Interview Maciej Fijalkowski PyPy

As part of my research for “Python for R Users- A Data Science Approach” (Wiley 2016), I came across PyPy ( What is PyPy?

PyPy is a fast, compliant alternative implementation of the Python language (2.7.10 and 3.2.5). It has several advantages and distinct features:

  • Speed: thanks to its Just-in-Time compiler, Python programs often run faster on PyPy.

  • Memory usage: memory-hungry Python programs (several hundreds of MBs or more) might end up taking less space than they do in CPython.

  • Compatibility: PyPy is highly compatible with existing python code. It supports cffi and can run popular python libraries like twisted and django.

  • Stackless: PyPy comes by default with support for stackless mode, providing micro-threads for massive concurrency.

Now R users might remember the debate with Renjin and pqR a few years ago. PyPy is an effort which has been around for some time and they are currently at an interesting phase.

Here is an interview with Maciej Fijalkowski of PyPy

pypy-logo (1)

Ajay Ohr-Why did you create PyPy to serve what need ?

PyPy– I joined pypy in 2006 or 2007, I don’t even remember, but it was about 2 years into the project existence. Shockingly enough, the very first idea was that there will be a python-in-python for educational purposes only. It later occurred to us that we can use the fact that PyPy is written in a high level language and apply various transformations to it, including just-in-time compilation. Overall it was a very roundabout way, but we came to the conclusion that this is the right way to provide a high-performance python virtual machine, after Armins experience writing Psyco, that likely only few people

Ajay Ohri-  Describe the current state of PyPy especially regarding to using NumPy. Can we use it for Pandas, matplotlib,seaborn, scikit-learn, statsmodels in near future. What hinders your progress?

PyPy- We are right now in the state of flux. I’m almost inclined to say “talk to us in a few weeks/months”. I will describe the status right now as well as possible near futures. Right now, we have a custom version of numpy that supports most of the existing numpy and can be used, although it does not pass all the tests. It has a very fast array item access routines, so you can write your algorithms directly in python without looking into custom solutions. It however, does not provide a C API and so does not support anything else from the numeric stack.

We’re considering also supporting the original numpy with CPython C API, which will enable the whole numeric stack with some caveats. Currently, there are ongoing discussions and I can get back to you once this is resolved.

Our main problem is the CPython C API and the dependency of the entire numeric stack on that. It exposes a lot of CPython internals, like reference counting, the exact layout of lists and strings etc. We have a layer that provides some sort of compatibility with that, but we need more work in order to make it more robust and faster. In the case of C API the main hindrance is funding – I wrote a blog post detailing the current situation: We would love to support the entire numeric stack and we will look into ways that make it possible.

Ajay Ohri-A faster more memory efficient Python – will it be useful for analysis of large amounts of numeric data ?

PyPy- Python owes much of it’s success to good integration with the C ecosystem. For years we’ve been told that no one needs a fast Python, because what is necessary to be fast is already in C and we can go away. That has proven to be blatantly false with projects like apache spark embedding python as a way to do computations. There are also a lot of Python programmers and it’s a bit unfair to expect from them to “write all the performance critical parts in C” or any of the other custom languages built around Python, like Cython. I personally think that there is a big place for a faster Python and we’re mostly fulfilling that role, except exactly for the case of integration with numeric libraries that is absolutely crucial for a lot of people. We need to improve that story if we were to fill in that gap completely and while predicting future is hard, we would do our best to support the numeric stack a lot better in the coming months.

Ajay Ohri- What are the day to day challenges you face while working on PyPy? 

PyPy- That’s a tough question. There is no such thing in IT as “day to day challenges with technology” because if it’s really such a hindrance, you can usually automate it away. However, I don’t do only technical work these days, I deal a lot with people asking questions, looking at issues, trying to organize money for PyPy etc. This means that it’s very hard to pinpoint what a day-to-day activity is, let alone what it’s problems are.

The most repeating challenges that we face are how to make sure there is funding for chronically underfunded open source projects and how to explain our unusual architecture to newcomers. The technical issues we are heavily trying to automate away so if it’s a repeating problem, we are going to have more and more infrastructure to deal with it in a more systematic manner.

