* Talk

I just gave a talk about this at [[https://www.socallinuxexpo.org/scale/17x][SCaLE 17x]]. Here are the [[https://www.youtube.com/watch?v=Qvb_uNkFGNQ&t=12830s][video of the talk]] and
the [[https://github.com/dkogan/talk-feedgnuplot-vnlog/blob/master/feedgnuplot-vnlog.org]["slides"]].

* Summary

Vnlog ("vanilla-log") is a toolkit for manipulating tabular ASCII data with
labelled fields using normal UNIX tools. If you regularly use =awk= and =sort=
and =uniq= and others, these tools will make you infinitely more powerful. The
vnlog tools /extend/, rather than replace the standard tooling, so minimal
effort is required to learn and use these tools.

Everything assumes a trivially simple log format:

- A whitespace-separated table of ASCII human-readable text
- A =#= character starts a comment that runs to the end of the line (like in
  many scripting languages)
- The first line that begins with a single =#= (not =##= or =#!=) is a /legend/,
  naming each column. This is required, and the field names that appear here are
  referenced by all the tools.
- Empty fields reported as =-=

This describes 99% of the format, with some extra details [[#format-details][below]]. Example:

#+BEGIN_EXAMPLE
#!/usr/bin/whatever
# a b c
1 2 3
## comment
4 5 6
#+END_EXAMPLE

Such data can be processed directly with almost any existing tool, and /this/
toolkit allows the user to manipulate this data in a nicer way by relying on
standard UNIX tools. The core philosophy is to avoid creating new knowledge as
much as possible. Consequently, the vnlog toolkit relies /heavily/ on existing
(and familiar!) tools and workflows. As such, the toolkit is small, light, and
has a /very/ friendly learning curve.

* Synopsis

I have [[https://raw.githubusercontent.com/dkogan/vnlog/master/dji-tsla.tar.gz][two sets of historical stock data]], from the start of 2018 until now
(2018/11):

#+BEGIN_SRC sh :results output :exports both
< dji.vnl head -n 4
#+END_SRC

#+RESULTS:
: # Date Open High Low Close AdjClose Volume
: 2018-11-15 25061.48 25354.56 24787.79 25289.27 25289.27 383292840
: 2018-11-14 25388.08 25501.29 24935.82 25080.50 25080.50 384240000
: 2018-11-13 25321.21 25511.03 25193.78 25286.49 25286.49 339690000

And

#+BEGIN_SRC sh :results output :exports both
< tsla.vnl head -n 4
#+END_SRC

#+RESULTS:
: # Date Open High Low Close AdjClose Volume
: 2018-11-15 342.33 348.58 339.04 348.44 348.44 4486339
: 2018-11-14 342.70 347.11 337.15 344.00 344.00 5036300
: 2018-11-13 333.16 344.70 332.20 338.73 338.73 5448600

I can add whitespace to make the headers more legible by humans:

#+BEGIN_SRC sh :results output :exports both
< dji.vnl head -n 4 | vnl-align
#+END_SRC

#+RESULTS:
: #  Date      Open     High      Low     Close  AdjClose   Volume 
: 2018-11-15 25061.48 25354.56 24787.79 25289.27 25289.27 383292840
: 2018-11-14 25388.08 25501.29 24935.82 25080.50 25080.50 384240000
: 2018-11-13 25321.21 25511.03 25193.78 25286.49 25286.49 339690000

I can pull out the closing prices:

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-filter -p Close | head -n4
#+END_SRC

#+RESULTS:
: # Close
: 25289.27
: 25080.50
: 25286.49

=vnl-filter= is primarily a wrapper around =awk= or =perl=, allowing the user to
reference columns by name. I can then plot the closing prices:

#+BEGIN_SRC sh :results file link :exports both
< dji.vnl vnl-filter -p Close |
  feedgnuplot --lines --unset grid
#+END_SRC

#+RESULTS:
[[file:guide-1.svg]]

Here I kept /only/ the closing price column, so the x-axis is just the row
index. The data was in reverse chronological order, so this plot is also in
reverse chronological order. Let's fix that:

#+BEGIN_SRC sh :results file link :exports both
< dji.vnl vnl-sort -k Date |
  vnl-filter -p Close |
  feedgnuplot --lines --unset grid
#+END_SRC

#+RESULTS:
[[file:guide-2.svg]]

The =vnl-sort= tool (and most of the other =vnl-xxx= tools) are wrappers around
the core tools already available on the system (such as =sort=, in this case).
With the primary difference being reading/writing vnlog, and referring to
columns by name.

We now have the data in the correct order, but it'd be nice to see the actual
dates on the x-axis. While we're at it, let's label the axes too:

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-filter -p Date,Close | head -n4
#+END_SRC

#+RESULTS:
: # Date Close
: 2018-11-15 25289.27
: 2018-11-14 25080.50
: 2018-11-13 25286.49

#+BEGIN_SRC sh :results file link :exports both
< dji.vnl vnl-sort -k Date |
  vnl-filter -p Date,Close |
  feedgnuplot --lines --unset grid --timefmt %Y-%m-%d --domain \
              --xlabel 'Date' --ylabel 'Price ($)'
#+END_SRC

#+RESULTS:
[[file:guide-3.svg]]

What was the highest value of the Dow-Jones index, and when did it happen?

