
In this context, _giving_ is primarily about giving money to non-profits and charity orgs.

<div class="mb-4"></div>

I'd like to avoid this essay from sounding like a humblebrag. If it ends up sounding like that, I'll bite the bullet for goodness's sake (uh, pun intended?).

Instead, this is an _invitation_ to give, and a look into my internal thought process, which I will concede [might not be completely internally consistent](https://www.are.na/block/7639528), but at least it gives me _meaning_.

Now that we have the meta out of the way...

## Ways to justify not giving (at all) (or _right now_)

- Living in a bubble
  - "It doesn't affect me!" (related: [Make Your Own Bubble in 10 Easy Steps](https://www.econlib.org/archives/2013/04/make_your_own_b.html), [Paradox of voting](https://en.wikipedia.org/wiki/Paradox_of_voting), [Politics as Charity](https://www.lesswrong.com/posts/SgZ2mhvDbneBusFEB/politics-as-charity))
- Doing it later
  - "Once I'm comfortable"
  - "Once I'm a billionaire"
  - "Once a personal fund reaches a certain rate of return, I'll donate gains above that percentage", etc.

## My main reason for giving

When I look back, I want to have made a good impact on the world. Tons of people I know say the same thing, and they'll say stuff like the above. I'm fine with people who come to different conclusions than I do; I don't like imposing lifestyle choices on others. Some of these points have pretty compelling arguments behind them, depending on your taste. **I believe how much one gives is a pretty personal choice**, and I value my relationships over winning an argument/moralizing in this lifestyle area.

Anyway, I believe I can impact the world _**now**_ and that **it can start small**.

This is what my character arc for changing the world looks like:

- _between 19-23_: Mentor others, help friends and talented folk get internships, start student orgs that increase students' meaning and purpose, and make as much sense of the world as I can so that I can get better at those things. The principle/platitude I tried to live by during this time is "_Be who you needed when you were younger_".
- _between 24-27_ (writing this as I turn 25 in two months): As my general sense-making and communication skills improve, increase my leverage through writing and building great products. Donate what I can without sacrificing my productivity or a lifestyle that makes me happy (including the ability to weather a financial storm), and amplify other people's donations without letting it feel like a huge burden.
- _27 and later_: Keep doing the above, but make grander moves on the "building great products" front. Keep building as a technical lead or coordinating projects as an empathetic manager, [sponsor others](https://www.leadersedge.com/brokerage-ops/mentor-vs-sponsor), start a business, angel invest, etc.

There are tons of ways to do make the world a better place: building, teaching, curing, feeding, helping directly "on the ground"—and then slightly more detached but probably still effective ways like allocating capital more efficiently, [increasing the world's GDP](https://80000hours.org/podcast/episodes/tyler-cowen-stubborn-attachments/) (to some extent), and then **giving**! Specifically giving money to non-profits or charity organizations who would allocate the capital to people who need it or to resources intended to help those who need it, including the labor of people who are helping directly.

## My plans and criteria for giving

The plan is to start small. About 1000 USD to selected causes I care about this year, and then to roughly double that year-over-year—or until a personally capped percent of my net worth at the time is met.

<img class="mb-5 lg:max-w-md" src="https://s3-us-west-2.amazonaws.com/rainier.io/giving_joke.png"/>

How do I choose which organizations to give money to? The weighting of each criterion is a bit fuzzy and by no means perfect (but better to give some than none at all, that is, to not let "_perfect be the enemy of the good_"):

- Financial accountability
- Transparency
- Long-term impact
- Directness
- Personal taste for cause—does this give me meaning? (Subtext: Would this make others think I'm a good person, and even encourage _others_ to donate?)
  - **This is important** if you want to motivate someone to give _at all_: Some of my friends would get more meaning out of personally handing twenty bucks to someone in demonstrable need, and my dad would love to surprise a family that is as poor as we once were with a brimming cart of organic groceries from Costco, all paid for.

I'll also use resources like [Charity Navigator](https://www.charitynavigator.org/) and [GiveWell](https://www.givewell.org/) to assess the factors above for a given charity.

## It's feels conflicting to part with your money

It feels weird to part ways with your money at first. What else could I have done with the money instead?! Real estate investing! My future child's school expenses!

In some cultures, it's considered disrespectful to not give some money back home (especially first-gen immigrants to their original country), and family resources are held to the highest importance. I truly empathize with this view. This bit is a little personal, but I recently talked to my parents about how much I've been giving and I'm honestly relieved and feel fortunate that they weren't distraught or annoyed by it.

If anything, in a weird way it gives me a jolt. Like, "_Wow, I should definitely keep growing my business/self so I feel more comfortable giving in the future._" At least for now, I feel fine about giving. I'm fortunate to have a safety net back home and some baseline of skills + network to stay cash flow-positive and have a roof over my head.

In a lot of ways, [donating feels like voting](https://en.wikipedia.org/wiki/Paradox_of_voting). I've found other ways to "rationalize" the act of giving to my "selfish" self. Example: this year specifically, I'm spending less money during shelter-in-place, and my employer let me expense up to 1000 USD on items make WFH more comfortable (for me and my coworkers, this went towards headphones, air purifiers, standing desks, office chairs, etc.).

## How employees with corporate matching gift programs (and their friends) can donate effectively

65% of Fortune 500 companies, including Microsoft and Coca-Cola, offer a "_corporate matching gift program_" as a benefit to their employees, which let employers match their employees donations to \[typically\] 501(c)(3)'s. Some companies will even match their employees' donations by 200% in normal or dire circumstances (e.g., Apple in 2020 during the Australian wildfires and the p\*ndemic).

According to [Double The Donation](https://doublethedonation.com/tips/matching-grant-resources/matching-gift-statistics/): although "\[a\]n estimated $2-$3 billion is donated through matching gift programs annually", "\[a\]n estimated **$4-$7 billion in matching gift funds goes unclaimed per year**".

