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• FFMPEG command runs in terminal but not by subprocess

  1er septembre 2022, par Basilique

  I am trying to run a bash command using the subprocess module from within python 3.10.

  


  The bash command is :

  


  ffmpeg -framerate 1 -pattern_type glob -i '*.png' -c:v libx264 -pix_fmt yuv420p -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" out.mp4


  


  In terminal the command runs fine. Here is the output :

  


  ffmpeg version 4.2.7-0ubuntu0.1 Copyright (c) 2000-2022 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
  configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Input #0, image2, from '*.png':
  Duration: 00:16:39.00, start: 0.000000, bitrate: N/A
    Stream #0:0: Video: png, rgba(pc), 895x332 [SAR 3937:3937 DAR 895:332], 1 fps, 1 tbr, 1 tbn, 1 tbc
Stream mapping:
  Stream #0:0 -> #0:0 (png (native) -> h264 (libx264))
Press [q] to stop, [?] for help
[libx264 @ 0x55726ab95d00] using SAR=1/1
[libx264 @ 0x55726ab95d00] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512
[libx264 @ 0x55726ab95d00] profile High, level 2.2
[libx264 @ 0x55726ab95d00] 264 - core 155 r2917 0a84d98 - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=10 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=1 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'out.mp4':
  Metadata:
    encoder         : Lavf58.29.100
    Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 894x332 [SAR 1:1 DAR 447:166], q=-1--1, 1 fps, 16384 tbn, 1 tbc
    Metadata:
      encoder         : Lavc58.54.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
frame=  173 fps=0.0 q=17.0 size=     512kB time=00:01:56.00 bitrate=  36.2kbits/frame=  351 fps=350 q=17.0 size=    1536kB time=00:04:54.00 bitrate=  42.8kbits/frame=  517 fps=343 q=17.0 size=    2560kB time=00:07:40.00 bitrate=  45.6kbits/frame=  725 fps=361 q=17.0 size=    3328kB time=00:11:08.00 bitrate=  40.8kbits/frame=  913 fps=364 q=17.0 size=    4352kB time=00:14:16.00 bitrate=  41.6kbits/frame=  999 fps=361 q=-1.0 Lsize=    4986kB time=00:16:36.00 bitrate=  41.0kbits/s speed= 360x    
video:4974kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.241361%
[libx264 @ 0x55726ab95d00] frame I:4     Avg QP: 6.12  size: 24072
[libx264 @ 0x55726ab95d00] frame P:346   Avg QP:12.94  size:  5708
[libx264 @ 0x55726ab95d00] frame B:649   Avg QP:18.19  size:  4655
[libx264 @ 0x55726ab95d00] consecutive B-frames:  5.8% 16.0% 20.1% 58.1%
[libx264 @ 0x55726ab95d00] mb I  I16..4: 59.1% 10.6% 30.4%
[libx264 @ 0x55726ab95d00] mb P  I16..4:  5.6%  0.6%  2.2%  P16..4: 10.5%  4.3%  2.3%  0.0%  0.0%    skip:74.5%
[libx264 @ 0x55726ab95d00] mb B  I16..4:  2.2%  0.1%  1.7%  B16..8: 16.9%  4.8%  1.6%  direct: 1.1%  skip:71.5%  L0:50.9% L1:45.2% BI: 3.9%
[libx264 @ 0x55726ab95d00] 8x8 transform intra:5.9% inter:10.4%
[libx264 @ 0x55726ab95d00] coded y,uvDC,uvAC intra: 20.1% 18.3% 17.3% inter: 4.7% 4.7% 4.6%
[libx264 @ 0x55726ab95d00] i16 v,h,dc,p: 66% 33%  1%  0%
[libx264 @ 0x55726ab95d00] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 18%  8% 73%  0%  0%  0%  0%  0%  0%
[libx264 @ 0x55726ab95d00] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 23% 31% 31%  2%  3%  2%  4%  2%  3%
[libx264 @ 0x55726ab95d00] i8c dc,h,v,p: 73% 23%  3%  0%
[libx264 @ 0x55726ab95d00] Weighted P-Frames: Y:0.0% UV:0.0%
[libx264 @ 0x55726ab95d00] ref P L0: 57.2%  1.5% 24.3% 17.0%
[libx264 @ 0x55726ab95d00] ref B L0: 69.6% 24.8%  5.6%
[libx264 @ 0x55726ab95d00] ref B L1: 92.4%  7.6%
[libx264 @ 0x55726ab95d00] kb/s:40.78