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-sort -rgk Close |
  head -n2 |
  vnl-align
#+END_SRC

#+RESULTS:
: #  Date      Open     High      Low     Close  AdjClose   Volume 
: 2018-10-03 26833.47 26951.81 26789.08 26828.39 26828.39 280130000

Alrighty. Looks like the high was in October. Let's zoom in on that month:

#+BEGIN_SRC sh :results file link :exports both
< dji.vnl vnl-sort -k Date |
  vnl-filter 'Date ~ /2018-10/' -p Date,Close |
  feedgnuplot --lines --unset grid --timefmt %Y-%m-%d --domain \
              --xlabel 'Date' --ylabel 'Price ($)'
#+END_SRC

#+RESULTS:
[[file:guide-4.svg]]

OK. Is this thing volatile? What was the largest single-day gain?

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-filter -p '.,d=diff(Close)' |
  head -n4 |
  vnl-align
#+END_SRC

#+RESULTS:
: #  Date      Open     High      Low     Close  AdjClose   Volume     d   
: 2018-11-15 25061.48 25354.56 24787.79 25289.27 25289.27 383292840 -      
: 2018-11-14 25388.08 25501.29 24935.82 25080.50 25080.50 384240000 -208.77
: 2018-11-13 25321.21 25511.03 25193.78 25286.49 25286.49 339690000  205.99

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-filter -p '.,d=diff(Close)' |
  vnl-sort -rgk d |
  head -n2 |
  vnl-align
#+END_SRC

#+RESULTS:
: #  Date      Open     High      Low     Close  AdjClose   Volume     d   
: 2018-02-02 26061.79 26061.79 25490.66 25520.96 25520.96 522880000 1175.21

Whoa. So the best single-gain day was 2018-02-02: the dow gained 1175.21 points
between closing on Feb 1 and Feb 2. But it actually lost ground that day! What
if I looked at the difference between the opening and closing in a single day?

#+BEGIN_SRC sh :results output :exports both
< dji.vnl vnl-filter -p '.,d=Close-Open' |
  vnl-sort -rgk d |
  head -n2 |
  vnl-align
#+END_SRC

#+RESULTS:
: #  Date      Open     High      Low     Close  AdjClose   Volume    d  
: 2018-02-06 24085.17 24946.23 23778.74 24912.77 24912.77 823940000 827.6

I guess by that metric 2018-02-06 was better. Let's join the Dow-jones index
data and the TSLA data, and let's look at them together:

#+BEGIN_SRC sh :results output :exports both
vnl-join --vnl-autosuffix dji.vnl tsla.vnl -j Date |
  head -n4 |
  vnl-align
#+END_SRC

#+RESULTS:
: #  Date    Open_dji High_dji  Low_dji Close_dji AdjClose_dji Volume_dji Open_tsla High_tsla Low_tsla Close_tsla AdjClose_tsla Volume_tsla
: 2018-11-15 25061.48 25354.56 24787.79 25289.27  25289.27     383292840  342.33    348.58    339.04   348.44     348.44        4486339    
: 2018-11-14 25388.08 25501.29 24935.82 25080.50  25080.50     384240000  342.70    347.11    337.15   344.00     344.00        5036300    
: 2018-11-13 25321.21 25511.03 25193.78 25286.49  25286.49     339690000  333.16    344.70    332.20   338.73     338.73        5448600    

#+BEGIN_SRC sh :results output :exports both
vnl-join --vnl-autosuffix dji.vnl tsla.vnl -j Date |
  vnl-filter -p '^Close' |
  head -n4 |
  vnl-align
#+END_SRC

#+RESULTS:
: # Close_dji Close_tsla
: 25289.27    348.44    
: 25080.50    344.00    
: 25286.49    338.73    

#+BEGIN_SRC sh :results file link :exports both
vnl-join --vnl-autosuffix dji.vnl tsla.vnl -j Date |
  vnl-filter -p '^Close' |
  feedgnuplot --domain --points --unset grid \
              --xlabel 'DJI price ($)' --ylabel 'TSLA price ($)'
#+END_SRC

#+RESULTS:
[[file:guide-5.svg]]

Huh. Apparently there's no obvious, strong correlation between TSLA and
Dow-Jones closing prices. And we saw that with just a few shell commands,
without dropping down into a dedicated analysis system.

* Build and installation
vnlog is a part of Debian/buster and Ubuntu/cosmic (18.10) and later. On those
boxes you can simply

#+BEGIN_EXAMPLE
$ sudo apt install vnlog libvnlog-dev libvnlog-perl python3-vnlog
#+END_EXAMPLE

to get the binary tools, the C API, the perl and python3 interfaces
respectively.

** Install on non-Debian boxes
Most of this is written in an interpreted language, so there's nothing to build
or install, and you can run the tools directly from the source tree:

#+BEGIN_EXAMPLE
$ git clone https://github.com/dkogan/vnlog.git
$ cd vnlog
$ ./vnl-filter .....
#+END_EXAMPLE

The python and perl libraries can be run from the tree by setting the
=PYTHONPATH= and =PERL5LIB= environment variables respectively. For the C
library, you should =make=, and then point your =CFLAGS= and =LDLIBS= and
=LD_LIBRARY_PATH= to the local tree.