Ajay Ohri-  You and your highly skilled team could probably make much more money per
hour working for companies in consulting projects, Why devote time to open source coding tools. What is the way we can get more people to donate or  devote time

PyPy- It is a very interesting question, probably exceeding the scope of this interview, but I will try to give it a go anyway. I think by now it’s pretty obvious that Open Source is just a better way to make software, at least as far as infrastructure goes. I can’t think about a single proprietary language platform that’s not tied to a specific architecture. Even Microsoft and .NET are moving slowly towards Open Source, with Apple owning so much of the platform that no one has a say there.

That means that locally, yes, we could very likely make far more money working for some corporations, but globally it’s pretty clear that both our impact and the value we bring is much higher than it would be working for a corporation looking for its short term gains.

Additionally, the problems we are presented to work with are much more interesting than the ones we would likely encounter in the corporate environment. Funding Open Source is a very tricky question here and I think we need to find answers to that.

Everyone uses Open Source software, directly or indirectly and there is enough money made by companies profiting from using it to fund it. How to funnel this money is a problem that we’re trying to solve on a small scale, but would be wonderful to see the solution on a bigger scale.

Ajay Ohri- How can ensure automatic porting of algorithms from languages to Java Python R rather than manually creating packages. I mean if we can have Google Translate for Human languages, what can we do to make automatic translation of code between computer languages

PyPy- It would be very useful, but no one managed to do it well, maybe that means something. However, it’s quite easy to translate between languages naively – without taking into account best practices, more efficient ways of achieving goals etc. There is a whole discussion to be had, but I don’t think I’m going to have much insight into this.


PyPy is a replacement for CPython. It is built using the RPython language that was co-developed with it. The main reason to use it instead of CPython is speed: it runs generally faster

See more here

Understanding Indians and their Politics

I am not speaking of Indian Politicians here. Whatever Rahul Gandhi (or his speechwriter) , the ruling party in the state or the central government has always been a perennial source of bemusement to me, unlike the rest of my fellow Indians who keep fighting wars on Facebook and Social Media. Indeed I am surprised by the complete lack of conversation on politics when I am in North America, and a fellow friend of mine confirmed it, Europeans and Indians do talk more about politics than North Americans. Part of the reason is ideologies are much less pronounced between the extremes of political spectrum and  the general culture is to be polite and avoid controversial debates (which explains lack of politics as a dinner topic in the North American West)

I am speaking of politics as I have seen it practiced in Indian companies, startups and educational institutes. The level of politics is much higher than in USA or Canada, and the rudeness and crudeness is much more. Note I have interacted with people at extremely senior levels  (thanks to my blog and consulting) and junior levels (thanks to my teaching).

Without getting into anecdotal details and impose my projections as the New World Order on you- this is what I feel drives Politics between Ordinary Indians (the ones who never get figured in Newspapers)

  1. Insecurity drives politics- Prosperity and luxury is barely half a generation old. The economic insecurity of success is what drives politics in many institutes and institutions. People think- if someone else succeeds I will not get a slice of the pie. That’s because we all came from a socio-economic status where the pie was so small. How small ? Well when I was a Kid, we had one channel on Television, and there were waiting periods for a car for many years. Telephone was a luxury. Even though new India has many malls, many mobile phones and many luxuries, the trauma of childhood endures and ensures educated Indians use sharp elbows at the workplace to grab a share of the bonus or the pie or the economic success on offering
  2. Mistrust drives politics- Mistrust is driven by the different way Indians treat lying compared to North Americans. What is vilified as lying or cunning is treated as being chalu (smart) or jugaad ( innovative) in dodging questions, giving non-clear answers, or plain untruths. Why give promises you cannot keep. That is the Indian way of doing business. Why do people delay payments for vendors. That is both power politics and part economics. In addition a very slow legal system ensures people reach compromises on their own
  3. Saving Face- A big chunk of energy wasted by Indians is to save face, to avoid saying they failed. Everyone fails and everyone learns from their failures. But few people like to admit to mistakes and failures, and the culture in India is vindictive. Saving face is the number one reason people try to harass other people in workplaces when they are trying to leave. They ignore future relationships for the current need to save Face.
  4. Different Ethics– Some people point out to how people joke in Indian workplaces about women as misogny. That is universal. Men treat women badly in North America and are reigned only by legal system and that society. Some people point to hiring people only along state lines (North India, family members, South Indians, Bengalis, Mallus etc)  as regionalism. Midler forms of that racism exist in the US too. No we just have different ethics here. We treat mediocre old people with respect and treat brilliant young  people with condescension. Protestant ethics are different from the ethics of arguementative Indians

What is the solution? One solution is greater intermingling between people of different countries for Indians to learn about the best way to balance your personal ambitions with your professional needs. I recommend Canadians as the politest people among any country I have seen. Maybe we should invite more Canadians to settle in India rather than the other way around!