  


  In my python script I tried the following solutions :

  


  video_cmd = """ffmpeg -framerate 1 -pattern_type glob -i '*.png' -c:v libx264 -pix_fmt yuv420p -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" out.mp4"""

subprocess.run(shlex.split(video_cmd), shell=False, cwd=path_viz, stderr=subprocess.STDOUT, check=True, text=False)

subprocess.run(video_cmd, shell=True, cwd=path_viz, stderr=subprocess.STDOUT, check=True, text=False)


  


  as well as the solution proposed for this similar question

  


  subprocess.Popen(video_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)


  


  None of them worked. Apparently, the right command is run (output of the check_out function) :

  


  Command 'ffmpeg -y -framerate 1 -pattern_type glob -i '*.png' -c:v libx264 -pix_fmt yuv420p -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" out.mp4' returned non-zero exit status 1.


  


  the first part of the job (up to Stream mapping:) is done also correctly :

  


  fmpeg version 4.3 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7.3.0 (crosstool-NG 1.23.0.449-a04d0)
  configuration: --prefix=/home/rsghazanfari/anaconda3/envs/_cuda --cc=/opt/conda/conda-bld/ffmpeg_1597178665428/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc --disable-doc --disable-openssl --enable-avresample --enable-gnutls --enable-hardcoded-tables --enable-libfreetype --enable-libopenh264 --enable-pic --enable-pthreads --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libmp3lame
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
Input #0, image2, from '*.png':
  Duration: 00:16:39.00, start: 0.000000, bitrate: N/A
    Stream #0:0: Video: png, rgba(pc), 895x332 [SAR 3937:3937 DAR 895:332], 1 fps, 1 tbr, 1 tbn, 1 tbc


  


  but it then pops up the following error :

  


  Unknown encoder &#x27;libx264&#x27;&#xA;Traceback (most recent call last):&#xA;  File "/home/rsgh/anaconda3/envs/_cuda/lib/python3.10/code.py", line 90, in runcode&#xA;    exec(code, self.locals)&#xA;  File "<input />", line 1, in <module>&#xA;  File "/home/rsgh/anaconda3/envs/_cuda/lib/python3.10/subprocess.py", line 524, in run&#xA;    raise CalledProcessError(retcode, process.args,&#xA;&#xA;subprocess.CalledProcessError: Command &#x27;ffmpeg -y -framerate 1 -pattern_type glob -i &#x27;*.png&#x27; -c:v libx264 -pix_fmt yuv420p -vf "crop=trunc(iw/2)*2:trunc(ih/2)*2" out.mp4&#x27; returned non-zero exit status 1.&#xA;</module>

  


  Any ideas of why this error is produced in python while in terminal it runs fine ? Thank you in advance.

  


  PS : ffmpeg -version outputs :

  


  ffmpeg version 4.2.7-0ubuntu0.1 Copyright (c) 2000-2022 the FFmpeg developers
built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
libavutil      56. 31.100 / 56. 31.100
libavcodec     58. 54.100 / 58. 54.100
libavformat    58. 29.100 / 58. 29.100
libavdevice    58.  8.100 / 58.  8.100
libavfilter     7. 57.100 /  7. 57.100
libavresample   4.  0.  0 /  4.  0.  0
libswscale      5.  5.100 /  5.  5.100
libswresample   3.  5.100 /  3.  5.100
libpostproc    55.  5.100 / 55.  5.100


  


  ubuntu version :

  


  Distributor ID: Ubuntu
Description:    Ubuntu 20.04.4 LTS
Release:    20.04
Codename:   focal


  


• Data Privacy in Business : A Risk Leading to Major Opportunities

  9 août 2022, par Erin — Privacy

  Data privacy in business is a contentious issue. 

