Design for searchcode server

A very brief update about the progress of searchcode server. Currently I am in the middle of reworking how the index is built and maintained. The idea being I want to add zero downtime index rebuilds which requires a blue/green index strategy. It is still very much in flux but the current design is to merge the indexer and searcher which should allow this to happen. I have been playing around with using an iPad as a production device these days and produced the following document.

Edit. People keep asking me what App I used to create this. It was made Pureflow for iOS and then exported.

How to identify software licenses using Python, Vector Space Search and Ngram Keywords

The below is mostly a log of my thought process while building out some functionality that I wanted to add into searchcode server. I kept a record of progress and thoughts while doing this in the hopes that I get some sort of useful blog post out of it. It has been edited somewhat for clarity.

One of the tickets raised for searchcode server is the ability to to filter by licence yes, I am the one who raised the ticket, but it is based on requests from customers. It will also put searchcode server closer to feature parity with Krugle so it seems like a good thing to add.

This means that ideally all I want is a script that given a projects directory and a filename can tell me what licenses it is likely to be under. I can then port that over to searchcode-server and its Java codebase at my leisure.

My first thought was that adding it for say the top 20 most popular licenses shouldn’t be too difficult, and its something that I could always expand on later if things are working well.

As such the first thing I needed was to determine the top software licenses in use which thankfully Blackduck Software has already done

Then I needed to get a copy of them and in a nice format such as JSON to allow for processing. I decided to source them from since generally they should be considered the source of truth for license information.

I then wrote a simple script to pull all the licenses down (yes using regex to pull information out of HTML which is BAD but I am not trying to parse it so I am pretty sure he won’t come) locally and allow for further processing. Sorry SPDX people about crawling your site in a non robots compliant way. I did try to get what I needed and cache it locally so I suspect I impacted the site less than Googlebot would have.

I also added a simple filter to pull back the top 20+ licences that we previously identified so we can test things out.

The next step was to turn the HTML into JSON. Again an ugly script which calls the beast by using regex to pull information out of HTML. One thing I did notice is that the Fair Source licence was missing. Since I was planning on using searchcode server as a test bed I needed that and added it myself.

Once again sorry to the SPDX people. If you come to Sydney and ill buy you a beer and apologize for,

  1. For creating my own short-name for the Fair Source License without permission
  2. For the crappy internet you will experience (Seriously search for Turnbull NBN if you want to see how backwards a country can become, copper for life yo)

The result is now we have a database of about 20 licences that we can use to try and determine what licence a software project is.

Attempt 1

To start with I made the following assumptions.

A file with a name such as LICENSE or COPYING is likely to exist in the root folder of any project and contain license information. If not have a look inside the readme (if it exists). This file if found and it has a license that we can identify then it becomes the base license for all files inside the project. However files inside the project itself may have a header which must also be considered.

One thing that I didn’t consider at first is that there may be another license/copying file somewhere deeper inside the file tree. Something to consider for later.

First thought was to just use the vector space search algorithm. It really is my hammer for every problem. It works reasonably well for a lot of them, is fast enough in most cases and generally gets the job done. Thankfully I had already written one for Python a while ago. Don’t hate please, I wrote this 10 years ago when I was first learning it and yes its not Pythonic but works. One thing to note is that licenses tend to be of different length. This means that licenses that are closer to each other in length will be matched more closely using the vector space which is a cool side effect of how it works.

So the algorithm is,

Find likely candidates for license files.
Compare them to the list of known licenses using the vector space model.
Keep the most likely match.

Then walk through every file in the repository, checking for the special header and when there are no matches try the full header because things like the entire MIT license tends to get included at the top of the file. The resulting ugly script produced the following.

The result for searchcode-server

Project License
0.929696395964 Fair Source License v0.9
0.802095284986 Mozilla Public License 2.0 (no copyleft exception)
0.802095284986 Mozilla Public License 2.0

0.925341443302 MIT License /searchcode-server/src/main/resources/public/js/cache.js

Wow. That is a very cool result. It actually worked. It not only picked up that we are using the Fair Source Licence it also picked up that that one file is using the MIT license. Lets try it out on some other projects.

Against wordpress,

Project License
0.623430083878 GNU General Public License v2.0 only
0.614318516008 GNU General Public License v1.0 only
0.601642491832 GNU Library General Public License v2 only

While it did pick up that its probably using GNU GPL v2.0 but it wasn’t as confident as it was with the previous. Lets try another one.

Against minitwit (a Spark Java example project)

Project License
0.954897366777 MIT License
0.784597744861 Fair Source License v0.9
0.777231345803 Apache License 2.0

Not bad. Its pretty confident that it us under the MIT license.

Against Armory React

Project License
0.945769202843 BSD 3-clause Clear License
0.937649791859 BSD with attribution
0.927894236317 BSD 2-clause "Simplified" License

Again pretty good.

Ok. So it looks like we could just pop the top license off and call it a day. This works pretty well with the most common licenses, but why limit ourselves. Lets just do every license that SPDX has listed? It should work just as well in theory. All we need to do is remove the filter in and rebuild the database and try again.

Trying out on searchcode-server again

Project License
0.929696395964 Fair Source License v0.9
0.813818153434 OCLC Research Public License 2.0
0.804549095187 OSET Public License version 2.1

0.977617793941 BSD Zero Clause License /searchcode-server/include/license/database.json
0.939606278132 Attribution Assurance License /searchcode-server/include/license/database.json
0.908192569643 Open CASCADE Technology Public License /searchcode-server/include/license/database.json
0.902275136399 Adaptive Public License 1.0 /searchcode-server/include/license/database.json
0.93217139424 JSON License /searchcode-server/src/main/resources/public/js/cache.js
0.925341443302 MIT License /searchcode-server/src/main/resources/public/js/cache.js
0.914039614281 feh License /searchcode-server/src/main/resources/public/js/cache.js

Ok so it still picked up fair source as the main project license which is a good result. However our very cool result of MIT being found in cache.js has gone away. Apparently the JSON license looks like the MIT license to the vector space. Indeed a diff between them shows that they are almost the same. The differences being right at the start,

MIT License Copyright (c)
JSON License Copyright (c) 2002

and buried in the middle of the JSON license

The Software shall be used for Good, not Evil.