Interview PythonAnywhere

As part of my research for “Python for R Users- A Data Science Approach” (Wiley 2016) I am interviewing startups as well as package creators in the Python Data Science Space. Accordingly here is an interview with Giles Thomas, who leads PythonAnywhere, a UK based company that helps makes Python available anywhere thanks to cloud computing.
Ajay- Describe your journey to set up and create Python Anywhere. What were the reasons you chose Python. How has this choice helped you? Describe some usage stats and your core team.

PythonAnyWhere – Well, that’s a long story :-)   There have been a couple of turns along the way…

In 2005 a couple of friends and I decided to start a company to create a new kind of spreadsheet.  We felt that Excel spreadsheets became unmanageable at scale, and a better solution for many use cases would be to create something that integrated a programming language more closely.  There definitely seemed to be a market for it, especially in the financial world.  We looked at the programming languages available, and Python stood out because it was very powerful, but also easy to learn.  The existence of numerical libraries like NumPy/SciPy was also a huge plus point.

So we built our spreadsheet, a desktop application called Resolver One with Python deeply integrated, and released it in 2008.  Unfortunately that coincided with a downturn in our target market of finance, and additionally we discovered that although many people were very keen on the product, there just weren’t enough of them to run a viable business based on it, especially under the desktop “buy a license and use it forever” kind of business model.  Over the following years we tried moving into alternative markets, and tried different approaches to selling it, but eventually we decided we needed to pivot to a different business, based on the knowledge we’d built up while creating Resolver One.

Our first pivot was simply to take the idea of Resolver One, and turn it into a cloud-based application.  This was codenamed “Project Dirigible”, and went live in 2010.  It was a highly-programmable spreadsheet, displayed in a web browser.  One of the most interesting things about it was that you could code the whole recalculation loop in Python — a default empty spreadsheet would contain code that looked something like this:


…so if you wanted to add your own functions, you could just def them above the code, and if you wanted to do something like goal-seeking, you could just put a while loop around the call to therecalculate_formulae function.   You can see (a slightly cut-down version of) Dirigible’s source code here:<>

Dirigible was an excellent product; you could run complex analysis with a spreadsheet-like interface, but you could also (for example) spread calculations over a cluster of servers by calling one spreadsheet from another, kind of like a function call, running multiple spreadsheets in parallel.   And it started getting users, but again, not enough to keep the business going.

So we sat down and looked at how people were using it.  We discovered that for many users, the spreadsheet itself was an irrelevance.  What they wanted was an easy way to run a pre-configured Python distribution from their browser, without setting stuff up, configuring and maintaining machines, and so on.

We pivoted again, rapidly adjusted the code we had, and created PythonAnywhere.  We took a very user-centric attitude for development, keeping up conversations with as many users as possible, implementing the features they asked for (weighted by votes) — a hosted database, websites, cron-style scheduled tasks, and so on.  And that’s what has taken us to where we are today.

Right now, there are four people in the company including myself.  We’re based in Clerkenwell, in London (just up the road from the “Silicon Roundabout” area around Old Street which is London’s tech hub).  We have about 130,000 users, ranging from hobbyists playing around with ideas to data analysts, commercial websites, and startups.  Between them they’ve created about 50,000 websites, and started over 2 million in-browser consoles.  We provide the “Try Python now” in-browser console on, and also a popular “Try IPython” page for people who want to try it out as an alternative Python command-line.


Ajay- What are some of the ways your platform is used especially in data science? How does using Python Anywhere help with setting up data science

PythonAnywhere- That’s hard for us to say.  We provide a platform, and our users decide how to use it.  Data scientists tend to know more about what they’re doing than website creators, so they tend to talk to us less…


3) How does Python Anywhere facilitate teaching coding. Name some eamples or user feedback on using your platform for education

It’s hard for teachers to get all of their students set up with a working Python environment.  One person who does training for a living told us that in a five-day Python course, he can spend the first day simply getting Python and all of the appropriate packages installed on people’s laptops.  Django Girls have a special multi-hour “install session” the evening before each of their one-day courses just to get enough basic stuff installed to do their web development tutorial.

So having a site where teachers and trainers can just tell their students to sign up, and then know that everyone has a working development environment in a known state is a huge plus.