  Claims that “big data is the new oil of the digital economy” and strong links between “data-driven personalisation and customer experience” encourage leaders to set up massive data collection programmes.

  However, many of these conversations downplay the magnitude of security, compliance and ethical risks companies face when betting too much on customer data collection. 

  In this post, we discuss the double-edged nature of privacy issues in business — the risk-ridden and the opportunity-driven. ​​

  3 Major Risks of Ignoring Data Privacy in Business

  As the old adage goes : Just because everyone else is doing it doesn’t make it right.

  Easy data accessibility and ubiquity of analytics tools make data consumer collection and processing sound like a “given”. But the decision to do so opens your business to a spectrum of risks. 

  1. Compliance and Legal Risks 

  Data collection and customer privacy are protected by a host of international laws including GDPR, CCPA, and regional regulations. Only 15% of countries (mostly developing ones) don’t have dedicated laws for protecting consumer privacy. 

  

  Global legislature includes provisions on : 

  • Collectible data types
  • Allowed uses of obtained data 
  • Consent to data collection and online tracking 
  • Rights to request data removal 

  Personally identifiable information (PII) processing is prohibited or strictly regulated in most jurisdictions. Yet businesses repeatedly circumnavigate existing rules and break them on occasion.

  In Australia, for example, only 2% of brands use logos, icons or messages to transparently call out online tracking, data sharing or other specific uses of data at the sign-up stage. In Europe, around half of small businesses are still not fully GDPR-compliant — and Big Tech companies like Google, Amazon and Facebook can’t get a grip on their data collection practices even when pressed with horrendous fines. 

  Although the media mostly reports on compliance fines for “big names”, smaller businesses are increasingly receiving more scrutiny. 

  As Max Schrems, an Austrian privacy activist and founder of noyb NGO, explained in a Matomo webinar :

  “In Austria, my home country, there are a lot of €5,000 fines going out there as well [to smaller businesses]. Most of the time, they are just not reported. They just happen below the surface. [GDPR fines] are already a reality.”​

  In April 2022, the EU Court of Justice ruled that consumer groups can autonomously sue businesses for breaches of data protection — and nonprofit organisations like noyb enable more people to do so. 

  Finally, new data privacy legislation is underway across the globe. In the US, Colorado, Connecticut, Virginia and Utah have data protection acts at different stages of approval. South African authorities are working on the Protection of Personal Information Act (POPI) act and Brazil is working on a local General Data Protection Law (LGPD).

  Re-thinking your stance on user privacy and data protection now can significantly reduce the compliance burden in the future. 

  2. Security Risks 

  Data collection also mandates data protection for businesses. Yet, many organisations focus on the former and forget about the latter. 

  Lenient attitudes to consumer data protection resulted in a major spike in data breaches.

  Check Point research found that cyberattacks increased 50% year-over-year, with each organisation facing 925 cyberattacks per week globally.

  Many of these attacks end up being successful due to poor data security in place. As a result, billions of stolen consumer records become publicly available or get sold on dark web marketplaces.

  What’s even more troublesome is that stolen consumer records are often purchased by marketing firms or companies, specialising in spam campaigns. Buyers can also use stolen emails to distribute malware, stage phishing and other social engineering attacks – and harvest even more data for sale. 

  One business’s negligence creates a snowball effect of negative changes down the line with customers carrying the brunt of it all. 