This demonstrates that the corporate matching gift program is so incredibly underrated, and I want to convince F500 employees and their friends to consider closing this $4-$7 billion gap using corporate matching for the remainder of this essay.

<img class="my-5 lg:max-w-md" src="https://doublethedonation.com/tips/wp-content/uploads/2018/12/matching-gift-statistics-2018.jpg">

** Tips for employees 👩🏾‍💻👨‍💻 **

Want to make an impact on the world as an entry-level employee at your mega-corp job? You can serve as a broker between someone else's money and a non-profit you both support, essentially **amplifying their impact**. [Yes, it's allowed](https://donate2x.co/faq). According to the folk at MSCHF who have checked in with industry attorneys, they have "flagged no broad legal concerns" to doing this, and that "some companies explicitly **encourage** this behavior."

I mean, what makes using funds other than one's own to make a donation, different from getting money as a gift from family and **using that _fungible_ money to donate**? The worst that could happen _might_ be a warning from the company to the employee, but there's virtually no way to trace that the money wasn't the employee's, particularly if donations from multiple separate people to the same org were pooled. It would be... ridiculous if someone got fired for asking a company to match a donation they didn't make with their own money.

Get more of these cool facts from [Double The Donation](https://doublethedonation.com/tips/matching-grant-resources/matching-gift-statistics/):

> • **84% of survey participants say they’re more likely to donate if a match is offered.**  
> . . .  
> • Mentioning matching gifts in fundraising appeals results in a 71% increase in response rate and a 51% increase in average donation amount.

When I started posting on Instagram that I was personally 50% matching up to two thousand dollars other people's donations for BLM-related causes (effectively _tripling_ their donations as my employer matched 100% of our contributions), I wanted the orgs I advertised to be somewhat well-known and popular, and also to display just a few options. That's because—especially when there are so many well-intentioned non-profits to choose from—**it's easy to experience "decision fatigue" or "paralysis", which causes _friction_ for prospective donors**. Remember that e-commerce startups used to spend a significant amount of their R&D reducing friction to customer conversion (clicks before "checkout", etc.)—now instead, imagine the process of "checking out" for a cause that might not affect you immediately!

I still gave people the flexibility to propose organizations I had not suggested and was able to match some of those.

** Tips for friends and family of employees 👨‍👩‍👧‍👦👫 **

Find friends who can match your donations and come up with a compelling case for them to match your donation with their benefit. Or better yet, inspire them to graciously match or partially match your donation. One of the most common donation management platforms, used by firms like Microsoft and Google, is called [Benevity](https://causes.benevity.org/causes/search). See if the non-profit you want to support is on there before you ask.

** Here's a project idea **

A marketplace (like Craigslist or GoFundMe) where verified employees could post the causes they're interested in supporting, and non-employee donors can send them money for them to exploit corporate matching and at least 2x the donation to supported non-profit orgs. Bonus points for integrating a way to verify receipts and donation amounts while a non-employee donor's money to the employee is in escrow.

Essentially a scalable version of [this](https://donate2x.co/). Remember that $4-$7B gap I was talking about? 😉

Let me know if you're working on this and I'd be happy to send somewhat of a design doc I've written of my thoughts on this.

## More cause areas I'd like to support

- STEM education (e.g., [Black Girls Code](https://www.blackgirlscode.com/))
- Technical sponsorship for the under-represented in tech (e.g., [Code2040](http://www.code2040.org/), [Techtonica](https://techtonica.org/))
- Food insecurity (e.g., [Feeding America](https://www.feedingamerica.org/))
- Negative emissions, carbon sequestration (e.g., [Project Wren](https://projectwren.com/), see [Stripe's efforts](https://stripe.com/blog/first-negative-emissions-purchases))

## Links to other interesting and related ideas

In addition to the links I've already sprinkled throughout this essay:

- "[Americans gave 427.71B USD](https://www.nptrust.org/philanthropic-resources/charitable-giving-statistics/) to charity in 2018."
- "[Just 1% of households accounted for nearly half of all individual donations in 2015](https://www.charitychoices.com/page/how-much-given-whom-what)"—perhaps our country's economic divide is being reflected in philanthropy.
- [A Case For Giving Locally](https://ssir.org/articles/entry/a_case_for_giving_locally#)—includes touching anecdotes by an ex-_GiveWell_ researcher from her time as a debate teacher on Rikers Island, mentioning bail funds, and how we can "_reduce huge amounts of suffering right down the street, at a relatively low cost._"
- "[It should not be considered noble to remain anonymous when donating to charity, because publicizing one’s donation encourages other people to donate.](https://juliagalef.com/2017/08/23/unpopular-ideas-about-social-norms/)"—number 3 on a list of "_Unpopular ideas about social norms_".
- [A blurb about investing money and donating it before you die](https://marginalrevolution.com/marginalrevolution/2013/04/investment-and-inefficient-charity.html), and [a comment](https://marginalrevolution.com/marginalrevolution/2013/04/investment-and-inefficient-charity.html#blog-comment-157753568) about giving money to charity "_with the stipulation that they invest the donation for N years before spending it . . . so that they have the flexibility to cash out at a high point in the economic cycle._"

If you're curious, [here's a spreadsheet](https://www.notion.so/rainieratx/a6381a8a9b874c0f9f3bc2c2443d4df9?v=673c7bee6fa84ab1a33694a26dee698c) of the causes I've supported this year.



A friend of mine asked me this in our quarantine Discord the other day:

<div class="mb-4"></div>

> Any advice on how to make a good first impression to my manager and my team? I start Monday 😀

## Why this needs to be specific

Advice for new grads should be more specific than the usual advice for standing out as a software engineer.