We also support console sharing; if you’re working in an in-browser Python console and have a question about something you’re seeing, and your teacher can’t easily come and look over your shoulder, it’s useful to be able to share the console with them so that they can see it in their own browser, and help you out.

Recently, we’ve started specifically adding extra features for teachers and students — for example, a student can designate another user as their teacher, which gives the teacher access to all of their consoles and their files, so that they can — for example — help out with problems, collect homework assignments, and that kind of thing.  More features along those lines are coming.

Finally (and perhaps less relevantly for your readers) people who are teaching website development love the way that it’s easy to deploy a website on PythonAnywhere.   A webdev tutorial that ends with a website running on someone’s laptop is inherently unsatisfactory.   If it’s a website, it should be online!   But teaching a beginner web developer how to configure Apache/nginx, mod_wsgi/uWSGI, and how to secure a machine in the cloud, and so on, is a huge deal and better avoided if possible.

In terms of numbers, it’s hard to say how many people are using us for education, because we offer cut-down free accounts and some courses just use them (we can sometimes spot those when a bunch of people sign up for free accounts with email addresses on the same .edu domain, but often we just can’t tell).  But we do know that there are about 2,000 students using our new education features, and it’s growing about 25% month-on-month.


Ajay- You give ipython and python consoles. Any plans to feature Jupyter or Beaker Notebook.

PythonAnywhere- Absolutely — Jupyter is in private beta at the moment.  If you’d like me to add you, just let me know the name of a PythonAnywhere account.


Ajay- How is using Python Anywhere a superior user experience than just taking a VM on Amazon AWS and doing the installs themself

PythonAnywhere- Well, firstly you don’t have to do the installs yourself :-)   Installing Python and its dependencies is a bit of a pain.  Perhaps more importantly, maintaining everything is a huge pain.  Security fixes are constantly being made, and you have to keep up-to-date with them to avoid getting hacked.

Additionally, there’s server size.  We run on extra-large Amazon instances, and you can pay for as much or as little CPU seconds a day as you want, which makes it easier to scale up and down.


Ajay- What are your views on using Docker for Python.  Do you see Docker usage increasing faster? What are some of the disadvantages of using it.

PythonAnywhere- We’re using Docker internally for a subset of our in-browser consoles, and are gradually rolling it out to more of them as we discover bottlenecks and errors in our own code that uses it.

It’s an excellent way of sandboxing executable code; we’re using it to replace the sandboxing code we’d written ourselves, and it seems to be superior.  We think that in the future we may well move to a model where every console, every Jupyterhub kernel, every scheduled task, and every website worker process on PythonAnywhere runs in its own Docker container.

We are, however, also tracking alternatives with great interest.  Docker is getting quite large, and adding features that we don’t need (possibly at the expense of performance or even security).   rkt from CoreOS looks like it might be worth considering as an alternative at some point.

For more on PythonAnywhere see and try out their free plan to test Python in the cloud. You can also email them at

The planet is fine. The polar bears are fucked.

What has George Carlin got to do with Climate Change.  Well apparently plenty of vision came from Carlin. Those days we used to call Climate Change as Global Warming. The Ozone layer was a separate problem.

To hack climate change you may want to hack the way people think. The way people think is the way the climate ended up changing itself.

See this at NYTIMES Greeland is melting away. “Every scientist, Dr. Smith said, is keenly aware that the research costs “a tremendous amount of taxpayer money.”


Rather the spend a lot of money to exotic places in Greenland to collect data, maybe we can use the Internet of Things to just keep some chips to collect data and transmit it via the Internet.


Newer forms of climate change data might need newer forms of mathematics rather than brute forcing older mathematical techniques. It might need newer languages in terms of computer software. There is a lot of carbon locked up in ice and it will increase exponentially not linearly. We dont even have a proper way to forecast yet.

Rising temperatures would also mean newer species maybe at a smaller microbial or bacterial level. There will be change. Summer is coming. or maybe a newer Ice Age is coming. Who knows. We were too busy spending money on Christmas trees. We forgot to do the math.

The planet will be fine. The polar bears are fucked. The people … the people… Oh the people. (or read it here)


You got people like this around you? Country’s full of ’em now. People walkin’ around all day long every minute of the day, worried about everything. Worried about the air, worried about the water, worried about the soil. Worried about insecticides, pesticides, food additives, carcinogens, worried about radon gas, worried about asbestos, worried about saving endangered species.