  In 2020, hackers successfully targeted a Finnish psychotherapy practice. They managed to steal hundreds of patient records — and then demanded a ransom both from the firm and its patients for not exposing information about their mental health issues. Many patients refused to pay hackers and some 300 records ended up being posted online as Associated Press reported.

  Not only did the practice have to deal with the cyber-breach aftermath, but it also faced vocal regulatory and patient criticisms for failing to properly protect such sensitive information.

  Security negligence can carry both direct (heavy data breach fines) and indirect losses in the form of reputational damages. An overwhelming 90% of consumers say they wouldn’t buy from a business if it doesn’t adequately protect their data. This brings us to the last point. 

  3. Reputational Risks 

  Trust is the new currency. Data negligence and consumer privacy violations are the two fastest ways to lose it. 

  Globally, consumers are concerned about how businesses collect, use, and protect their data. 

  

  • According to Forrester, 47% of UK adults actively limit the amount of data they share with websites and apps. 49% of Italians express willingness to ask companies to delete their personal data. 36% of Germans use privacy and security tools to minimise online tracking of their activities. 
  • A GDMA survey also notes that globally, 82% of consumers want more control over their personal information, shared with companies. 77% also expect brands to be transparent about how their data is collected and used. 

  When businesses fail to hold their end of the bargain — collect just the right amount of data and use it with integrity — consumers are fast to cut ties. 

  Once the information about privacy violations becomes public, companies lose : 

  • Brand equity 
  • Market share 
  • Competitive positioning 

  An AON report estimates that post-data breach companies can lose as much as 25% of their initial value. In some cases, the losses can be even higher. 

  In 2015, British telecom TalkTalk suffered from a major data breach. Over 150,000 customer records were stolen by hackers. To contain the issue, TalkTalk had to throw between $60-$70 million into containment efforts. Still, they lost over 100,000 customers in a matter of months and one-third of their company value, equivalent to $1.4 billion, by the end of the year. 

  Fresher data from Infosys gives the following maximum cost estimates of brand damage, companies could experience after a data breach (accidental or malicious).

  

  3 Major Advantages of Privacy in Business 

  Despite all the industry mishaps, a reassuring 77% of CEOs now recognise that their companies must fundamentally change their approaches to customer engagement, in particular when it comes to ensuring data privacy. 

  Many organisations take proactive steps to cultivate a privacy-centred culture and implement transparent data collection policies. 

  Here’s why gaining the “privacy advantage” pays off.

  1. Market Competitiveness 

  There’s a reason why privacy-focused companies are booming. 

  Consumers’ mounting concerns and frustrations over the lack of online privacy, prompt many to look for alternative privacy-centred products and services. 

  The following B2C and B2B products are moving from the industry margins to the mainstream : 

  • Private search engines (Duckduckgo)
  • Password managers (1password, Dashlane)
  • Online identity networks (id.me)
  • Web analytics solutions (Matomo) 
  • And secure messaging apps (Signal) among others 

  Across the board, consumers express greater trust towards companies, protective of their privacy : 

  

  And as we well know : trust translates to higher engagement, loyalty, and – ultimately revenue. 

  By embedding privacy into the core of your product, you give users more reasons to select, stay and support your business. 

  2. Higher Operational Efficiency

  Customer data protection isn’t just a policy – it’s a culture of collecting “just enough” data, protecting it and using it responsibly. 

  Sadly, that’s the area where most organisations trail behind. At present, some 90% of businesses admit to having amassed massive data silos. 

  Siloed data is expensive to maintain and operationalise. Moreover, when left unattended, it can evolve into a pressing compliance issue. 

  A recently leaked document from Facebook says the company has no idea where all of its first-party, third-party and sensitive categories data goes or how it is processed. Because of this, Facebook struggles to achieve GDPR compliance and remains under regulatory pressure. 

  Similarly, Google Analytics is riddled with privacy issues. Other company products were found to be collecting and operationalising consumer data without users’ knowledge or consent. Again, this creates valid grounds for regulatory investigations. 