Hah! I remember reading about that a while ago. Something about Google not being able to use it because apparently their motto “Don’t be evil” is more a guideline then a rule. In all seriousness though its actually due to the license being classified as a non-free license because it imposes conditions which restrict the usage see for more details.

So what we would normally do about now is add keyword weighting to the terms so that in this case MIT makes it rank higher for MIT and JSON for JSON. In fact I started doing just that with keyword it then realised with 328 licenses this is going to be a painful process. Perhaps there is a better way.

Thinking about it what we really want is to find keywords or a collection of multiple keywords that we know to be unique for each license. Then all we need to is check the text for the presence of those keywords. The catch being we need to ensure that they are unique for each license. To do so what I think will work is break the license up into collections of works of length 1-10 and check for unique-ness against the other licenses. The technical term for these terms is ngram.

An example would be,

Lorem ipsum dolor sit amet consetetur sadipscing elitr


[('lorem', 'ipsum'), ('ipsum', 'dolor'), ('dolor', 'sit'), ('sit', 'amet'), ('amet', 'consetetur'), ('consetetur', 'sadipscing'), ('sadipscing', 'elitr')]


[('lorem', 'ipsum', 'dolor'), ('ipsum', 'dolor', 'sit'), ('dolor', 'sit', 'amet'), ('sit', 'amet', 'consetetur'), ('amet', 'consetetur', 'sadipscing'), ('consetetur', 'sadipscing', 'elitr')]

Thankfully this is pretty easy to do in Python so I borrowed an existing bit of code to do it for me,

input_list = ['all', 'this', 'happened', 'more', 'or', 'less']

def find_ngrams(input_list, n):
  return zip(*[input_list[i:] for i in range(n)])

For the record I am totally aware that NTLK can also do this but since I don’t currently have that installed lets go pure Python. It will be a little slower but considering this should rarely run this calculation I am not too worried about performance yet. Of course thats a good idea to live by anyway. Only worry about performance when it becomes an issue.

We can then generate ngrams for each license, then check for its uniqueness in every other one. If no matches found then woohoo we have a gram that uniquely matches the license.

Some simple but stupid code was written which does exactly this. Turns out that language is a lot more distinctive for licenses then I first thought,

0BSD 188
AAL 1985
Abstyles 437
Adobe-2006 1234
Adobe-Glyph 1620
ADSL 608
AFL-1.1 555
AFL-1.2 251
AFL-2.0 69
AFL-2.1 67
AFL-3.0 452
Afmparse 959
AGPL-1.0 2212

For the BSD Zero Clause License there are apparently 188 unique ngrams between a length of 2-10 words in it. For the Affero General Public License v1.0 there are a whopping 2212! The numbers were so high that I changed the ngrams to start at 5 to 10. This dropped the numbers found by about 25% which seems about right as you would expect the most unique combinations of words to exist at the upper range of ngrams.

One problem I noticed with this is that a lot of the ngrams are based on names that exist within the sample licenses that SPDX has. For example BSD Zero Clause has the name “Rob Landley” which produces a lot of ngrams with this name in it as is indeed unique, but is useless unless we happen to be checking code that Rob has written.

However the performance issue that I was worried about before popped up. it was taking a long time to process. Not surprising considering the actual implementation consists of multiple nested loops. With the encouraging result that there is a lot of uniqueness for most licenses I tried just searching for ngrams of 4-5 words long to speed things up. Assuming we didn’t find 0 matches then happy days we can try implementing using what we have and everything should be fine. A few small tweaks later and I ran it again.

Doh! As it turns out some are not unique enough. The culprits,


I modified the code to just loop those ones with a more exhaustive search to find what worked. With ngrams of length 2-10 still there was not enough uniqueness. So I went all out, ngrams from length 2-35.

Artistic-1.0 120
BSD-3-Clause 21

This resolved the issue for Artistic-1.0 and BSD-3-Clause but we still have nothing for the following licenses,


Something is wrong here.

Turns out some of these are particularly troubling. The Mozilla Public License 1.1 (MPL-1.1 in the above) for example seems to be embedded  in the Netscape Public License v1.1 which of course means nothing about it is unique compared to the other. The others have a similar story. I tried searching just between both those licences with ngrams of length 2-100 to see if anything would turn up, which of course took a crazy amount of time to process. The result was that there was nothing that could be used keyword wise to seperate these licenses.

How about a hybrid approach?

If we cannot definitively say using keywords what license the file is, then we can fall back to the vector space to rank based on those without keywords. To do so I flushed the results of the last run into the database file using 7-8 ngrams for everything except Artistic-1.0 and BSD-3-Clause which checked for ngrams with a range of 2-35. The results of this produced the following licenses with their number of unique ngrams,

0BSD 25
AAL 246
Abstyles 54
Adobe-2006 163
Adobe-Glyph 210
Fair-Source-0.9 267

Most seem to have over 100 or so unique ngrams which means they will probably work pretty well, and as expected the only exceptions are the MPL licenses which has nothing unique about it compared to every other license.

I ended up cleaning up the code at this point and improving on the loops so thankfully it took only a few minutes to run. Some of the original runs were taking tens of minutes due to inefficient code so this was a big win. The resulting file was on the heavy side though at 20 megabytes and crashed most editors when I tried to read it. To resolve this I truncated down to at most 50 unique ngrams per license to see how this worked in the real world. This file weighed in a much more realistic 3 megabytes.