If you do want to install to some arbitrary location to simplify the paths, do
this:

#+BEGIN_EXAMPLE
$ make
$ PREFIX=/usr/local make install
#+END_EXAMPLE

This will install /all/ the components into =/usr/local=.

* Description
Vnlog data is nicely readable by both humans and machines. Any time your
application invokes =printf()= for either diagnostics or logging, consider
writing out vnlog-formatted data. You retain human readability, but gain the
power all the =vnl-...= tools provide.

Vnlog tools are designed to be very simple and light. There's an ever-growing
list of other tools that do vaguely the same thing. Some of these:

- https://github.com/BurntSushi/xsv
- https://csvkit.readthedocs.io/
- https://github.com/johnkerl/miller
- https://github.com/jqnatividad/qsv
- https://github.com/greymd/teip
- https://github.com/eBay/tsv-utils-dlang
- https://www.gnu.org/software/datamash/
- https://stedolan.github.io/jq/
- https://github.com/benbernard/RecordStream
- https://github.com/dinedal/textql
- https://www.visidata.org/
- http://harelba.github.io/q/
- https://github.com/BatchLabs/charlatan
- https://github.com/dbohdan/sqawk

Many of these provide facilities to run various analyses, and others focus on
data types that aren't just a table (json for instance). Vnlog by contrast
doesn't analyze anything, and targets the most trivial possible data format.
This makes it very easy to run any analysis you like in any tool you like. The
main envisioned use case is one-liners, and the tools are geared for that
purpose. The above mentioned tools are much more powerful than vnlog, so they
could be a better fit for some use cases. I claim that

- 90% of the time you want to do simple things, and vnlog is a great fit for the
  task
- If you really do need to do something complex, you shouldn't be in the shell
  writing oneliners anymore, and a fully-fledged analysis system (numpy, etc) is
  more appropriate

In the spirit of doing as little as possible, the provided tools are wrappers
around tools you already have and are familiar with. The provided tools are:

- =vnl-filter= is a tool to select a subset of the rows/columns in a vnlog
  and/or to manipulate the contents. This is an =awk= wrapper where the fields
  can be referenced by name instead of index. 20-second tutorial:

#+BEGIN_SRC sh :results none :exports code
vnl-filter -p col1,col2,colx=col3+col4 'col5 > 10' --has col6
#+END_SRC

  will read the input, and produce a vnlog with 3 columns: =col1= and =col2=
  from the input, and a column =colx= that's the sum of =col3= and =col4= in the
  input. Only those rows for which /both/ =col5 > 10= is true /and/ that have a
  non-null value for =col6= will be output. A null entry is signified by a
  single =-= character.

#+BEGIN_SRC sh :results none :exports code
vnl-filter --eval '{s += x} END {print s}'
#+END_SRC

#+RESULTS:

  will evaluate the given awk program on the input, but the column names work as
  you would hope they do: if the input has a column named =x=, this would
  produce the sum of all values in this column.

- =vnl-sort=, =vnl-uniq=, =vnl-join=, =vnl-tail=, =vnl-ts= are wrappers around
  the corresponding commandline tools. These work exactly as you would expect
  also: the columns can be referenced by name, and the legend comment is handled
  properly. These are wrappers, so all the commandline options those tools have
  "just work" (except options that don't make sense in the context of vnlog). As
  an example, =vnl-tail -f= will follow a log: data will be read by =vnl-tail=
  as it is written into the log (just like =tail -f=, but handling the legend
  properly). And you already know how to use these tools without even reading
  the manpages! Note: I use the Linux kernel and the tools from GNU Coreutils
  exclusively, but this all has been successfully tested on FreeBSD and OSX
  also. Please let me know if something doesn't work.

- =vnl-align= aligns vnlog columns for easy interpretation by humans. The
  meaning is unaffected

- =Vnlog::Parser= is a simple perl library to read a vnlog

- =vnlog= is a simple python library to read a vnlog. Both python2 and python3
  are supported

- =libvnlog= is a C library to simplify reading and writing a vnlog. Clearly all
  you /really/ need for writing is =printf()=, but this is useful if we have
  lots of columns, many containing null values in any given row, and/or if we
  have parallel threads writing to a log. In my usage I have hundreds of columns
  of sparse data, so this is handy

- =vnl-make-matrix= converts a one-point-per-line vnlog to a matrix of data.
  I.e.

#+BEGIN_EXAMPLE
$ cat dat.vnl
# i j x
0 0 1
0 1 2
0 2 3
1 0 4
1 1 5
1 2 6
2 0 7
2 1 8
2 2 9
3 0 10
3 1 11
3 2 12

$ < dat.vnl vnl-filter -p i,x | vnl-make-matrix --outdir /tmp
Writing to '/tmp/x.matrix'

$ cat /tmp/x.matrix
1 2 3
4 5 6
7 8 9
10 11 12
#+END_EXAMPLE

All the tools have manpages that contain more detail. And more tools will
probably be added with time.