  Smaller companies have a better chance of making things right at the onset. 

  By curbing customer data collection, you can : 

  • Reduce data hosting and Cloud computation costs (aka trim your Cloud bill) 
  • Improve data security practices (since you would have fewer assets to protect) 
  • Make your staff more productive by consolidating essential data and making it easy and safe to access

  Privacy-mindful companies also have an easier time when it comes to compliance and can meet new data regulations faster. 

  3. Better Marketing Campaigns 

  The biggest counter-argument to reducing customer data collection is marketing. 

  How can we effectively sell our products if we know nothing about our customers ? – your team might be asking. 

  This might sound counterintuitive, but minimising data collection and usage can lead to better marketing outcomes. 

  Limiting the types of data that can be used encourages your people to become more creative and productive by focusing on fewer metrics that are more important.

  Think of it this way : Every other business uses the same targeting parameters on Facebook or Google for running paid ad campaigns on Facebook. As a result, we see ads everywhere — and people grow unresponsive to them or choose to limit exposure by using ad blocking software, private browsers and VPNs. Your ad budgets get wasted on chasing mirage metrics instead of actual prospects. 

  Case in point : In 2017 Marc Pritchard of Procter & Gamble decided to first cut the company’s digital advertising budget by 6% (or $200 million). Unilever made an even bolder move and reduced its ad budget by 30% in 2018. 

  Guess what happened ?

  P&G saw a 7.5% increase in organic sales and Unilever had a 3.8% gain as HBR reports. So how come both companies became more successful by spending less on advertising ? 

  They found that overexposure to online ads led to diminishing returns and annoyances among loyal customers. By minimising ad exposure and adopting alternative marketing strategies, the two companies managed to market better to new and existing customers. 

  The takeaway : There are more ways to engage consumers aside from pestering them with repetitive retargeting messages or creepy personalisation. 

  You can collect first-party data with consent to incrementally improve your product — and educate them on the benefits of your solution in transparent terms.

  Final Thoughts 

  The definitive advantage of privacy is consumers’ trust. 

  You can’t buy it, you can’t fake it, you can only cultivate it by aligning your external appearances with internal practices. 

  Because when you fail to address privacy internally, your mishaps will quickly become apparent either as social media call-outs or worse — as a security incident, a data breach or a legal investigation. 

  By choosing to treat consumer data with respect, you build an extra layer of protection around your business, plus draw in some banging benefits too. 

  Get one step closer to becoming a privacy-centred company by choosing Matomo as your web analytics solution. We offer robust privacy controls for ensuring ethical, compliant, privacy-friendly and secure website tracking. 

• Matomo Celebrates 15 Years of Building an Open-Source & Transparent Web Analytics Solution

  30 juin 2022, par Matthieu Aubry — About, Community
  &lt;script type=&quot;text/javascript&quot;&gt;<br />
       if ('function' === typeof window.playMatomoVideo){<br />
       window.playMatomoVideo(&quot;brand&quot;, &quot;#brand&quot;)<br />
       } else {<br />
       document.addEventListener(&quot;DOMContentLoaded&quot;, function() { window.playMatomoVideo(&quot;brand&quot;, &quot;#brand&quot;); });<br />
       }<br />
  &lt;/script&gt;

  Fifteen years ago, I realised that people (myself included) were increasingly integrating the internet into their everyday lives, and it was clear that it would only expand in the future. It was an exciting new world, but the amount of personal data shared online, level of tracking and lack of security was a growing concern. Google Analytics was just launched then and was already gaining huge traction – so data from millions of websites started flowing into Google’s database, creating what was then the biggest centralised database about people worldwide and their actions online.

  So as a young engineering student, I decided we needed to build an open source and transparent solution that could help make the internet more secure and private while still providing organisations with powerful insights. I aimed to create a win-win solution for businesses and their digital consumers.