I then created which used the new database using keywords to guess which license the applications had applicable. Firstly I tried it against searchcode-server itself. With the result that the LICENCE file found was indeed the Fair Source License. I then tried it against GCC. Its interesting to note that this resulted in its COPYING file being marked as containing both the GPL-2.0 and LGPL-2.1. At first I thought this might have been a bug in my logic but it seems it was actually correct. The offending ngram used to match was

"street, fifth floor, boston, ma 02110-1301 usa"

Which is supposed to be unique to LGPL-2.1 but included in this case. Since we actually have 813 (but truncated to 50) ngrams for each I figured we might as well when checking see if MOST (70%) of the keywords are there, and if so mark it as a match otherwise ignore. This resutled in the following for GCC


Which is correct. In fact further tests on various other repositories worked until I hit the react-armory which is under the BSD Clear License. Turns out most of the ngrams generated for it actually involve the project name meaning they are useless. Annoyingly the ngram of length 3 “BSD Clear License” which is unique was missed because the parser was set to look from 7-8 ngrams. Urgh.

Thinking about this for a bit, it totally makes sense to look for ngrams from 2-8 even when we are truncating to the top 50. The smaller ones are going to be high value ones usually and there shouldn’t be too many of them. The only problem is the increased processing time to walk all of the combinations of things like [‘the’, ‘license’] and the like. At the very least we should include trigrams (3 length ngrams) since it solves this specific issue and should work to be unique for a lot of licenses. Modifying the script to take in a range of numbers defined was easy enough then just let it run and produce the new database to work with and try everything again. It took longer than before but not so much that it was annoying.

Due to how painful this was getting to test manually I started to build a small test harness ( which I could eyeball to see if I was getting closer to a result I wanted without regressions. Thankfully it was working perfectly for the tests I was trying.

At this point I tried the same technique across all the files in repositories. Using the previous example of searchcode-server I would have expected that the cache.js file would be marked as MIT license as before. This however was not the case. Because I had the keyword match script as a sliding scale where it needed a few matches to be considered positive it was missing out on this one as there were only a few matches.

I decided at this time to integrate the Vector Space back in. If a file was marked with any license, we would then confirm using the Vector Space and if it was able to have a high degree of confidence over the license that matched then it would be marked as the license. After adding this logic I managed to get the following output,

Bens-MBP:license boyter$ python
0.988840442861 Fair-Source-0.9 /searchcode-server/LICENSE.txt
0.442713859889 MIT /searchcode-server/src/main/resources/public/js/cache.js

Exactly what I was looking for. All of the tests I had previously written also passed with this logic. With a simple change to only check the top of the file where the header would be by cutting the string down to the length of the license I was able to improve the result considerably,

Bens-MBP:license boyter$ python
0.988840442861 Fair-Source-0.9 /searchcode-server/LICENSE.txt
0.985719098155 MIT /searchcode-server/src/main/resources/public/js/cache.js

That is a seriously cool result. Not only was the code able to identify the licences, it did so with a very high percentage of confidence to boot.

I tried running it over a collection of projects I had checked out including GCC, Linux and WordPress