Lemme tell ya bout endangered species, awright? Saving endangered species is just one more arrogant attempt by humans to control Nature. It’s arrogant meddling. It’s what got us in trouble in the first place. Doesn’t anybody understand that? Interfering with Nature. Over 90 percent, over, way over 90 percent, of the species that have ever lived on this planet, ever lived, are gone. Wooosh! They’re extinct. We didn’t kill them all. They just disappeared. That’s what nature does. They disappear these days at the rate of 25 a day—and I mean regardless of our behavior. Irrespective of how we act on this planet, 25 species that were here today will be gone tomorrow. Let them go gracefully. Leave Nature alone. Haven’t we done enough? We’re so self-important, so self-important. Everybody’s gonna save something now. Save the trees, save the bees, save the whales, save those snails. And the greatest arrogance of all, save the planet. What? Are these fucking people kidding me? Save the planet? We don’t even know how to take care of ourselves yet. We haven’t learned to care for one another—we’re gonna save the fuckin’ planet? I’m gettin’ tired of that shit. Tired of that shit. Tired.

I’m tired of fuckin’ Earth Day, I’m tired of these self-righteous environmentalists, these white bourgeoise liberals who think the only thing wrong with this country is there aren’t enough bicycle paths. People trying to make the world safe for their Volvos. Besides, environmentalist don’t give a shit about the planet, they don’t care about the planet, not in the abstract they don’t, not in the abstract they don’t. You know what they’re interested in? A clean place to live. Their own habitat. They’re worried that someday in the future they might be personally inconvenienced. Narrow, unenlightened self-interest doesn’t impress me. Besides, there is nothing wrong with the planet, nothing wrong with the planet. The planet is fine. The people are fucked. Difference. Difference. The planet is fine. Compared to the people, the planet is doin’ great! It’s been here four and a half billion years. Did you ever think about the arithmetic? The planet has been here four and a half billion years. We’ve been here, what? A hundred thousand? Maybe two hundred thousand and we’ve only been engaged in heavy industry for a little over two hundred years. Two hundred years versus four and a half billion. And we have the conceit to think that somehow we’re a threat? That somehow we’re gonna put in jeopardy this beautiful little blue-green ball that’s just a floatin’ around the sun? The planet has been through a lot worse than us. Been through all kinds of things worse than us. Been through earthquakes, volcanoes, plate tectonics, continental drift, solar flares, sunspots, magnetic storms, the magnetic reversal of the poles, hundreds of thousands of years of bombardment by comets and asteroids, and meteors, world-wide floods, tidal waves, world-wide fires, erosion, cosmic rays, recurring ice ages, and we think some plastic bags and some aluminum cans are going to make a difference?

The planet isn’t going anywhere. We are! We’re goin’ away. Pack your shit, Folks, we’re goin’ away. We won’t leave much of a trace either, thank god for that. Maybe a little styrofoam, maybe, little styrofoam. Planet’ll be here and we’ll be long gone. Just another failed mutation. Just another closed-end biological mistake, an evolutionary cul de sac. The planet will shake us off like a bad case of fleas, a surface nuisance. You wanna know how the planet’s doin’? Ask those people at Pompeii, who were frozen into position from volcanic ash. How the planet’s doin’. Wanna know if the planet’s alright, ask those people in Mexico City or Armenia, or a hundred other places buried under thousands of tons of earthquake rubble if they feel like a threat to the planet this week. How about those people in Kilauea, Hawaii who built their homes right next to an active volcano and then wonder why they have lava in the living room. The planet will be here for a long, long, long time after we’re gone and it will heal itself, it will cleanse itself ’cuz that’s what it does. It’s a self-correcting system. The air and the water will recover, the earth will be renewed, and if it’s true that plastic is not degradable well, the planet will simply incorporate plastic into a new paradigm: the earth plus plastic. The earth doesn’t share our prejudice towards plastic. Plastic came out of the earth. The earth probably sees plastic as just another one of its children. Could be the only reason the earth allows us to be spawned from it in the first place: it wanted plastic for itself. Didn’t know how to make it, needed us. Could be the answer to our age-old philosophical question, “Why are we here?” “Plastic, assholes.”