- You'll be perceived as young.
- You most likely lack the experience to be "generally effective", even if you've had a few internships.

I'm excited to share what I've learned in the past 2 years.

## It's easier to lose a good impression than gain a better impression

It's tricky to manage a good impression IRL, especially remotely, but easy to tear down a good prior impression.

The trap I notice some smart new grads or interns fall into is trying to act like they know everything. Be humble and pleasant to work with. If you really want to, signal confidence in other contexts, maybe when talking about the things you're sure you're good at (like maybe you understand CSS specificity or obscure football trivia really well).

The majority of junior developers will [maintain code](https://medium.com/@jeffmeyerson/you-are-not-a-commodity-37083bdbf05a) the majority of the time. If you're maintaining code that's frustrating to read, don't let frustration lead you to think, "_oh, this code is so stupid, what_ dumbass _would write it like this?!_" and maybe even embark on a risky path down a rewrite no one asked for.

Maybe you're partially right, but there's also a good chance you're wrong.

- If you're maintaining the code to support a new usecase, it's likely that the engineer didn't care or know about that potential usecase at the time. Perhaps they weren't _dumb_ to not make the code modular or clear enough for it to be iterated on in the future, but rather they just realized "_You ain't gonna need it_", or [YAGNI](https://martinfowler.com/bliki/Yagni.html), at the time.
- Be wary of making large, sweeping changes or casting skepticism about the way things are in a codebase, without knowing the full reasoning behind it (or even simply assessing the author's code in _good faith_). The principle here is [Chesterton's fence](https://fs.blog/2020/03/chestertons-fence/) — from Wikipedia, "the principle that reforms should not be made until the reasoning behind the existing state of affairs is understood" — If you don't understand why something is, there might be a good reason it is the way it is.

There are obviously counterexamples to the above, but those are just things to keep in mind. You always reserve the right to be frustrated, I mean hopefully they're paying you a lot for your patience.

I forgot where I heard this from, but there's a saying that "**_the young make up for the old in speed and the old make up for the young in experience._**" This holds some truth on a software development team: the young are spry, ready to move fast and break things, whereas the more experienced are calm and calculated, making long-term decisions that don't bite the team back in the future (in the form of technical debt). This could be a powerful dynamic, respect it.

## How I stood out

Here's what worked for me:

- I was **eager** (but not to the level of brown-nosing/politicking).
  - I picked up stuff no one wanted to do.
- I demonstrated **coachability** and ability to grasp more senior engineers' opinions and implement them into my own work quickly.
- Very few times ever did a senior engineer have to explain something to me twice. It looks better to **ask for clarification** as they're describing something complex, and repeat their explanation back to them (in simpler terms) in the moment—rather than to feign understanding and ask them to repeat themselves a week later.
  - Or at least, say something like, "I don't get this _yet_, but I think I will once I dive into the code. I'll let you know if I get blocked."
  - (Because in their shoes, I would imagine, "Wow, so they didn't understand what I meant for the whole week? Wish they'd been more up front about that.")
- I demonstrated **ownership**. One of the coolest ideals for a senior engineer, which I learned from one of my best mentors, is that of an engineer who _does not need a manager_. I won't go into the details of what a manager should be doing (my opinion isn't actually well-formed on this), but essentially, the best engineer, in theory, **would not need a manager**.
  - She would pick up tasks _independently_ and be able to coordinate with product and design _on their own_. She would be able to plan and de-risk failures (both of the system and of the team's ability to deliver a project on schedule) with little guidance.
  - In this world, the main purpose of the manager would be to keep their engineers happy, to prevent them from leaving the company. To tell you the truth, this is an ideal I'm working towards, but this level of ownership is something you can start working towards once you've developed situational awareness of your organization's processes and mature out of new grad naiveté.

## Don't be a\[n inefficient\] sucker. Leverage is the name of the game

This held true for working life in the office and at home as well, but it doesn't impress me much when someone sends me a Slack notification or stays in the office until 3am (unless 3am is when they think they're productive).

Humans are probably capable of 6-8 hours of productive and creative flow time per day (writing code and prose, not shuffling emails). My idea of a "good engineer" is one who balances their time efficiently, understands the most important, **high leverage** things to work on, and spends their time on that.

The value of engineering as a discipline is _literally_ leverage, that is reducing the time for people to do dumb tasks, including _the way you engineer_. Let me get into that when I talk about going faster. For now, understand **leverage** as: `impact produced / time invested`.

What are examples of "high leverage" things? It's hard to think about especially if you're not being assigned interesting work. But tons of "uninteresting" work can be high leverage (and actually fun once you get into it):

- Writing engineer onboarding docs: This is particularly high leverage if the team is growing quickly. I have a friend at Airbnb who was one of the first engineers on their team (as a new grad) that team has grown to 20. I was tasked to write engineer onboarding docs at my last company as we were expanding our engineering team rapidly.
- I recommend [The Effective Engineer](https://www.amazon.com/dp/0996128107) by Edmond Lau. The first chapter of the book presents more details about the best mindsets to adopt to make a meaningful impact, including focusing on high-leverage activities.

One of the highest leverage things you could do when you're not being assigned interesting work is to **prove you're worth assigning interesting work to** (assuming your team has reasonable people assigning work).

To prove you're worth assigning work to, live out the four characteristics I described above, but also help yourself go **faster**. What a perfect segue...