 0.993261478239 BSD-3-Clause-Clear /armory-react/LICENSE
 0.999679612780 GPL-3.0 /decodingcaptchas/LICENSE
 0.980796066053 OFL-1.1 /decodingcaptchas/lib/font/source-sans-pro/LICENSE
 0.999692799354 GPL-3.0 /freemoz/LICENSE
 0.999792347852 GPL-2.0 /gcc/COPYING
 0.999922926136 LGPL-2.1 /gcc/COPYING.LIB
 0.999679612780 GPL-3.0 /gcc/COPYING3
 0.999902746595 LGPL-3.0 /gcc/COPYING3.LIB
 0.999792347852 GPL-2.0 /gcc/gcc/COPYING
 0.999932589474 LGPL-2.1 /gcc/gcc/COPYING.LIB
 0.999679612780 GPL-3.0 /gcc/gcc/COPYING3
 0.999902746595 LGPL-3.0 /gcc/gcc/COPYING3.LIB
 0.858896713823 GPL-2.0 /gcc/gcc/df-core.c
 0.999532020106 GFDL-1.3 /gcc/gcc/ada/doc/share/gnu_free_documentation_license.rst
 0.948529328513 bzip2-1.0.6 /gcc/gcc/testsuite/gcc.c-torture/execute/pr20527-1.c
 0.994200247145 bzip2-1.0.6 /gcc/gcc/testsuite/gcc.dg/params/LICENSE
 0.999792347852 GPL-2.0 /gcc/include/COPYING
 0.999679612780 GPL-3.0 /gcc/include/COPYING3
 0.889767272339 bzip2-1.0.6 /gcc/libbacktrace/alloc.c
 0.899838703127 bzip2-1.0.6 /gcc/libbacktrace/atomic.c
 0.883378984629 bzip2-1.0.6 /gcc/libbacktrace/backtrace.c
 0.885232659466 bzip2-1.0.6 /gcc/libbacktrace/btest.c
 0.866517942966 bzip2-1.0.6 /gcc/libbacktrace/dwarf.c
 0.881126480326 bzip2-1.0.6 /gcc/libbacktrace/elf.c
 0.876148037216 bzip2-1.0.6 /gcc/libbacktrace/fileline.c
 0.862314849462 bzip2-1.0.6 /gcc/libbacktrace/mmap.c
 0.876559695369 bzip2-1.0.6 /gcc/libbacktrace/mmapio.c
 0.903997364404 bzip2-1.0.6 /gcc/libbacktrace/nounwind.c
 0.880387358104 bzip2-1.0.6 /gcc/libbacktrace/pecoff.c
 0.872402129061 bzip2-1.0.6 /gcc/libbacktrace/posix.c
 0.881550515104 bzip2-1.0.6 /gcc/libbacktrace/print.c
 0.878971997218 bzip2-1.0.6 /gcc/libbacktrace/read.c
 0.880857671076 bzip2-1.0.6 /gcc/libbacktrace/simple.c
 0.897738871764 bzip2-1.0.6 /gcc/libbacktrace/sort.c
 0.890041393843 bzip2-1.0.6 /gcc/libbacktrace/state.c
 0.874782494001 bzip2-1.0.6 /gcc/libbacktrace/stest.c
 0.897023027383 bzip2-1.0.6 /gcc/libbacktrace/unknown.c
 0.879821572348 MITNFA /gcc/libffi/src/mips/ffi.c
 0.997055163924 LGPL-2.1 /gcc/libiberty/copying-lib.texi
 0.999932589474 LGPL-2.1 /gcc/libiberty/COPYING.LIB
 0.899167675944 Intel /gcc/liboffloadmic/runtime/liboffload_error.c
 0.889543866358 Intel /gcc/liboffloadmic/runtime/liboffload_msg.c
 0.887357763796 Intel /gcc/liboffloadmic/runtime/orsl-lite/lib/orsl-lite.c
 0.999932589474 LGPL-2.1 /gcc/libquadmath/COPYING.LIB
 0.857337014417 NCSA /gcc/libsanitizer/LICENSE.TXT
 1.000000000000 BSL-1.0 /gcc/zlib/contrib/dotzlib/LICENSE_1_0.txt
 0.998470560414 GPL-2.0 /linux/COPYING
 0.999831352903 LGPL-2.0 /linux/arch/sparc/lib/COPYING.LIB
 0.997101938433 GPL-2.0 /linux/Documentation/networking/LICENSE.qlcnic
 0.997101938433 GPL-2.0 /linux/Documentation/networking/LICENSE.qlge
 0.997004626197 GPL-2.0 /linux/Documentation/scsi/LICENSE.qla2xxx
 0.997004626197 GPL-2.0 /linux/Documentation/scsi/LICENSE.qla4xxx
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c3xxx/adf_c3xxx_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c3xxx/adf_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c3xxxvf/adf_c3xxxvf_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c3xxxvf/adf_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c62x/adf_c62x_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c62x/adf_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c62xvf/adf_c62xvf_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_c62xvf/adf_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_accel_engine.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_admin.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_aer.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_cfg.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_ctl_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_dev_mgr.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_hw_arbiter.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_init.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_isr.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_pf2vf_msg.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_sriov.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_transport.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_transport_debug.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_vf2pf_msg.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/adf_vf_isr.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/qat_algs.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/qat_asym_algs.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/qat_crypto.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/qat_hal.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_common/qat_uclo.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_dh895xcc/adf_dh895xcc_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_dh895xcc/adf_drv.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_dh895xccvf/adf_dh895xccvf_hw_data.c
 0.900564102581 Intel /linux/drivers/crypto/qat/qat_dh895xccvf/adf_drv.c
 0.998958351972 GPL-2.0 /linux/drivers/staging/rtl8192e/license
 0.999594583136 GPL-2.0 /linux/drivers/staging/rtl8192u/copying
 0.999792347852 GPL-2.0 /linux/tools/usb/usbip/COPYING
 0.952930843666 Sleepycat /pathos/dill-0.2.1/LICENSE
 0.952930843666 Sleepycat /pathos/pathos-master/LICENSE
 0.952930843666 Sleepycat /pathos/pox-0.2/LICENSE
 0.987991559152 MIT /phonecat/LICENSE
 1.000000000000 Apache-2.0 /python-goose/LICENSE.txt
 1.000000000000 Apache-2.0 /searchcode/searchcode/searchcode/static/admin/fonts/LICENSE.txt
 0.987991559152 MIT /searchcode/searchcode/searchcode/static/admin/js/vendor/xregexp/LICENSE-XREGEXP.txt
 0.988840442861 Fair-Source-0.9 /searchcode-server/LICENSE.txt
 0.985719098155 MIT /searchcode-server/src/main/resources/public/js/cache.js
 0.985719098155 MIT /searchcode-server/target/classes/public/js/cache.js
 0.999268167835 LGPL-2.1 /seo/vendor/videlalvaro/php-amqplib/LICENSE
 0.999692799354 GPL-3.0 /SingleBugs/LICENSE
 0.999692799354 GPL-3.0 /testing/LICENSE
 0.997865652460 GPL-2.0 /wordpress/license.txt
 0.999792346238 GPL-2.0 /wordpress/wp-content/themes/twentyfourteen/genericons/LICENSE.txt
 0.999792346238 GPL-2.0 /wordpress/wp-content/themes/twentythirteen/fonts/LICENSE.txt
 0.999792346238 GPL-2.0 /wordpress/wp-includes/js/plupload/license.txt
 0.999932589474 LGPL-2.1 /wordpress/wp-includes/js/tinymce/license.txt

Rather cool. Lots of licenses identified with quite a lot of confidence.

There is however one issue I am overlooking. Take for example a project which includes another project in a sub directory. What license should be displayed for the files that are in the latter? In this case I would expect that they are marked with both. It would be very nice to see this information.

One final issue is what to do when there are multiple license files in the root directory. GCC is an example of this and it has 4 licenses defined in the root. The idea being you take which one is most applicable to your project.

