl/mykey.key'
    # create some directory for notebook files ie. ~/Public/jupyter
    mkdir -p ~/Public/jupyter && cd ~/Public/jupyter
    # start notebook server
    jupyter notebook
  3. Add kernels
  4. You can add multiple kernels to Jupyter. Here I’ll cover installation of some:

    • Python
    • sudo pip install ipykernel
      # if you wish to use matplotlib, make sure to add to 
      # ~/.ipython/profile_default/ipython_kernel_config.py
      c.InteractiveShellApp.matplotlib = 'inline'
    • BASH kernel
    • sudo pip install bash_kernel
      sudo python -m bash_kernel.install
    • Perl
    • This didn’t worked for me:/

      sudo cpan Devel::IPerl
    • IRkernel
    • Follow this tutorial.

    • Haskell
    • sudo apt-get install cabal-install
      git clone http://www.github.com/gibiansky/IHaskell
      cd IHaskell

Then, just navigate to https://YOURDOMAIN.COM:8881/, accept self-signed certificate and enjoy!
Alternatively, you can obtain certificate from Let’s encrypt.

Using existing domain encryption aka Apache proxy
If your domain is already HTTPS, you may consider setting up Jupyter on localhost and redirect all incoming traffic (already encrypted) to particular port on localhost (as suggested by @shebang).

# enable Apache mods
sudo a2enmod proxy proxy_http proxy_wstunnel && sudo service apache2 restart

# add to your Apache config
    <Location "/jupyter" >
        ProxyPass http://localhost:8881/jupyter
        ProxyPassReverse http://localhost:8881/jupyter
    <Location "/jupyter/api/kernels/" >
        ProxyPass        ws://localhost:8881/jupyter/api/kernels/
        ProxyPassReverse ws://localhost:8881/jupyter/api/kernels/
    <Location "/jupyter/api/kernels/">
        ProxyPass        ws://localhost:8881/jupyter/api/kernels/
        ProxyPassReverse ws://localhost:8881/jupyter/api/kernels/

# update you Jupyter config (~/.jupyter/jupyter_notebook_config.py)
c.NotebookApp.ip = 'localhost'
c.NotebookApp.open_browser = False
c.NotebookApp.port = 8881
c.NotebookApp.base_url = '/jupyter'
c.NotebookApp.password = u'sha1:[your hashed password here]'
c.NotebookApp.allow_origin = '*'

Note, it’s crucial to add Apache proxy for kernels (/jupyter/api/kernels/), otherwise you won’t be able to use terminals due to failed: Error during WebSocket handshake: Unexpected response code: 400 error.

Working with large binary files in git

Git is great, there is no doubt about that. Being able to revert any changes and recover lost data is simply priceless. But recently, I have started to be concerned about the size of some of my repositories. Some, especially those containing changing binary files, were really large!!!
You can check the size of your repository by simple command:

git count-objects -vH

Here, git Large File Storage (LSF) comes into action. Below, I’ll describe how to install and mark large binary files, so they are not uploaded as a whole, but only relevant chunks of changed binary file is uploaded.

  1. Installation of git-lfs
  2. # add packagecloud repo
    curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
    # install git-lsf
    sudo apt-get install git-lfs 
    # end enable it
    git lfs install
  3. Marking and commiting binary file
  4. # mark large binary file
    git lfs track some.file
    # add, commit & push changes
    git add some.file
    git commit -m "some.file as LSF"
    git push origin master

On handy docker images

Motivated by successful stripping problematic dependencies from Redundans, I have decided to generate smaller Docker image, starting with Alpine Linux image (2Mb / 5Mb after downloading) instead of Ubuntu (49Mb / 122Mb). Previously, I couldn’t really rely on Alpine Linux, because it was impossible to make these problematic dependencies running… But now it’s whole new world of possibilities 😉

There are very few dependencies left, so I have started… (You can find all the commands below).

  1. First, I have check what can be installed from package manager.
    Only Python and Perl.

  2. Then I have checked if any of binaries are working.
    For example, GapCloser is provided as binary. It took me some time to find source code…
    Anyway, none of the binaries worked out of the box. It was expected, as Alpine Linux is super stripped…

  3. I have installed build-base in order to be able to build things.
    Additionally, BWA need zlib-dev.

  4. Alpine Linux doesn’t use standard glibc library, but musl-libc (you can read more about differences between the two), so some programmes (ie. BWA) may be quite reluctant to compile.
    After some hours of trying & thanks to the help of mp15, I have found a solution, not so complicated 🙂

  5. I have realised, that Dockerfile doesn’t like standard BASH brace expansion, that is working otherwise in Docker Alpine console…
    so ls *.{c,h} should be ls *.c *.h

  6. After that, LAST and GapCloser compilation were easy, relatively 😉

Below, you can find the code from Docker file (without RUN commands).