## Go faster

To go faster, invest in tools that improve your workflow. **Demonstrate curiosity about more senior engineers' dev workflow.** Some examples:

- All the shortcuts in your IDE that keep both of your hands on the keyboard and off the mouse/trackpad.
- My tech lead has a "paste buffer" on Alfred. She can store a "stack" of things on her clipboard, and a plethora of shortcuts for code snippets she commonly types.
- Multiple people on my team use tools for working with git effectively. Some of the most time consuming but brainless things people do at a large company is cherry-picking diffs on older release branches (especially true if you're fixing bugs). There are tons of tools that make cherry-picking with git (and even automatically composing a boilerplate commit message and PR title) a lot faster.
- I have a [blog post](https://rainier.io/blog/iteration-speed) I wrote during my second SWE internship in college that might still be applicable.
- And see relevant [xkcd](https://xkcd.com/1205/) below. Even if effort towards your automation doesn't pay off soon, it's good to exercise the habit of caring and getting better at the _act of improving your tooling_.

<br/>
<img class="lg:max-w-md" src="https://imgs.xkcd.com/comics/is_it_worth_the_time_2x.png"/>

## Filter through the noise

Think about the resources you encounter when you research towards solving a problem:

- Documentation written by others
  - in your team
  - in your org
  - at your company
  - who've left your company
  - for an open-source tool or language you use
- Tutorials that tangentially help you with your problem
- Conversations on a GitHub issue or PR
- StackOverflow answers

It's useful to be reflective about the relevance of the documents you're parsing and decide if they're worth understanding the details of _now_ or _later_. This can save you time from going down a rabbithole. Though I will say, old design docs and product briefs can be super interesting to read!

A related skill is knowing how to Google effectively.

## Timebox your confusion

I walked into my first job (a [startup](https://www.dominodatalab.com/careers/campus/)) with this mindset (no one there asked me to think this way):

> Rainier, you're the first new grad engineer hire at this startup. Right now and for the next few weeks, you're costing the company more than anyone else (think about the resources that went into hiring you and the time you'll take from senior engineers pairing). Your top priority is to be productive and impactful as quickly as possible.

Obviously, you don't have to approach it this direly at like, Microsoft. And no matter where you are, don't feel "selfish" with other people's time—if an senior engineer helps you with a task that you would've been stuck on otherwise for 5 hours, that's 5 hours of the _team's_ time.

A more specific analysis of the time tradeoff would go like this: Well, if I ping an engineer in flow, it'll probably take them 30 minutes to switch context back to whatever they were doing, plus the time they'll have spent helping me, plus the time I'd been stuck on it prior to messaging them. If you're working in an office (unlikely as of the time of this writing, so you're already doing this unless you're calling them on the phone), you should **instead message them _asynchronously_** (e.g., on Slack) if they seem busy.

On the flip side, you will learn by struggling a ton and you shouldn't ask your hand to be held for every complex task. As a happy median, _timebox your confusion_. **If you're stuck on something for longer than say, 30 minutes**, then ask. Also, I like to _round robin_ my teammates if the thing I'm stuck on is something anyone on my team can help with.

## Write down your wins

I had trouble keeping up with this, but I've recognized that as we're working remotely now more than ever, **a frequent _writing_ habit for your reflections and wins** can come in handy when you're thinking of things to talk about with your manager—and justifying a promotion or comp adjustment during performance review season. What are things I write about?

- What I learned this week, and how it ties into my medium- and long-term career progression (usually a twice-a-week reflection).
  - Related to this, as a general tip, is to **show curiosity** by asking questions about engineering practice (project coordination, team dynamics, hiring, inclusion, conflict resolution, risk management, security, site reliability, oh yeah and the code itself, etc.) and **writing down the "case studies" or opinions you encounter** so that you can develop your own opinions and models to apply to uncertainty or new problems in the future.
- Compliments and kudos from other teammates (these usually come in during our sprint retros or in code review feedback—could screenshot them in a digital scrapbook if you wish).
- Meaty features and bugs with a huge customer impact (can backtrack these from my commit history as well, but it's nice to synthesize these).
- Small, even one-pager design docs for large tasks that haven't been completely thought through yet.

I like these because they're a paper trail, these writings are artifacts of your personal growth and accomplishments outside of your GitHub commits.

If you made it to the end, you likely care enough that you'll be at least ok. You can do this! Good luck.

Did I miss anything? Feel free to reach out to me [@rainieratx](https://twitter.com/rainieratx) or via my contact form.



Time during shelter-in-place (day 48 as I'm writing this) has been interesting for me as I've had incredible _control_ over my time.

<div class="mb-4"></div>

And I don't mean control in the sense of _self-control_. If you know me, I'm definitely far from perfect, quite far in fact, from the "SF optimizer" archetype¹. Yes, particularly in this stressful time, I don't think I'm the only one who's ordered 20 McNuggets, 2 McDoubles, and an Oreo McFlurry a few hours into their weed-infused gummy.

By _control_ over my time, I mean that I get to do what I want, when I want to. My days are largely unstructured and I don't have set work hours. The only constraint is a generally-accepted range of time for meetings with my team and an uninterrupted block or two each day to get my work done. I no longer have to consider:

- The daily commute
- Showing up to the office for lunch and being with my co-workers
- Time spent getting ready to visit friends or meet at restaurants
- The cost of context-switching between those activities. As Paul Graham says in [Maker's Schedule, Manager's Schedule](http://www.paulgraham.com/makersschedule.html):
  > If I know the afternoon is going to be broken up, I'm slightly less likely to start something ambitious in the morning. I know this may sound oversensitive, but if you're a maker, think of your own case. Don't your spirits rise at the thought of having an entire day free to work, with no appointments at all? Well, that means your spirits are correspondingly depressed when you don't. And ambitious projects are by definition close to the limits of your capacity. A small decrease in morale is enough to kill them off.

With control of my time and so much time alone, I've been able to introspect more and tease out what some of my common failure modes, or _spirals_, are. The following thoughts have percolated in my mind for the past 3 years of having **deep, swinging levels of self-directed productivity** and medium introspection (now high introspection—no pun intended).