0.999792347852 GPL-2.0 /gcc/COPYING
0.999922926136 LGPL-2.1 /gcc/COPYING.LIB
0.99967961278 GPL-3.0 /gcc/COPYING3
0.999902746595 LGPL-3.0 /gcc/COPYING3.LIB

Looking at the SPDX specification the rule is to define them as being under all. This is the exact text regarding this,

Representing Multiple Licenses

Multiple licenses can be represented using a SPDX license expression as defined in Appendix IV. A set of licenses must be enclosed in parentheses (this is a convention for SPDX expressions). As further described there:

When there is a choice between licenses (“disjunctive license”), they should be separated with “OR”. If presented with a choice between two or more licenses, use the disjunctive binary “OR” operator to construct a new license expression.
Similarly when multiple licenses need to be simultaneously applied (“conjunctive license”), they should be separated with “AND”. If required to simultaneously comply with two or more licenses, use the conjunctive binary “AND” operator to construct a new license expression.
In some cases, a set of license terms apply except under special circumstances, in this case, use the “WITH” operator followed by one of the recognized exception identifiers.
Sometimes a set of license terms apply except under special circumstances. In this case, use the binary “WITH” operator to construct a new license expression to represent the special exception situation.

SPDX-License-Identifier: (GPL-2.0 OR MIT)
SPDX-License-Identifier: (LGPL-2.1 AND BSD-2-CLAUSE)
SPDX-License-Identifier: (GPL-2.0+ WITH Bison-exception-2.2)

This was taken from Appendix V: Using SPDX short identifiers in Source Files

Fair enough. We then need to write one last version of our license guesser which will use everything done above BUT support multiple licenses and look for license files inside root directories and make anything below it as belonging to that one, unless of course there is another license file or it is over-ridden by the header. We are not trying to keep track of the above WITH or AND logic described above as I just want to mark each file with the potential license. As such just marking it so is good enough.

For this I simply copied the existing and created which should hopefully be the last version for this. What we now need to do is walk the tree, and every time we encounter a license file, keep track of the license that the file should be under, and for any file that is a child of that license mark as such. When we leave the directory then we pop the license off.

Thankfully this was a very easy change to implement. I used a project which I knew to already have some mixed licenses and ran over it.

 >>>>>>> /decodingcaptchas/LICENSE GPL-3.0
 >>>>>>> /decodingcaptchas/LICENSE GPL-3.0
 >>>>>>> /decodingcaptchas/LICENSE GPL-2.0
 >>>>>>> /decodingcaptchas/LICENSE GPL-2.0
 /decodingcaptchas/Gruntfile.js GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/ GPL-2.0 GPL-3.0
 /decodingcaptchas/code/style.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/reveal.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/print/paper.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/print/pdf.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/beige.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/black.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/blood.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/league.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/moon.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/night.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/serif.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/simple.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/sky.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/solarized.css GPL-2.0 GPL-3.0
 /decodingcaptchas/css/theme/white.css GPL-2.0 GPL-3.0
 /decodingcaptchas/js/reveal.js GPL-2.0 GPL-3.0
 >>>>>>> /decodingcaptchas/lib/LICENSE Fair-Source-0.9
 /decodingcaptchas/lib/css/zenburn.css Fair-Source-0.9 GPL-2.0 GPL-3.0
 /decodingcaptchas/lib/font/league-gothic/league-gothic.css Fair-Source-0.9 GPL-2.0 GPL-3.0
 >>>>>>> /decodingcaptchas/lib/font/source-sans-pro/LICENSE OFL-1.1
 >>>>>>> /decodingcaptchas/lib/font/source-sans-pro/LICENSE OFL-1.1
 /decodingcaptchas/lib/font/source-sans-pro/source-sans-pro.css Fair-Source-0.9 GPL-2.0 GPL-3.0 OFL-1.1
 /decodingcaptchas/lib/js/classList.js Fair-Source-0.9 GPL-2.0 GPL-3.0
 /decodingcaptchas/lib/js/head.min.js Fair-Source-0.9 GPL-2.0 GPL-3.0
 /decodingcaptchas/lib/js/html5shiv.js Fair-Source-0.9 GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/highlight/highlight.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/leap/leap.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/markdown/markdown.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/markdown/marked.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/math/math.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/multiplex/client.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/multiplex/index.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/multiplex/master.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/notes/notes.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/notes-server/client.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/notes-server/index.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/print-pdf/print-pdf.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/remotes/remotes.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/search/search.js GPL-2.0 GPL-3.0
 /decodingcaptchas/plugin/zoom-js/zoom.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/qunit-1.12.0.css GPL-2.0 GPL-3.0
 /decodingcaptchas/test/qunit-1.12.0.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/test-markdown-element-attributes.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/test-markdown-slide-attributes.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/test-markdown.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/test-pdf.js GPL-2.0 GPL-3.0
 /decodingcaptchas/test/test.js GPL-2.0 GPL-3.0

What this shows is each file along with each license that the program believes it to belong to. Files prefixed with >>>>>>> indicate a license file which changes the licenses of the files below it.

The root of the project is dual licensed under GPL-2.0 and GPL-3.0 which makes everything have at least those two licenses. There are however also some fonts under the SIL Open Font License 1.1 which were also picked up. To make things a little harder I added the Fair Source license under the lib directory (just as a test) to see if this would be reflected correctly.

I am pretty happy with the result. So I took the code and ran it against GCC and the Linux Kernel. The output for both are too large to post on this blog but you can view the GCC one as a gist

The last part was to add back the file check so that we can identify license headers for each file in the subfolders. Thankfully this was just a short tweak. Of course the generation is now much slower due to add the additional processing but it seemed to work pretty well.

Well that about covers that. Everything seems to work as I would expect and it would be reasonably easy at this point to take the code and produce a full blown SPDX parser. I will leave that as an exercise for the reader (unless it turns out I need one at a later date).

The next step for me is to integrate this into searchcode server, which is just porting the above into Java and then adding this information as a facet for searching. This is something I may write about later. If you are interested in a code search application though please check it out!