* Format details
The high-level description of the vnlog format from [[#Summary][above]] is sufficient to
read/write "normal" vnlog data, but there are a few corner cases that should be
mentioned. To reiterate, the format description from above describes vnlog as:

- A whitespace-separated table of ASCII human-readable text
- A =#= character starts a comment that runs to the end of the line (like in
  many scripting languages)
- The first line that begins with a single =#= (not =##= or =#!=) is a /legend/,
  naming each column. This is required, and the field names that appear here are
  referenced by all the tools.
- Empty fields reported as =-=

For a few years now I've been using these tools myself, and supporting others as
they were passing vnlog data around. In the process I've encountered some
slightly-weird data, and patched the tools to accept it. So today the included
vnlog tools are /very/ permissive, and accept any vnlog data that can possibly
be accepted. Other vnlog tools may not be quite as permissive, and may not be
able to interpret "weird" data. Points of note, describing the included vnlog
tools:

- Leading and trailing whitespace is ignored. Everywhere. So this data file will
  be read properly, with the =x= column containing 1 and 3:

  #+begin_example
 # x y
1 2
  3 4
  #+end_example

- Empty (or whitespace-only) lines anywhere are ignored, and treated as a
  comment
- An initial =#= comment without field names is treated as a comment, and we
  continue looking for the legend in the following lines. So this data file will
  be read properly:

  #+begin_example
## comment
#
# x y
1 2
3 4
  #+end_example

- Trailing comments are supported, like in most scripting languages. So this
  data file will be read properly:

  #+begin_example
# x y
1 2 # comment
3 4
  #+end_example

- Field names are /very/ permissive: anything that isn't whitespace is
  supported. So this data file will be read properly:

  #+begin_example
# x y  # 1+  -
1   2  3  4  5
11 12 13 14 15
  #+end_example

  We can pull out the =#= and =1+= and =-= columns:

  #+begin_src sh
vnl-filter -p '#,1+,-'
  #+end_src

  And we can even operate on them, if we use whitespace to indicate field
  boundaries:

  #+begin_src sh
vnl-filter -p 'x=1+ + 5'
  #+end_src

  Note that this implies that trailing comments in a legend line are /not/
  supported: the extra =#= characters will be used for field names. Field names
  containing =,= or === are currently not accepted by =vnl-filter=, but /are/
  accepted by the other tools (=vnl-sort= and such). I'll make =vnl-filter= able
  to work with those field names too, eventually, but as a user, the simplest
  thing to do is to not pass around data with such field names.

- Duplicated labels are supported whenever possible. So

  #+begin_example
# x y  z  z
1   2  3  4
11 12 13 14
   #+end_example

  will work just fine, unless we're operating on =z=. With this data, both of
  these commands work:

  #+begin_src sh
vnl-filter -p x
vnl-filter -p z
  #+end_src

  Picking =z= selects both of the =z= columns. But neither of these commands can
  work with the non-unique =z= column:

  #+begin_src sh
vnl-filter -p s=z+1
vnl-sort -k z
  #+end_src

* Workflows and recipes
** Storing disjoint data

A common use case is a complex application that produces several semi-related
subsets of data at once. Example: a moving vehicle is reporting both its own
position and the observed positions of other vehicles; at any given time any
number of other vehicles may be observed. Two equivalent workflows are possible:

- a single unified vnlog stream for /all/ the data
- several discrete vnlog streams for each data subset

Both are valid approaches

*** One unified vnlog stream
Here the application produces a /single/ vnlog that contains /all/ the columns,
from /all/ the data subsets. In any given row, many of the columns will be empty
(i.e. contain only =-= ). For instance, a row describing a vehicle own position
will not have data about any observations, and vice versa. It is inefficient to
store all the extra =-= but it makes many things much nicer, so it's often worth
it. =vnl-filter= can be used to pull out the different subsets. Sample
=joint.vnl=:

#+BEGIN_EXAMPLE
# time x_self x_observation
1      10     -
2      20     -
2      -      100
3      30     -
3      -      200
3      -      300
#+END_EXAMPLE

Here we have 3 instances in time. We have no observations at =time= 1, one
observation at =time= 2, and two observations at =time= 3. We can use
=vnl-filter= to pull out the data we want:

#+BEGIN_EXAMPLE
$ < joint.vnl vnl-filter -p time,self

# time x_self
1 10
2 20
2 -
3 30
3 -
3 -
#+END_EXAMPLE

If we only care about our own positions, the =+= modifier in picked columns in
=vnl-filter= is very useful here:

#+BEGIN_EXAMPLE
$ < joint.vnl vnl-filter -p time,+self

# time x_self
1 10
2 20
3 30


$ < joint.vnl vnl-filter -p time,+observation

# time x_observation
2 100
3 200
3 300
#+END_EXAMPLE

Note that the default is =--skipempty=, so if we're /only/ looking at =x_self=
for instance, then we don't even need to =+= modifier:

#+begin_example
$ < joint.vnl vnl-filter -p self

# x_self
10
20
30
#+end_example

Also, note that the =vnlog= C interface works very nicely to produce these
datafiles:

- You can define lots and lots of columns, but only fill some of them before
  calling =vnlog_emit_record()=. The rest will be set to =-=.
- You can create multiple contexts for each type of data, and you can populate
  them with data independently. And when calling =vnlog_emit_record_ctx()=,
  you'll get a record with data for just that context.