## What is a spiral?

A **spiral** is defined as a pattern of consumption that, if pursued indefinitely, leads to self-sabotage. And **self-sabotage** is when you're the one preventing yourself from reaching your goals. Spiraling is when you're not being productive, there's low or negative long-term payoff from this position, and sometimes it's unclear when it'll stop.

I call them spirals because they're recurring and indefinite. Like Netflix and B2B enterprise SaaS subscriptions. Left unchecked, they can suck up your time on Earth or leave a hole in your wallet.

## The 5 (Sometimes Very Bad) Spirals

\[...of Rainier\]. I own these. Maybe our spirals overlap, or you never spiral! Let me know 😀🍥

### 1. The hedonistic spiral

Can be done with friends or by oneself. Characterized by medium-to-large amounts of alcohol and recreational drug (read: weed) use, consumption of comfort and fast food, etc.

**Is it purely bad, and why?**

It's not 100% bad. Bonding with your friends is good. It's "living a little". Some of my friends who do it will be the most successful people in their pursuits. I believe that altered states—low or in moderation—prevent you from "overfitting" on your models of the world, and that reduced giving-a-shit thresholds can be great in some social situations.

But it's undoubtedly bad in excess, like a bunch at one time or for multiple nights straight.

**What's the antidote?**

For me, it's a night of rest, a shower, and at least a 16-hour fast (with the exception of black coffee) from the last time I ate. To be clear, I endorse a healthy relationship with food. There is some solid science behind intermittent fasting and autophagy. Anyway, doesn't matter much in that it works for me.

### 2. The ~~conceited~~ nostalgic spiral

This happens when I post something on social media and wait for other people to like and comment on it. I scroll through my About page on Facebook, polish up my LinkedIn, reminisce on my old tweets, etc.

**Is it purely bad, and why?**

It's not harmful _per se_, but there's absolutely zero value to this activity, besides the effects of comparing yourself to the best versions of other people on social media. It's healthy to reminisce once in a while to see how far you've come with your friends, but there ought to be a limit.

And if people are replying to your posts, reading those replies can wait. Trust me.

**What's the antidote?**

Limiting social media time. Getting over yourself. Before I properly identified it and stamped it out, it probably took man-weeks out of my teenage years that could've been spent reading, building, or hanging out with friends.

Largely, I just had to get over myself.

### 3. The Wikipedia rabbit hole spiral

Characterized by a bunch of tabs you'll never get to and maybe some level of paralysis. It's 3 AM and you're reading about [the spy](https://en.wikipedia.org/wiki/Krystyna_Skarbek) that inspired Vesper Lynd's character in _Casino Royale_, or watching 60-year-old [MRE unboxing](https://www.youtube.com/watch?v=vkWM6mz_JVo) videos on YouTube.

**Is it purely bad, and why?**

This isn't bad in the sense of destroying your body (besides maybe sleep) or self-worth or anything, but can suck up time from other, deeper work.

**What's the antidote?**

Again this is the most innocent of spirals. Being curious about the world is a sparkly personality trait ✨. Recognize the spiraling and move on, or limit your time (e.g., going back to what you were doing at the end of the clock hour).

### 4. The "OCD"/over-engineering-this spiral

(Note: this might not make sense if you are not an engineer, so feel free to skip.)

This is the cousin of the **Wikipedia rabbit hole spiral**. This happens when you're working on a project. I've generalized this to two types I've experienced over and over again:

- "Over-engineering" a solution to a problem. I don't need Kubernetes to host a virtual trivia game site. (Yet.)
- Being stuck on a problem (my old CTO called this "rat-holing") for too long without having asked for help or _back-tracking_ to evaluate other potential "branches" that could lead to a solution.

**Is it purely bad, and why?**

Definitely not. Being in "explore" mode in the realm of personal projects is fine, until you have accomplished nothing or sunk time into an arcane framework that no one will interact with except yourself because you did not ship anything.

**What's the antidote?**

I have an angel on my shoulder that repeatedly asks me every few hours (nerds would call this some sort of "mental cron job"):

> 👼👨‍💻
> **"Am I delivering _value_ to my \[potential\] users right now? Or am I wasting time over a technical decision that won't affect anyone besides me?"**

This one also helps:

> 👼👨‍💻
> **"So what _exactly_ is the end goal here?"**

When you're working on a project with a lot of moving parts, it's easy to lose sight of the forest for the trees, as they say.

In the case of being stuck on a problem, I sometimes change what I'm working on, like moving to the frontend if I'm stuck on a backend issue, vice-versa, or I'll go for a run instead. Pretty typical problem-solving advice.

Setting aggressive timelines for yourself (see **Setting Your Goals Publicly** at the bottom—maybe an aggressive launch date for your projects) could force you to weigh the tradeoffs of taking a shortcut here and there. As an attendee of 13 hackathons in college, I should understand this well, but I still fall into this spiral occasionally!

### 5. The akrasiac spiral

Sort of a catch-all for spirals in my life. You don't want to get out of bed. There is so much to do or can be done, but you just won't do it. You might be overwhelmed, but that is not a necessary condition for akrasia.

**Is it purely bad, and why?**

It's terrifying. It's hard to pin it down.

**What's the antidote?**

This is probably closer to burn out or depression. What do I do? I go out for a walk, a run, set up early calls with my family and friends (not necessarily talking about it) so I have a reason to get up earlier. Maybe watch an episode of a great show like _Unbreakable Kimmy Schmidt_ or _Arrested Development_ to get into a relaxed state.

## Broad Interventions

What if the antidotes don't work as well as you wanted them to? Try introducing habits gradually, a drastic change of pace, setting goals publicly, or seeing a coach and/or therapist!