I have uploaded all the code into the following github repository released under the MIT License. Note that the database will also be released under Creative Commons inside the searchcode-server project itself and it is also something I will be keeping up to date so it might be a better source if you want to do any license matching.

Repository overview now in searchcode server

One feature that I have wanted for a long time in searchcode server was a page which would give an overview of a repository. I wanted the overview to give a very high look at the languages used, the total number of files, estimated cost and who would be the best people to talk to.

One thing that occurred to me when I started work was that it would be nice to calculate a bus factor for the repository as well. After all we all know that project managers do like to know who are the most critical contributors to any project and what the risk is.

Below is the what has been added into searchcode server.

The most interesting part of the above in my opinion is the overview blurb. It attempts to summarise all of the figures below and let anyone know in plain english where the repository stands.

An example for searchcode server’s code itself,

“In this repository 2 committers have contributed to 228 files. The most important languages in this repository are Java, CSS and Freemarker Template. The project has a low bus factor of 2 and will be in trouble if Ben Boyter is hit by a bus. The average person who commits this project has ownership of 50% of files. The project relies on the following people; Ben Boyter, =.”

Certainly there is room for improvement on this page and I am hoping to add what I am calling signals logic to it. This would involve scanning the code to determine what languages, features and libraries are being used and add those to the report. The end goal would be to find for instance C# code using MySQL and ReactJS.

The last bit of news is that I am moving over to the same codebase. This should improve things in a few ways. The first bring the improved performance when moving from Python to Java. It should also mean that I can focus on a single codebase.

Anyway you will be able to get the new repository overview in the next release of searchcode server 1.3.6 which will be released before the end of January 2017.

Sphinx Real Time Index How to Distribute and Hidden Gotcha

I have been working on real time indexes with Sphinx recently for the next version of and ran into a few things that were either difficult to search for or just not covered anywhere.

The first is how to implement a distributed search using real time indexes. It’s actually done the same way you would normally create an index. Say you had a single server with 4 index shards on it and you wanted to run queries against it. You could use the following,

index rt
    type = distributed
    local = rt1
    agent = localhost:9312:rt2
    agent = localhost:9312:rt3
    agent = localhost:9312:rt4

You would need to have each one of your indexes defined (only one is added here to keep the example short)

index rt1
    type = rt1
    path = /usr/local/sphinx/data/rt1
    rt_field = title
    rt_field = content
    rt_attr_uint = gid

Using the above you would be able to search across all of the shards. The trick is knowing that to update you need to update each shard yourself. You cannot pass documents to the distributed index but instead must make a separate update to each shard. Usually I split sphinx shards based on a query like the following,

SELECT cast((select id from table order by 1 desc limit 1)/4 as UNSIGNED)*2, \
         cast((select id from table order by 1 desc limit 1)/4 as UNSIGNED)*3 \
         FROM table limit 1

Where the 4 is the number of shards and the multiplier splits the shards out. It’s performant due to index use. However for RT I suggest a simple modulas operator % against the ID column for each shard as it allows you to continue to scale out to each shard equally.

The second issue I ran into was that when defining the attributes and fields you must define all the fields before the uints. The above examples work fine but the below is incorrect. I couldn’t find this mentioned in the documentation.

index rt
    type = rt
    path = /usr/local/sphinx/data/rt
    rt_attr_uint = gid # this should be below the rt_fields
    rt_field = title
    rt_field = content

GPL Time-bomb an interesting approach to #FOSS licensing

UPDATES Following some feedback I am going to rename my usage of “Time-Bomb” due to potential negative connotation on the words. I am going to call it “Eventually Open”. Also a few other things need mentioning. I am not looking for code submissions back into the source at this time. This was a move to show that there are no back-doors in the code sending source code back to a master server.

About a week ago I released searchcode server under the fair source licence. From day one I had wanted to release it using some form of licence where the code was available but I wanted to lock it somewhat because frankly I do want to make some money out of my time investment. That’s not the whole story however. I did not want to create another “Look but don’t touch” situation forever and I certainly didn’t want searchcode to be constrained by a licence in the event that I die, lose interest or stop updating the code.

The result of this was that I have added what I am going to call a GPL Time-Bomb into into the licencing of searchcode server. Here is how it works. After a specified period of time the current version of searchcode server can be re-licensed under the GPL v3. This is a shifting date such that each new release extends its own time-bomb further into the future. However the older releases time is still fixed. The time-bomb for version 1.2.3 and 1.2.4 takes place on the 27th August 2019 at which point you can take the source using GPL 3.0. Assuming searchcode server 6.1.2 comes out at roughly the same time its time-bomb will be set to the 27th of August 2022 but the 1.2.3 release will be unaffected.

In short I have put a time limit of 3 years to make money out of the product and if I am unable it is turned over to the world to use as they see fit. Even better, assuming searchcode server becomes a successful product I will be forced to continually improve it and upgrade if I want to keep a for sale version without there being an equivalent FOSS version around (which in theory could be maintained by the community). In short everyone wins from this arrangement, and I am not forced to rely on a support model to pay the bills which frankly only works when you have a large sales team.

Here’s hoping this sort of licencing catches on as there are so many products out there that could benefit from it. If they take off the creators have an incentive to maintain and not milk their creation and those that become abandoned even up available for public use which I feel is a really fair way of licencing software.

Agree? Disagree? Email me or hit me up on twitter.

searchcode server under fair source

A very quick blog today. I have released searchcode server under the fair source licence. This means that as of a few days ago you can view the source, change it modify it and run it as you see fit so long as you have less than 5 users.

The source is hosted on github (I may move this to GitLab sometime in the future) and you can view it here.