  And in 2007, I started developing Matomo with the help from Scott Switzer and Jennifer Langdon (who offered me an internship and support).   

  All thanks to the Matomo Community

  We have reached significant milestones and made major changes over the last 15 years, but we wouldn’t be where we are today without the Matomo Community.

  So I would like to celebrate and thank the hundreds of volunteer developers who have donated their time to develop Matomo, the thousands of contributors who provided feedback to improve Matomo, the countless supportive forum members, our passionate team of 40 at Matomo, the numerous translators who have translated Matomo and the 1.5 million websites that choose Matomo as their analytics platform.

  

  Matomo has been a community effort built on the shoulders of many, and we will continue to work for you. 

  So let’s look at some milestones we have achieved over the last 15 years.

  Looking back on milestones in our timeline

  2007

  • Birth of Matomo
  • First alpha version released

  2008

  • Release first public 0.1.0 version

  2009

  • 50,000 websites use Matomo

  2010

  • Matomo first stable 1.0.0 released
  • Mobile app launched

  2011

  • Released Ecommerce Analytics, Custom Variables, First Party Cookies

  • Released Privacy control features (first of many privacy features to come !)

  2012

  • Released Log Analytics feature
  • 1 Million Downloads !
  • 300,000 websites worldwide use Matomo

  2013

  • Matomo is now available in 50 languages !
  • Matomo brand redesign

  2016

  • Released Roll-Up Reporting Premium Feature, Users Flow Premium Feature, White Label Premium Feature, A/B Testing Premium Feature, Media Analytics Premium Feature, Funnels Premium Feature and Activity Log Premium Feature 
  • On-Premise Premium Plugins now available on the Marketplace

  2017

  • Launched Matomo Cloud service 
  • Released Multi Channel Conversion Attribution Premium Feature, Custom Reports Premium Feature, Login Saml Premium Feature, WooCommerceAnalytics Premium Feature and Heatmap & Session Recording Premium Feature 

  2018

  • Piwik renamed to Matomo
  • New Matomo logo and Matomo.org website re-launch
  • Launch of Matomo Tag Manager
  • 10,000 stars on Github
  • GDPR comes into effect, and Matomo released new product features and published several new guides
  • 17 Matomo features videos published online
  • Reached thousands of paying customers, making the project sustainable and financially independent

  2019

  • 700,000 websites worldwide use Matomo
  • Google Analytics importer released

  2020

  • Matomo For WordPress goes live on the WP Marketplace !
  • Released Paid Advertising Performance Premium feature
  • 100 million On-Premise Plugins downloads on the marketplace (since the beginning)

  2021

  • 1,000,000 websites worldwide use Matomo
  • including 30,000 active Matomo for WordPress installations
  • Released SEO Web Vitals, Advertising Conversion Export and Tracking Spam Prevention feature

  2022

  • Released WP Statistics to Matomo importer

  Our efforts continue

  While we’ve seen incredible growth over the years, our work doesn’t stop there. In fact, we’re only just getting started.

  Today over 55% of the internet continues to use privacy-threatening web analytics solutions, while 1.5% uses Matomo. So there are still great strides to be made to create a more private internet, and joining the Matomo Community is one way to support this movement.

  There are many ways to get involved too, such as :

  • Submitting feature requests
  • Developing for Matomo 
  • Leaving Matomo a review on sites like Capterra, TrustRadius, G2 Crowd, alternativeTo, SaaSworthy, Siftery, Open Hub
  • Translating Matomo
  • Joining our Security Bug Bounty Programme
  • Sharing Matomo with your peers
  • Talking about Matomo on social platforms

  So what comes next for Matomo ?

  The future of Matomo is approachable, powerful and flexible. We’re strengthening the customers’ voice, expanding our resources internally (we’re continuously hiring !) and conducting rigorous customer research to craft a tool that balances usability and functionality.

  I look forward to the next 15 years and seeing what the future holds for Matomo and our community.