- Developing a routine. Start with small, micro-habits. I sleep away from my phone, set my running gear in front of my bedroom door the night before, and I've found these to be fairly effective.
- Joining an early-to-mid stage startup. There's nothing like a drastic (and possibly intentional) change to your circumstances to "reboot" your "motivation drive". It could be one of the most meaningful arcs of your career.
- Setting your goals publicly, or sharing your goals with a friend. This overlaps with the coach or therapist in that they're a sort of "accountability" buddy—but you should be careful not to over-burden your friends who are in their own lane.
- A coach or therapist can "tease out" the weird patterns in your life in a few sessions as opposed to taking years for oneself. I'm extremely lucky to have met a coach I work well with during this time.

## Related reads

- [Akrasia is confusion about what you want](https://www.lesswrong.com/posts/XmqqkfY8XAJ6LkwdP/akrasia-is-confusion-about-what-you-want)
- [The Productivity Cycle](https://alexsexton.com/blog/2014/1/the-productivity-cycle/) — can also find this under my [recs](https://rainier.io/recs)

## Footnotes

¹ The SF-optimizer archetype: mid-to-late-20s keto Stanford graduate who splits their time between Equinox, bikes across the Golden Gate Bridge, scheduled 30-min syncs with their East Coast parentals, and flow time. See this tweet:

> <blockquote class="twitter-tweet"><p lang="en" dir="ltr">20-something SF tech people are just *frightfully* optimized. They&#39;re all athletic beautiful machine-learning geniuses who have cuddle puddles and go to Burning Man.<br><br>The Stanford super-kids I went to college with were like malformed goblins compared to this new breed.</p>&mdash; #TestAndTrace EVERYWHERE NOW 🐇 (@Noahpinion) <a href="https://twitter.com/Noahpinion/status/1153706839927738368?ref_src=twsrc%5Etfw">July 23, 2019</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

Write to me [@rainieratx](https://twitter.com/rainieratx) or via my [contact form](https://rainier.io/contact)!



One of my busy friends who loves his job but also wants to find ways to fit reading into his schedule—for personal enrichment, not to tell his friends at a party that he's "read" 52 books this year—asked me a question:
<br/>
<br/>

> have you used Audible?

Nah, I'm skeptical of how much is retained when listening to vs reading a book.

I mostly read non-fiction. When I read, I get to build mental structures of the ideas at my own speed. I get to flip the pages back, make sure the last idea that _this_ current idea was built on top of, made sense to me.

Maybe I'd use Audible if I read more fiction—but even then, there's a wealth of interesting fiction and narrative non-fiction podcasts _intended_ to be listened to, and I might get higher entertainment value out of those.

Examples of these are the [Long Distance](https://gimletmedia.com/shows/reply-all/6nh3wk/102-long-distance) episodes of _Reply All_ and [S-Town](https://stownpodcast.org/). They entertain well by weaving together a story through dialogue, using different voices (characters) and settings (studio vs. in-the-field), capture modes (raw surprise / thinking on their feet vs. a prepared response), ambient sounds mixed with music that illustrate a setting that is difficult to capture with words.

It's almost as if sound partly relieves the responsibility from the narrator to describe "what it was like" at the time. Sound abstracts away pieces of exposition ("_the man said in a booming, scary voice_"), without removing too much from the listener's imagination, like Hollywood sets and CGI might. Sometimes audio is the perfect balance between text and video in that regard.

<iframe class="mb-2" src="https://www.youtube.com/embed/YsufMtUOXtI" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<div class="mb-4 text-xs">Portlandia (Fred Armisen, Carrie Brownstein) pokes fun at true crime podcasts and it's hysterical.</div>

I heard the new Malcolm Gladwell book, _Talking to Strangers_, is actually read by a bunch of different voices that sound like actual strangers! So audiobooks with high production quality might be exceptional cases. But generally, in order to appreciate something heard, it needs to have a strong narrative with memorable characters. The individual ideas on the page can't be too dense. Some college students spend a week studying a paragraph of Nietzsche. Most authors speak differently from how they write.

Don't get me wrong, it's great to listen to informative things during one's "idle" time (folding laundry, cooking routinely, commuting). I'm just skeptical of how much I'll retain from a medium intended to be _read_ rather than _listened_ to.

Friend's response:

> ill continue reading while driving to work then
>
> lol

Related reads:

- [Write Like You Talk](http://www.paulgraham.com/talk.html)
- [Ode to Audio: Why You Should Give Podcasts and Audiobooks a Chance](https://devonzuegel.com/post/ode-to-audio-why-you-should-give-podcasts-and-audiobooks-a-chance)

Write to me [@rainieratx](https://twitter.com/rainieratx) or via my [contact form](https://rainier.io/contact)!



This week I messed up on an question whose solution involved a BFS over an element's left, right, and bottom neighbors in a grid. This post exists to make sure I don't mess it up again.

This requires writing the function to get the neighbor coordinates of the element in a grid, like this...

```python
grid = \
[[0 0 0 1 0 0],
 [0 0 1 X 1 0],
 [0 0 0 1 0 0]]

# let's say we want the neighbors of the coordinate where 'X' is
get_neighbors(grid, 1, 3) # -> [(1, 2), (2, 3), (1, 4)]
```

The part in question where I messed up on is my version of a _koan_ (that was the word, Ben!) that I learned from competitive programming class (thanks Arnav, though I doubt you'll ever read this). This is the **incorrect** version of a function that I should have really committed to memory by now...

```python
def get_neighbors(grid, visited, i, j):
    dx = [-1, 0, 1]
    dy = [0, -1, 0]
    return [(i+x, j+y) for x, y in zip(dx, dy) \
            if legal(grid, i+x, j+y) \
            and grid[i+x][j+y] == PASS \ # problem-dependent
            and (i+x, j+y) not in visited]
```

Do you see it??