So what does this mean? Well the community edition still exists (run searchcode with as many users as you want) as do the paid versions with support and all the full features. The real advantage however is that you can now vet the source code to ensure that searchcode server is not secretly sending your most valuable asset to some hidden server somewhere. In addition it means I can now talk about the source openly and will be writing some posts about how I ran into some CPU branching issues which slowed down some code.

Good news all around then. Be sure to check out the source and let me know what you think.

Syncing Stash/BitBucket with searchcode server

Recently it came up to perform a slight integration piece between a on premises Stash/BitBucket install and a searchcode server install. Thankfully both have an API and very thankfully there is a nice Python library for talking to Stash/BitBucket.

Below is the code used. It pulls out all of the repositories from every project, checks if it exists in searchcode and if not adds it as a repository to be indexed. You need to install stashy (pip install stashy) and run it whenever you have new repositories. One idea is to set it as a cron task and ensure everything is in sync.

Note that this does not remove repositories that have been indexed, but it would not take much work to achieve it.

import stashy
from hashlib import sha1
from hmac import new as hmac
import urllib2
import json
import urllib

def getstashrepos():
    stash = stashy.connect("https://mystashserver/", "STASH_USERNAME", "STASH_PASSWORD")

    projects = stash.projects.list()
    repos = [stash.projects[x['key']].repos.list() for x in projects]

    stashrepos = []

    for repo in repos:
        stashrepos = stashrepos + [{'name': x['project']['key'] + '-' + x['slug'],
                                    'cloneUrl': x['cloneUrl'],
                                    'browse': x['links']['self'][0]['href']} for x in repo]

    return stashrepos

def addtosearchcode(repo):
    reponame = repo['name']
    repourl = repo['cloneUrl']
    repotype = "git"
    repousername = "STASH_USERNAME"
    repopassword = "STASH_PASSWORD"
    reposource = repo['browse']
    repobranch = "master"

    message = "pub=%s&reponame=%s&repourl=%s&repotype=%s&repousername=%s&repopassword=%s&reposource=%s&repobranch=%s" % (

    sig = hmac(privatekey, message, sha1).hexdigest()

    url = "http://mysearchcodeserver/api/repo/add/?sig=%s&%s" % (urllib.quote_plus(sig), message)

    data = urllib2.urlopen(url)
    data =

    data = json.loads(data)
    print reponame, data['sucessful'], data['message']


message = "pub=%s" % (urllib.quote_plus(publickey))

sig = hmac(privatekey, message, sha1).hexdigest()
url = "http://mysearchcodeserver/api/repo/list/?sig=%s&%s" % (urllib.quote_plus(sig), message)

data = urllib2.urlopen(url)
data =

data = json.loads(data)
existingrepos = [x['name'] for x in data['repoResultList']]

for repo in getstashrepos():
    if repo['name'] not in existingrepos:
        addtosearchcode(repo) The Architecture – migration 3.0

27th July 2016 at about 9:30pm my local time (GMT +10) I updated the A records for searchcode’s nameservers to point at a new stack that has been several months in the making. As with most posts of this sort of nature a quick recap of where things were and where they are now.

The previous searchcode stack consisted of two dedicated servers hosted by Hetzner. I have previously discussed this about two years ago when discussing searchcode next. The first server was a reasonably powerful machine running pretty much all of code required to deliver itself with the exception of the actual index. searchcode is a Django application and was using nginx to serve results directly out of memcached where possible to avoid consuming a running Gunicorn process. The move to have another server for the index came pretty quickly after searchcode was released as it was just not performant enough with everything on a single box which was the situation for a short time.

searchcode before

This structure worked well for the last 2 years or so but I had noticed that the load average on the frontend was starting to average out at about 3.0+ and would quite often rise to 7.0+ Considering the machine had only 4 real CPU cores this was an issue. Interestingly it also caused the number of requests that searchcode could respond to to max out. In addition the MySQL database had some corruption somewhere in the middle which made to app increasingly unstable. The application was going down where nothing short of a reboot would save it at least once a month. Finally I had grown as a developer over the last two years and it was time to move to something more stable and better performing.

The first thing in this modern cloud world was start looking at moving to something like AWS or DigitalOcean. I firstly created a simple spreadsheet with what I was looking to move towards along with expected costs. In short I wanted to break searchcode apart so that it consisted of the following parts,

Frontend server. Would provide SSL termination to Varnish and reverse proxy back to application servers. Requires, either a lot of RAM or fast disk. If RAM is low but disk is fast can use Varnish with disk cache.

Backend server. Would run the application itself. Scales horizontally. Requires a fast CPU to process the code results.

Indexer server. Would host the Sphinx indexer. Scales horizontally. Requires a fast CPU, reasonably amounts of RAM and about 25 GB of amount of disk space per CPU core, preferably SSD.

Database server. Would host the MySQL database. Does not scale horizontally. Requires lots of RAM (more than 4 GB) and 2 TB of disk space.

With these requirements in mind. I started shopping around.

AWS was ruled out almost immediately due to the cost. This was in spite of the fact that I have a great deal of experience dealing with the AWS API’s. As a rule I run as lean as possible and AWS while brilliant ended up costing more than I would have liked.

I then started looking at DigitalOcean. I have always been a fan of how fast they spin instances up, the simple API and their prices. They also have excellent support and are pretty lenient when it comes to how much CPU and DiskIO you consume. When I started looking however they had not launched Block Storage, which meant I needed the $640 a month plan for the database which was even more expensive then AWS. Later they did release block storage, but the resulting price was still rather high. I still use DigitalOcean for spinning up test stacks.

I also looked at Vultr. It’s pretty safe to say they are a DigitalOcean clone but with more data centers, competitive prices and much worse customer support. They do have one intriguing server option however not mentioned on their public website, which is a storage server. It’s a server backed by a regular spinning rust style disk, but as such is far cheaper than anything offered by any other company. A database server with 1 TB of storage, 4 GB RAM and 2 CPU’s (the largest storage instance they have) is only $40 a month.