*** Several discrete vnlog streams

Conversely, the application can produce /separate/ vnlog streams for /each/
subset of data. Depending on what is desired, exactly, =vnl-join= can be used to
re-join them:

#+BEGIN_EXAMPLE
$ cat self.vnl

# time x_self
1 10
2 20
3 30


$ cat observations.vnl

# time x_observation
2 100
3 200
3 300


$ vnl-join -j time -a- self.vnl observations.vnl

# time x_self x_observation
1 10 -
2 20 100
3 30 200
3 30 300
#+END_EXAMPLE

** Data statistics

A common need is to compute basic statistics from your data. Many of the
alternative toolkits listed above provide built-in facilities to do this, but
vnlog does not: it's meant to be unixy, where each tool has very limited scope.
Thus you can either do this with =awk= like you would normally, or you can use
other standalone tools to perform the needed computations. For instance, I can
generate some data:

#+BEGIN_EXAMPLE
$ seq 2 100 | awk 'BEGIN {print "# x"} {print log($1)}' > /tmp/log.vnl
#+END_EXAMPLE

Then I can compute the mean with =awk=:

#+BEGIN_EXAMPLE
$ < /tmp/log.vnl vnl-filter --eval '{sum += x} END {print sum/NR}'
3.67414
#+END_EXAMPLE

Or I can compute the mean (and other stuff) with a separate standalone tool:

#+BEGIN_EXAMPLE
$ < /tmp/log.vnl ministat
x <stdin>
+----------------------------------------------------------------------------+
|                                                                         xx |
|                                                                  x xxxxxxx |
|                                                             xx xxxxxxxxxxxx|
|                                                x  x xxxxxxxxxxxxxxxxxxxxxxx|
|x       x    x    x  x  x  x x x xx xx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx|
|                                         |_______________A____M___________| |
+----------------------------------------------------------------------------+
    N           Min           Max        Median           Avg        Stddev
x  99      0.693147       4.60517       3.93183     3.6741353    0.85656382
#+END_EXAMPLE

=ministat= is not a part of the vnlog toolkit, but the vnlog format is generic
so it works just fine.

** Powershell-style filtering of common shell commands

Everything about vnlog is generic and simple, so it's easy to use it to process
data that wasn't originally meant to be used this way. For instance filtering
the output of =ls -l= to report only file names and sizes, skipping directories,
and sorting by file sizes:

#+BEGIN_EXAMPLE
$ ls -l

total 320
-rw-r--r-- 1 dima dima  5044 Aug 25 15:04 Changes
-rw-r--r-- 1 dima dima 12749 Aug 25 15:04 Makefile
-rw-r--r-- 1 dima dima 69789 Aug 25 15:04 README.org
-rw-r--r-- 1 dima dima 33781 Aug 25 15:04 README.template.org
-rw-r--r-- 1 dima dima  5359 Aug 25 15:04 b64_cencode.c
drwxr-xr-x 4 dima dima  4096 Aug 25 15:04 completions
drwxr-xr-x 3 dima dima  4096 Aug 25 15:04 lib
drwxr-xr-x 3 dima dima  4096 Aug 25 15:04 packaging
drwxr-xr-x 2 dima dima  4096 Aug 25 15:04 test
-rwxr-xr-x 1 dima dima  5008 Aug 25 15:04 vnl-align
-rwxr-xr-x 1 dima dima 56637 Aug 25 15:04 vnl-filter
-rwxr-xr-x 1 dima dima  5678 Aug 25 15:04 vnl-gen-header
-rwxr-xr-x 1 dima dima 29815 Aug 25 15:04 vnl-join
-rwxr-xr-x 1 dima dima  3631 Aug 25 15:04 vnl-make-matrix
-rwxr-xr-x 1 dima dima  8372 Aug 25 15:04 vnl-sort
-rwxr-xr-x 1 dima dima  5822 Aug 25 15:04 vnl-tail
-rwxr-xr-x 1 dima dima  4439 Aug 25 15:04 vnl-ts
-rw-r--r-- 1 dima dima   559 Aug 25 15:04 vnlog-base64.h
-rw-r--r-- 1 dima dima  8169 Aug 25 15:04 vnlog.c
-rw-r--r-- 1 dima dima 12677 Aug 25 15:04 vnlog.h


$ (echo '# permissions num_links user group size month day time name';
   ls -l | tail -n +2) |
  vnl-filter 'permissions !~ "^d"' -p name,size |
  vnl-sort -gk size |
  vnl-align

#       name         size
vnlog-base64.h        559
vnl-make-matrix      3631
vnl-ts               4439
vnl-align            5008
Changes              5044
b64_cencode.c        5359
vnl-gen-header       5678
vnl-tail             5822
vnlog.c              8169
vnl-sort             8372
vnlog.h             12677
Makefile            12749
vnl-join            29815
README.template.org 33781
vnl-filter          56637
README.org          69789
#+END_EXAMPLE

With a bit of shell manipulation, these tools can be applied to a whole lot of
different data streams that know nothing of vnlog.