There are a few things wrong with it, based on my forgetting that Cartesian coordinates `!=` the convention for multi-dimensional array indexing. When I'm coding it and saying it out loud in my head, like "Yeah, the change in `x` will be `-1`, change in `y` will be `0` if you go left, `x` `0` `y` `-1` if you go bottom", it makes total sense, but it's wrong. Applying a `-1` transformation to the index associated with `y` (which is not `j`, by the way, but `i`, so that was another mistake) is wrong -
that will examine the neighbor **above** the input coordinate.

This is the correct way to get the left, right, and bottom neighbors:

```python
def get_neighbors(grid, visited, i, j):
    di = [0, 1, 0]
    dj = [-1, 0, 1]
    return [(i+y, j+x) for y, x in zip(di, dj) \
            if legal(grid, i+y, j+x) \
            and grid[i+y][j+x] == PASS \ # problem-dependent
            and (i+y, j+x) not in visited]
```

Do you see the difference? I flipped the indices I made the association with x-y coordinates for, and changed the `-1` to `+1`.

Another interesting problem came up today, which involved a series of sums of a sub-matrix of size K\*K in a matrix of size N\*M. Here's a candidate for a new personal koan:

```python
def subsum(grid, i1, i2, j1, j2):
    psum = 0
    for i in range(i1, i2):
        psum += sum(grid[i][j1:j2])
    return psum

for i in range(len(grid)-K+1):
    for j in range(len(grid[0])-K+1):
        subsum(grid, i, i+K, j, j+K) # do something with this
```

Do you think there is a better way to do this? Please email me, so I can get a job 😅



In about 52 hours I'll get into Heathrow Airport in the UK. Starting next week, I'll be an engineering intern at Desktop Genetics, a hot bioinformatics startup in London focused on a machine learning and data engineering SaaS for CRISPR/Cas9 gene-editing.

Starting out as a biochemistry major in college, realizing my love for **genetics** and later on when I became a computer science major, love for thinking in abstractions and thusly my potential as a **software engineer**, I don't think I could have picked up a more exciting opportunity than to intern at a company specializing at the intersection of my first and second loves.

I'm incredibly grateful and lucky for all of the people and experiences I've had so far that have led me to this point, and can't wait to write code that can make an impact on the world.

Living in a foreign country in a continent I've never been to shall also be an adventure.

See you soon, London.



## Clover

I interned at Clover. **Facts about them:**

- Point-of-sales (POS) platform startup that launched in 2012 and was acquired later that year by First Data, the world's largest credit card processing company.
- First Data is in charge of sales and support, and Clover engineers the hardware and software for new POS devices.
- There's a "Founder's Clause" in the acquisition contract that would make First Data pay a large fine if they interfered with Clover's operations. So it still operates and feels like a startup.
- Their devices run a custom fork of Android. They provide an app store and ecosystem with a public API and SDK for developers to build business-related apps (e.g. for tabling, employee/inventory management, etc.).
- Over 100 people work in the Sunnyvale HQ as of this writing. However, I saw new engineers and business people get hired every week.
- 11 engineering interns at Clover HQ this summer (8 from UT Austin due to some early employees being alum).

It went for 13 weeks, from May 23rd to August 19th, 2016.

I was on the server team. My project initially involved integrating a time-series database and fixing a metrics collection service written in Python and a tiny bit of Go. Later on, I helped redesign and rewrite it completely in Go, both experiences from which I learned immensely from. Also, I was assigned bugs and performance issues related to the main server codebase like any other full-time engineer on the team. This allowed me to dust off my Java, learn Netty, pick up a large codebase, understand architectural concepts like the difference between monolith and microservices, and get better at switching tasks quickly.

My favorite part about the server team was how talented everybody had to be. To be a successful server engineer at Clover, you have to be a **full-stack generalist**. I'm not talking about being able to tie together web app frontends and backends with React, Node.js and MongoDB, although that's still a marketable skill on its own. You have to pick up parts of the Android and Web ecosystems to see how your changes will affect those end-users, know database query optimizations, know where it's smart to introduce caches and fiddle with the JVM, account security compliance into your implementations (it is a payments company, after all), and apply statistics for performance anomaly detection. If a critical part of server goes down or experiences significant latency, lots of businesses are potentially affected - the code at Clover _matters_. But on top of the engineering culture, there are friendly and approachable people everywhere. I didn't feel discouraged from asking anyone questions.

The food and perks were nice. We had swanky corporate housing, free Uber for commuting to work and back, highly-customizable lunch from Forkable and catered dinner, daily. Yummy snacks and drinks like harmless coconut water and matcha green tea Kit Kats. Open bar and weekly happy hours if you're 21+.

Clover was a very good place to intern - I had fun, felt that I had provided tangible value to the company, and learned a ton, which should be the goal of an internship. They are growing and hiring rapidly, and their internship program can only get better every year. I recommend it.

## Why you should try a smaller company at least once

I'm a strong believer that software engineering internships should be about trying as many experiences as you can, and **growing**. Especially at small-to-midsize startups, there's the unique possibility of witnessing the extremely fast growth of a company. Then you'll get to watch (or help 😀) engineers wrestle with scaling issues, listen to product design meetings, overhear business people who aren't on a different floor yet perform pitches, participate in a company's early all-hands meetings, and so much more.

I've been privileged to intern at two differently-sized startups: a 10-person one and a 110-person one. I've had the chance to report to and get my code reviewed by very senior engineers at each one and push features to production that had a much likely **higher relative impact** (or as my friends in management consulting would call it, "value add") than if I had worked at a larger corporation. Finally, I've gained experience with technologies that are easy to scale, iterate with, and will build the future, including Go, Python, and JavaScript. When I asked some engineers at Clover why they prefer working there over bigger shops, it's because of huge technical growth, the available bandwidth to take ownership of, and impact.

I'm not saying you shouldn't work at a larger company - I hope I'll get to try it out one day and see which experiences optimize for my growth and personal happiness at whatever stage of life I'm in. But a smaller company is something, I believe, you should try at least once.