A believer in infrastructure as code I was very keen to move to one of the cloud servers and picked Vultr based on the storage instance and cost. I started importing the searchcode database into the storage instance. However about 3/4 the way through I received an email from Vultr support saying that I was exceeding the DiskIO of the storage instance using a sustained 125 IOPS. Fair enough, and I would have been willing to throttle it back if I could gain some assurance about the terms of service. Sadly Vultr lived up to their reputation of having poor support and I am yet to hear back. I terminated the instance and started looking again. They do offer dedicated instances and the prices are actually not too bad, but did not have enough disk space for my needs. I still use them for spinning up test stacks as they have a Sydney data centre which for me has lower network latency and offsets the slower creation time.

I realised that the only real option for something like searchcode (which is fully bootstrapped) is that I need as much power as possible and the lowest price. I also don’t mind getting my hands dirty and can deal without the support. Lastly I need to be able to abuse the machine as I see fit and the only way to do that is go dedicated.

Thankfully Hetzer has a very nice server auction house. You can browse through and pick up used servers for a considerable discount over a new order. In addition you don’t have to pay the setup fee. To avoid the database corruption issue I experienced previously I went shopping for a ECC RAM server for the database and quickly found a tidy machine with 32 GB RAM and enough disk space. For the frontend I just picked up the cheapest 32 GB machine I could find which interestingly was similar to my previous frontend machine but with 32 GB of RAM. Lastly I went looking for something to server as the backend and the indexer. I quickly realized that I could combine both the machines into one and save a few dollars. With this saving I was able to overlook the initial setup fee and went for two machines with 32 GB of RAM and 500 GB SSD’s. Since Hetzner cannot spin servers up and down like a cloud provider I hard-coded the details into my fab file for building the stack but otherwise everything deploys as though I was using a cloud provider. Only it costs considerably less and should be much much faster.

searchcode current

The results?

Well as mentioned the previous instances were sitting around a load average of 3.0+ most of the time. The new backend/indexer boxes are sitting at a load average of 0.1+ which is a massive improvement. The database and frontend are similarly loaded. The DNS at this point is still flipping over for some so its not serving all results yet but I cannot imagine the load rising beyond 1.0+ for everything.

With the hardware decisions discussed lets dive into the software starting with the data storage. MySQL has always been my database of choice simply because I am more familiar with it than any other database. I had previously toyed with migrating to Postgresql but decided against it simply because there are other things I should focus my time on that actually provide real value. As such I have stuck with that for the latest searchcode version however one change I did make was to upgrade to 5.7 so I can leverage the native JSON data type. Otherwise the only change was to modify the MySQL config to take advantage of the power of the box as per best practices.

The backend machines have Nginx set to listen to incoming connections from the frontend. They pass requests back to Gunicorn/Django which performs the appropriate action. Where possible the result using Django/Memcached is served directly, if not a request to Sphinx may be made for search results followed by a lookup to the database, or a direct request to the database. Gunicorn is configured to have four worker processes per box. Sphinx is configured using a distributed index with 4 agents running on each box and one box as the master. Memcached is currently configured with 8 GB of RAM for each backend instance but is not pooled together.

The frontend machine is configured using Varnish with 24 GB of the RAM allocated to cache. The remaining 8 GB is deliberately left over for use by OS caching and Nginx. Nginx is the frontend to the whole system providing SSL termination and proxying back to Varnish. I did briefly consider using HAProxy for this role, but since I was already familiar with Nginx and at the scale searchcode currently operates at Nginx was a better choice. If in time there is much greater load moving to HAProxy is something that will be considered.

Whats next? Well the future of at this point is to leverage the new machines to increase the size of the index and make it refresh the code more quickly. I have a few plans on how to do so and will release details in the next update. If you have read this far you are a beast! Thanks for the support and feel free to email with any further questions.

searchcode server released

searchcode server the downloadable self hosted version of is now available. A large amount of work went into the release with a variety of improvements based on feedback from the general beta releases.

searchcode server

searchcode server has a number of advantages over that will eventually be back-ported in. The full list of things to check out is included below,

  • New Single Page Application UI for smooth search experience
  • Ability to split on terms so a search for “url signer” will match “UrlSigner”
  • Massively improved performance 3x in the worst case and 20x in the best
  • Configurable through UI and configuration
  • Spelling suggestion that learns from your code

A few things of note,

  • Java 8 application built using Lucene and Spark Framework
  • Designed to work any server. The test bench server is a netbook using an Intel Atom CPU and searches return in under a second
  • Scales to Gigabytes of code and thousands of repositories
  • Works on Linux, OSX and Windows

Be sure to check it out!

searchcode server
searchcode server
searchcode server

searchcode server

A month or so ago I started collection emails on to determine if there was enough interest in a downloadable version of searchcode. The results were overwhelmingly positive. The email list grew far beyond what I would have expected, and this was in the first month. As such I have been working in this downloadable version of searchcode which will probably be called searchcode server.

Progress has been reasonably straight forward consider that is written using mostly Python and searchcode server is mostly Java. The main reason for choosing Java is that I really wanted searchcode server to be a self contained application which could be downloaded and run without the configuration and setup of additional services.

At present it is surprisingly workable. You can input repositories (git only at this point) to be indexed and after a short amount of time they will be searchable via the main interface. A few screenshots are included at the end of this post for those curious.

There is still time to sign up and be one of the first to receive access. Being on the sign up list will also give you a discount when it is actually released if you need something greater than the community edition. To register your interest use the form below, or visit the searchcode server product page.

This has been released and you can now get the actual product.

Screen Shot 2015-12-29 at 1.04.54 pm

Screen Shot 2015-12-29 at 1.11.30 pm