apk add --update --no-cache python perl bash wget build-base zlib-dev
mkdir -p /root/src && cd /root/src && wget http://downloads.sourceforge.net/project/bio-bwa/bwa-0.7.15.tar.bz2 && tar xpfj bwa-0.7.15.tar.bz2 && ln -s bwa-0.7.15 bwa && cd bwa && \
cp kthread.c kthread.c.org && echo "#include <stdint.h>" > kthread.c && cat kthread.c.org >> kthread.c && \
sed -ibak 's/u_int32_t/uint32_t/g' `grep -l u_int32_t *.c *.h` && make && cp bwa /bin/ && \
cd /root/src && wget http://liquidtelecom.dl.sourceforge.net/project/soapdenovo2/GapCloser/src/r6/GapCloser-src-v1.12-r6.tgz && tar xpfz GapCloser-src-v1.12-r6.tgz && ln -s v1.12-r6/ GapCloser && cd GapCloser && make && cp bin/GapCloser /bin/ && \
cd /root/src && wget http://last.cbrc.jp/last-744.zip && unzip last-744.zip && ln -s last-744 last && cd last && make && make install && \
cd /root/src && rm -r last* bwa* GapCloser* v* 

# SSPACE && redundans in /root/srt
cd /root/src && wget -q http://www.baseclear.com/base/download/41SSPACE-STANDARD-3.0_linux-x86_64.tar.gz && tar xpfz 41SSPACE-STANDARD-3.0_linux-x86_64.tar.gz && ln -s SSPACE-STANDARD-3.0_linux-x86_64 SSPACE && wget -O- -q http://cpansearch.perl.org/src/GBARR/perl5.005_03/lib/getopts.pl > SSPACE/dotlib/getopts.pl && \
wget --no-check-certificate -q -O redundans.tgz https://github.com/lpryszcz/redundans/archive/master.tar.gz && tar xpfz redundans.tgz && mv redundans-master redundans && ln -s /root/src/redundans /redundans && rm *gz

apk del wget build-base zlib-dev 
apk add libstdc++

After building & pushing, I have noticed that Alpine-based image is slightly smaller (99Mb), than the one based on Ubuntu (127Mb). Surprisingly, Alpine-based image is larger (273Mb) than Ubuntu-based (244Mb) after downloading. So, I’m afraid all of these hours didn’t really bring any substantial reduction in the image size.

I was very motivated to build my application on Alpine Linux and expected substantial size reduction. But I’d say that relying on Alpine Linux image doesn’t always pay off in terms of smaller image size, forget about production time… And this I know from my own experience.
But maybe I didn’t something wrong? I’d be really glad for some advices/comments!

Nevertheless, stripping a few dependencies from my application (namely Biopython, numpy & scipy), resulted in much more compact image even using Ubuntu-based image (127Mb vs 191Mb; and 244Mb vs 440Mb after downloading). So I think this is the way to go 🙂

On simplifying dependencies

Lately, to make Redundans more user friendly, I have simplified it’s dependencies, by replacing Biopython, numpy, scipy and SQLite with some (relatively) simple functions or modules.

Here, I will just focus on replacing Biopython, particularly SeqIO.index_db with FastaIndex. You may ask yourself, why I have invested time in reinventing the wheel. I’m big fan of Biopython, yet it’s huge project and some solutions are not optimal or require problematic dependencies. This is the case with SeqIO.db_index, that relies on SQLite3. Here again, I’m a big fan of SQLite, yet building Biopython with SQLite enabled proved not to be very straightforward for non-standard systems or less experience users. Beside, on some NFS settings, the SQLite3 db cannot be created at all.

Ok, let’s start from the basics. SeqIO.index_db allows random access to sequence files, so for example you can rapidly retrieve any entry from very large file. This is achieved by storing the ID and position of each entry from particular file in database, SQLite3 db. Then, if you want to retrieve particular record, SeqIO.index_db looks up if this record is present in SQLite3 db, retrieves record position in the file and reads only small chunk of this file instead of parsing entire file every time you want to get some record(s).
Similar feature is offered by samtools faidx, but in this case, the coordinates of each entry are stored in tab-delimited file .fai (more info about .fai). This format can be easily read & write by any programme, so I have decided to use it. In addition, I have realised, that samtools faidx is flexible enough, so you can add additional columns to the .fai without interrupting its functionality, but about that later…

In Redundans, I’ve been using SeqIO.index_db during assembly reduction (fasta2homozygous.py). Additionally, beside storing index, I’ve been also generating statistics for every FastA file, like number of contigs, cumulative size, N50, N90, GC and so on. I have realised, that these two can be easily combined, by extending .fai with four additional columns, storing number of occurencies for A, C, G & T in every sequence. Such .fai is compatible with samtools faidx and provides very easy way of calculating bunch of statistics about this file.
All of these, I’ve implemented in FastaIndex. Beside being dependency-free & very handy indexer, it can be used also as alternative to samtools faidx to retrieve sequences from large FastA files.

# retrieve bases from 20 to 60 from NODE_2
./FastaIndex.py -i test/run1/contigs.fa -r NODE_2_length_7674_cov_46.7841_ID_3:20-60
#Time elapsed: 0:00:00.014243

samtools faidx test/run1/contigs.fa NODE_2_length_7674_cov_46.7841_ID_3:20-60