* C interface
** Writing vnlog files
*** Basic usage
For most uses, vnlog files are simple enough to be generated with plain prints.
But then each print statement has to know which numeric column we're populating,
which becomes effortful with many columns. In my usage it's common to have a
large parallelized C program that's writing logs with hundreds of columns where
any one record would contain only a subset of the columns. In such a case, it's
helpful to have a library that can output the log files. This is available.
Basic usage looks like this:

In a shell:

#+BEGIN_SRC sh :results none :exports code
vnl-gen-header 'int w' 'uint8_t x' 'char* y' 'double z' 'void* binary' > vnlog_fields_generated.h
#+END_SRC

#+RESULTS:

In a C program test.c:

#+BEGIN_SRC C
#include "vnlog_fields_generated.h"

int main()
{
    vnlog_emit_legend();

    vnlog_set_field_value__w(-10);
    vnlog_set_field_value__x(40);
    vnlog_set_field_value__y("asdf");
    vnlog_emit_record();

    vnlog_set_field_value__z(0.3);
    vnlog_set_field_value__x(50);
    vnlog_set_field_value__w(-20);
    vnlog_set_field_value__binary("\x01\x02\x03", 3);
    vnlog_emit_record();

    vnlog_set_field_value__w(-30);
    vnlog_set_field_value__x(10);
    vnlog_set_field_value__y("whoa");
    vnlog_set_field_value__z(0.5);
    vnlog_emit_record();

    return 0;
}
#+END_SRC

Then we build and run, and we get

#+BEGIN_EXAMPLE
$ cc -o test test.c -lvnlog

$ ./test

# w x y z binary
-10 40 asdf - -
-20 50 - 0.2999999999999999889 AQID
-30 10 whoa 0.5 -
#+END_EXAMPLE

The binary field in base64-encoded. This is a rarely-used feature, but sometimes
you really need to log binary data for later processing, and this makes it
possible.

So you

1. Generate the header to define your columns

2. Call =vnlog_emit_legend()=

3. Call =vnlog_set_field_value__...()= for each field you want to set in that
   row.

4. Call =vnlog_emit_record()= to write the row and to reset all fields for the
   next row. Any fields unset with a =vnlog_set_field_value__...()= call are
   written as null: =-=

This is enough for 99% of the use cases. Things get a bit more complex if we
have have threading or if we have multiple vnlog ouput streams in the same
program. For both of these we use vnlog /contexts/.

*** Contexts

To support independent writing into the same vnlog (possibly by multiple
threads; this is reentrant), each log-writer should create a context, and use it
when talking to vnlog. The context functions will make sure that the fields in
each context are independent and that the output records won't clobber each
other:

#+BEGIN_SRC C
void child_writer( // the parent context also writes to this vnlog. Pass NULL to
                   // use the global one
                   struct vnlog_context_t* ctx_parent )
{
    struct vnlog_context_t ctx;
    vnlog_init_child_ctx(&ctx, ctx_parent);

    while(records)
    {
        vnlog_set_field_value_ctx__xxx(&ctx, ...);
        vnlog_set_field_value_ctx__yyy(&ctx, ...);
        vnlog_set_field_value_ctx__zzz(&ctx, ...);
        vnlog_emit_record_ctx(&ctx);
    }

    vnlog_free_ctx(&ctx); // required only if we have any binary fields
}
#+END_SRC

If we want to have multiple independent vnlog writers to /different/ streams
(with different columns and legends), we do this instead:

=file1.c=:
#+BEGIN_SRC C
#include "vnlog_fields_generated1.h"

void f(void)
{
    // Write some data out to the default context and default output (STDOUT)
    vnlog_emit_legend();
    ...
    vnlog_set_field_value__xxx(...);
    vnlog_set_field_value__yyy(...);
    ...
    vnlog_emit_record();
}
#+END_SRC

=file2.c=:
#+BEGIN_SRC C
#include "vnlog_fields_generated2.h"

void g(void)
{
    // Make a new session context, send output to a different file, write
    // out legend, and send out the data
    struct vnlog_context_t ctx;
    vnlog_init_session_ctx(&ctx);
    FILE* fp = fopen(...);
    vnlog_set_output_FILE(&ctx, fp);
    vnlog_emit_legend_ctx(&ctx);
    ...
    vnlog_set_field_value__a(...);
    vnlog_set_field_value__b(...);
    ...
    vnlog_free_ctx(&ctx); // required only if we have any binary fields
    vnlog_emit_record();
}
#+END_SRC

Note that it's the user's responsibility to make sure the new sessions go to a
different =FILE= by invoking =vnlog_set_output_FILE()=. Furthermore, note that
the included =vnlog_fields_....h= file defines the fields we're writing to; and
if we have multiple different vnlog field definitions in the same program (as in
this example), then the different writers /must/ live in different source files.
The compiler will barf if you try to =#include= two different
=vnlog_fields_....h= files in the same source.

*** Remaining APIs

- =vnlog_printf(...)= and =vnlog_printf_ctx(ctx, ...)= write to a pipe like
=printf()= does. This exists primarily for comments.