So, so, the plastic is here, our job is done, we can be phased out now. And I think that’s really started already, don’t you? I mean, to be fair, the planet probably sees us as a mild threat, something to be dealt with, but I’m sure the planet will defend itself in the manner of a large organism like a bee hive or an ant colony can muster a defense. I’m sure the planet will think of something. What would you do, if you were the planet trying to defend against this pesky, troublesome species? Let’s see, what might, viruses, viruses might be good, they seem vulnerable to viruses. And, viruses are tricky, always mutating and forming new strains whenever a vaccine is developed. Perhaps this first virus could be one that compromises the immune system in these creatures. Perhaps a human immuno deficiency virus making them vulnerable to all sorts of other diseases and infections that might come along, and maybe it could be spread sexually, making them a little reluctant to engage in the act of reproduction.

Well, that’s a poetic note. And it’s a start. But I can dream, can’t I? I don’t worry about the little things, bees, trees, whales, snails. I think we’re part of a greater wisdom than we’ll ever understand, a higher order, call it what you want. You know what I call it? The Big Electron. The Big Electron. Woooohhhh, woooohhhh, woooohhhh. It doesn’t punish, it doesn’t reward, it doesn’t judge at all. It just is, and so are we, for a little while. Thanks for being here with me for a little while tonight.

Smart people Stupid things

Smart people do stupid things. Do stupid people come up with smart ideas too. Ideas that can make a billion unicorns out of me-too ideas.

Smart people doing stupid things is a thread on Quora with 600,000 views and 100+ answers. Clearly there is a lot of public examination on smart and stupid stuff. Of course smart people say stupid things sometimes. There is an Internet of Things and there is an Internet of Stupid Things.

Intelligence is a fascinating concept. All humans are supposed to be equal, but clearly some people are intelligent in some things. A few are intelligent in many things compared to the average. How do societies, governments and venture capitalists fund smart people to do smart things.

Business Insider, the Jeff Bezos funded web startup was kind enough to scrape, aggregate, curate, collect a few answers. I am returning the kindness to put the bullet points here. Artists steal. Great artists get inspired.

Stupid Things done by Smart People

  1. Overthinking, overplanning and underdoing
  2. Follow the herd mentality
  3. Risk Averseness
  4. Giving up too soon
  5. Undervaluing social skills, networking and social bonhomie
  6. Not recognizing their own cognitive biases. I scraped some stuff on that shit here. Cognitive bias deals with bad decision making due to biases.Cognitive biases are tendencies to think in certain ways that can lead to systematic deviations from a standard of rationality or good judgment, and are often studied in psychology and behavioral economics.Among the “cold” biases,
    • some involve a decision or judgement being affected by irrelevant information (for example the framing effect where the same problem receives different responses depending on how it is described; or the distinction bias where choices presented together have different outcomes than those presented separately)
    • others give excessive weight to an unimportant but salient feature of the problem (e.g.,anchoring)
  7. Ego. Life is a bitch. Karma is a bitch. Ego is the dumbest bitch. There I said it.
  8. Equating education with intelligence ( a cognitive bias I think) . But the school you went to (Stanford) or dropped out affects people more than it should. Just saying.
  9. Underestimating the competition
  10. Getting wrapped in their own theoretical world and failing to see reality. Sometimes the basic data on the assumptions on the product, produce, process, people or profitability has moved. Reality is a dose that is usually externally administered. Smart people should see reality on their own faster.

What is the stupidest thing I did? Losing my temper. Thats never smart. Did you ever lose yours?

 Intelligence as a demand- supply problem.

Can we measure intelligence as a statistical quantity. IF the world had a few geniuses (Einstein, Fermi) when the population was 1 billion, does it mean the number of geniuses has increased by six times. We could do it for bacteria so why not humans?

How would IQ scores be distributed for different countries and races. Ooh, now we are asking scary uncomfortable questions.


How do we increase the supply of educated geniuses in a country or location or race? Don’t say MOOC or Coursera, please. Intelligence is not that easy. Is it easy comrade?




Things I can change and Things I cant change

In the mind of a weekend hacker run a few thoughts too many:

There are some things I cant change even though I wish I could change them because quite clearly I would make a tonne of money more.

Trusting the instincts of others to go north when my instincts tell me to go south. Keeping my mouth and my bloggy fingers shut for things I think I are dishonest. Hanging out with people I wont really like or respect any more. Stop writing technical books and start making more products to mmm sell more soap stars.

I cant change that at all. What can I change? Oh that. Someday I am going to write a piece of code, nothing big , just a few k lines to make the change.

I  can change the world by writing a beautiful piece of code.