- =vnlog_clear_fields_ctx(ctx, do_free_binary)= clears out the data in a context
and makes it ready to be used for the next record. It is rare for the user to
have to call this manually. The most common case is handled automatically
(clearing out a context after emitting a record). One area where this is useful
is when making a copy of a context:

#+BEGIN_SRC C
struct vnlog_context_t ctx1;
// .... do stuff with ctx1 ... add data to it ...

struct vnlog_context_t ctx2 = ctx1;
// ctx1 and ctx2 now both have the same data, and the same pointers to
// binary data. I need to get rid of the pointer references in ctx1

vnlog_clear_fields_ctx(&ctx1, false);
#+END_SRC

- =vnlog_free_ctx(ctx)= frees memory for an vnlog context. Do this before
throwing the context away. Currently this is only needed for context that have
binary fields, but this should be called for all contexts anyway, in case this
changes in a later revision

** Reading vnlog files
The basic usage goes like this:

#+begin_src c
#include <stdio.h>
#include <stdbool.h>
#include <vnlog/vnlog-parser.h>
bool parse_vnlog(const char* filename)
{
    FILE* fp = fopen(filename);
    if(fp == NULL)
        return false;

    vnlog_parser_t ctx;
    if(VNL_OK != vnlog_parser_init(&ctx, fp))
        return false;

    // String in the "time" column for the most-recently-parsed row
    const char*const* time_record = vnlog_parser_record_from_key(&ctx, "time");
    if(time_record == NULL)
    {
        vnlog_parser_free(&ctx);
        return false;
    }

    int i_record = 0;
    vnlog_parser_result_t result;
    while(VNL_OK == (result = vnlog_parser_read_record(&ctx, fp)))
    {
        for(int i=0; i<ctx.Ncolumns; i++)
            printf("Record %d: %s = %s\n",
                   i_record,
                   ctx.record[i].key, ctx.record[i].value);
        printf("Record %d: time = %s\n",
               i_record, *time_record);
        i_record++;
    }

    vnlog_parser_free(&ctx);
    return true;
}
#+end_src

The usage should be clear from this example. See =vnlog-parser.h= for details.

** Base64 interface
The C interface supports writing base64-encoded binary data using Chris Venter's
libb64. The base64-encoder used here was slightly modified: the output appears
all on one line, making is suitable to appear in a vnlog field. If we're writing
a vnlog with =printf()= directly without using the =vnlog.h= interface described
above, we allow this modified base64 encoder to be invoked by itself. Usage:

#+BEGIN_SRC C
void* binary_buffer     = ...;
int   binary_buffer_len = ...;

char base64_buffer[vnlog_base64_dstlen_to_encode(binary_buffer_len)];
vnlog_base64_encode( base64_buffer, sizeof(base64_buffer),
                     binary_buffer, binary_buffer_len );
#+END_SRC

Clearly the above example allocates the base64 buffer on the stack, so it's only
suitable for small-ish data chunks. But if you have lots and lots of data,
probably writing it as base64 into a vnlog isn't the best thing to do.
* Python interface
Reading vnlog data into a python program is simple. The =vnlog= Python module
provides three different ways to do that:

1. slurp the whole thing into a numpy array using the =slurp()= function. Basic
   usage:

   #+begin_src python
import vnlog
arr,list_keys,dict_key_index = \
    vnlog.slurp(filename_or_fileobject)
   #+end_src

   This parses out the legend, and then calls =numpy.loadtxt()=. Null data values
   (=-=) are not supported

2. Iterate through the records: =vnlog= class, used as an iterator. Basic usage:

   #+begin_src python
import vnlog
for d in vnlog.vnlog(filename_or_fileobject):
    print(d['time'],d['height'])
   #+end_src

   Null data values are represented as =None=

3. Parse incoming lines individually: =vnlog= class, using the =parse()= method.
   Basic usage:

   #+begin_src python
import vnlog
parser = vnlog.vnlog()
for l in file:
    parser.parse(l)
    d = parser.values_dict()
    if not d:
        continue
    print(d['time'],d['height'])
   #+end_src

Most of the time you'd use options 1 or 2 above. Option 3 is the most general,
but also the most verbose and slowest.

** Structured dtypes in slurp()

The =slurp()= example from above is simple: it doesn't specify a =dtype= (data
type), so =float= (64-bit IEEE-754 float) is used by default, for /all/ the data
in the array. You can specify another =dtype=, for instance:

   #+begin_src python
arr,list_keys,dict_key_index = \
    vnlog.slurp(filename_or_fileobject,
                dtype = int)
   #+end_src

You can also specify a [[https://numpy.org/doc/stable/user/basics.rec.html][/structured/ dtype]] to pull out different columns, with
different individual dtypes. Most notably, this allows interpreting some columns
as strings. Let's say you have a very common vnlog data, such as this "data.vnl":

#+begin_example
#  image   x y z temperature
image1.png 1 2 5 34
image2.png 3 4 1 35
#+end_example

Reading this with a simple =vnlog.slurp()= will fail: the filenames are not
parseable as numerical values. We can instead do this:

#+begin_src python
dtype = np.dtype([ ('image',       'U16'),
                   ('x y z',       int, (3,)),
                   ('temperature', float), ])
arr = vnlog.slurp("data.vnl", dtype=dtype)
#+end_src

This will read the image filename, the xyz points and the temperature into
different sub-arrays, with different types each. Accessing the result looks
like this:

#+begin_example
print(arr['image'])
---> array(['image1.png', 'image2.png'], dtype='<U16')

print(arr['x y z'])
---> array([[1, 2, 5],
            [3, 4, 1]])

print(arr['temperature'])
---> array([34., 35.])
#+end_example

Notes:

- The given structured dtype defines both how to organize the data, and which
  data to extract. So it can be used to read in only a subset of the available
  columns. Here I could have omitted the 'temperature' column, for instance

- Sub-arrays are allowed. In the example I could say either

  #+begin_src python
  dtype = np.dtype([ ('image',       'U16'),
                     ('x y z',       int, (3,)),
                     ('temperature', float), ])
  #+end_src

  or

  #+begin_src python
  dtype = np.dtype([ ('image',       'U16'),
                     ('x',           int),
                     ('y',           int),
                     ('z',           int),
                     ('temperature', float), ])
  #+end_src

  The latter would read =x=, =y=, =z= into separate, individual arrays. Sometime
  we want this, sometimes not.

- Nested structured dtypes are not allowed. Fields inside other fields are not
  supported, since it's not clear how to map that to a flat vnlog legend

- If a structured dtype is given, =slurp()= returns the array only, since the
  field names are already available in the dtype

* numpy interface
If we need to read data into numpy specifically, nicer tools are available than
the generic =vnlog= Python module. The built-in =numpy.loadtxt= =numpy.savetxt=
functions work well (with the caveat that =numpy.loadtxt()= should be followed
by =numpysane.atleast_dims(..., -2)= to make sure that a data array of shape
=(Nrows,Ncols)= is returned even if =Nrows==1=. For example to write to standard
output a vnlog with fields =a=, =b= and =c=:

#+BEGIN_SRC python
numpy.savetxt(sys.stdout, array, fmt="%g", header="a b c")
#+END_SRC

Note that numpy automatically adds the =#= to the header. To read a vnlog from a
file on disk, do something like

#+BEGIN_SRC python
array = numpysane.atleast_dims(numpy.loadtxt('data.vnl'), -2)
#+END_SRC

These functions know that =#= lines are comments, but don't interpret anything
as field headers. That's easy to do, so I'm not providing any helper libraries.
I might do that at some point, but in the meantime, patches are welcome.

* Compatibility

I use GNU/Linux-based systems exclusively, but everything has been tested
functional on FreeBSD and OSX in addition to Debian, Ubuntu and CentOS. I can
imagine there's something I missed when testing on non-Linux systems, so please
let me know if you find any issues.

* Caveats and bugs

These tools are meant to be simple, so some things are hard requirements. A big
one is that columns are whitespace-separated. There is /no/ mechanism for
escaping or quoting whitespace into a single field. I think supporting something
like that is more trouble than it's worth.

* Manpages
** vnl-filter
#+BEGIN_EXAMPLE
xxx-manpage-vnl-filter-xxx
#+END_EXAMPLE

** vnl-align
#+BEGIN_EXAMPLE
xxx-manpage-vnl-align-xxx
#+END_EXAMPLE

** vnl-sort
#+BEGIN_EXAMPLE
xxx-manpage-vnl-sort-xxx
#+END_EXAMPLE

** vnl-join
#+BEGIN_EXAMPLE
xxx-manpage-vnl-join-xxx
#+END_EXAMPLE

** vnl-tail
#+BEGIN_EXAMPLE
xxx-manpage-vnl-tail-xxx
#+END_EXAMPLE

** vnl-ts
#+BEGIN_EXAMPLE
xxx-manpage-vnl-ts-xxx
#+END_EXAMPLE

** vnl-uniq
#+BEGIN_EXAMPLE
xxx-manpage-vnl-uniq-xxx
#+END_EXAMPLE

** vnl-gen-header
#+BEGIN_EXAMPLE
xxx-manpage-vnl-gen-header-xxx
#+END_EXAMPLE

** vnl-make-matrix
#+BEGIN_EXAMPLE
xxx-manpage-vnl-make-matrix-xxx
#+END_EXAMPLE

* Repository

https://github.com/dkogan/vnlog/

* Authors

Dima Kogan (=dima@secretsauce.net=) wrote this toolkit for his work at the Jet
Propulsion Laboratory, and is delighted to have been able to release it
publically

Chris Venter (=chris.venter@gmail.com=) wrote the base64 encoder

* License and copyright

This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License as published by the Free
Software Foundation; either version 2.1 of the License, or (at your option) any
later version.

Copyright 2016-2017 California Institute of Technology

Copyright 2017-2018 Dima Kogan (=dima@secretsauce.net=)

=b64_cencode.c= comes from =cencode.c= in the =libb64= project. It is written by
Chris Venter (=chris.venter@gmail.com=) who placed it in the public domain. The
full text of the license is in that file.