## Silicon Valley

I went to a few networking events. I couldn't intern in Silicon Valley and _not_ network - it's Silicon Valley. Tweet or DM [@rainieratx](https://twitter.com/rainieratx) if you missed me at one of them!

- KPCB Diversity Mixer
- Accel Backyard Bash
- Keen IO Party
- HackCon IV (in Colorado)
- FutureForce Friendfest
- Google SF Insider Night
- Medallia Game Night
- Explore Pinterest
- Uber Open House

I also visited some friends at Facebook and Twitch HQ. I was surrounded by brilliant engineers, product designers, and thought leaders of the entrepreneurial spirit everywhere. Lots of people were passionate about stuff outside of work or school, and I loved the culture of building the future.

The areas surrounding Sunnyvale were nice. I hung around Palo Alto, Mountain View, and Santa Clara whenever I chilled in South Bay. Visited Half Moon Bay, Santa Cruz, and Yosemite. Went to San Francisco nearly every weekend via Caltrain. Asian food, including sushi and bubble tea, was 10x better there than in Austin. Iced mint mojitos from Philz were amazing but California hasn't seemed to figure out breakfast burritos or queso yet 😬.

I'm glad I tried it out, and I wouldn't mind coming back to the Bay Area next summer.

_What did you like about your summer? Questions about my internship?_  
_Tweet or DM [@rainieratx](https://twitter.com/rainieratx)!_



## Motivation

In this post, we will explore a string manipulation task with the constraint that the solution is to be in as few lines as possible. Why? Just for fun. I would _never_ commit an unclear, maybe inefficient one-liner into production code just to show off, and you shouldn't either. However, I think this and similar constraint puzzles (in the category of what is called "code golf") are really fun mental exercises in abstraction, problem decomposition, and mastering a language's esoteric features.

The Slack for one of the student organizations I'm in has a channel called #_politics_. The channel's pinned post is an ever-growing URL to a visualization of each channel member's political views on the two axes of the political spectrum created by this website: "Libertarian-Authoritarian" and "Left-Right".

The following is a sample URL that's pinned in our channel (names replaced with the Greek alphabet):

```
https://www.politicalcompass.org/crowdchart?alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&delta=-4.75%2C-4.97&epsilon=-9.0%2C-8.31&zeta=-7.38%2C-4.36&eta=-3.5%2C-3.6&theta=-4.38%2C-2.92&iota=-7.13%2C-6.0&kappa=1.63%2C-2.36&lambda=-5.75%2C-6.51&mu=-3.25%2C-3.64&nu=1.75%2C-2.15&xi=-3.75%2C-5.08&name=omicron&ec=-4.88&soc=-2.05
```

And a sample image:

![image](https://www.politicalcompass.org/charts/crowdchart?alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&delta=-4.75%2C-4.97&epsilon=-9.0%2C-8.31&zeta=-7.38%2C-4.36&eta=-3.5%2C-3.6&theta=-4.38%2C-2.92&iota=-7.13%2C-6.0&kappa=1.63%2C-2.36&lambda=-5.75%2C-6.51&mu=-3.25%2C-3.64&nu=1.75%2C-2.15&xi=-3.75%2C-5.08&name=omicron&ec=-4.88&soc=-2.05)

(Not surprising, considering that I go to the University of Texas). It would be nice to get a JSON encoding of this information so we might be able to integrate it into dataviz tools for practice.

## Problem

Given an URL, such as:

```
https://www.politicalcompass.org/charts/crowdchart?alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&name=omicron&ec=-4.88&soc=-2.05
```

write a function to deserialize it into a JSON-like encoding, such as:

```
[
    {
        "alpha": {
            "economic": "-3.38",
            "social": "-5.38"
        }
    },
    {
        "beta": {
            "economic": "-2.75",
            "social": "-4.62"
        }
    },
    {
        "gamma": {
            "economic": "-4.63",
            "social": "-4.15"
        }
    },
    {
        "omicron": {
            "economic": "-4.88",
            "social": "-2.05"
        }
    }
]
```

using as few lines as possible.

## Decomposition

We are mainly interested in the names of people and their econo-/socio- political preference scores, which are delimited by various characters. In a string `s = 'https://www.politicalcompass.org/charts/crowdchart?alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&name=omicron&ec=-4.88&soc=-2.05'`, we can split it by `?` to return a list object:

```python
In [1]: s = 'https://www.politicalcompass.org/charts/crowdchart?alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&name=omicron&ec=-4.88&soc=-2.05'

In [2]: s.split('?')
Out[2]:
['https://www.politicalcompass.org/charts/crowdchart',
 'alpha=-3.38%2C-5.38&beta=-2.75%2C-4.62&gamma=-4.63%2C-4.15&name=omicron&ec=-4.88&soc=-2.05']
```

Now we can get the string we're interested in using the expression `s.split('?')[1]`. In length-constrained coding, we want to minimize the number of new variable assignments, and this language's AST lets us do this. Since `s.split('?')[1]` returns our string of interest, we can call `.split('&')` on that expression to obtain a list of strings:

```python
In [3]: s.split('?')[1].split('&')
Out[3]:
['alpha=-3.38%2C-5.38',
 'beta=-2.75%2C-4.62',
 'gamma=-4.63%2C-4.15',
 'name=omicron',
 'ec=-4.88',
 'soc=-2.05']
```

We are getting closer to the form we would like, but there is some cleaning up to do with special cases at the end. As soon as a person (let's say their name is `omicron`) adds their own name and scores to the list, the new HTTP GET parameters remain encoded in the URL (after the third-to-the-last `&`). (The endpoint handler can handle URLs without the last three GET parameters, but we don't want the client to have to conform their parameters to the previous parameters by hand). Let's make an expression to select the last 3 elements in the list to transform it into one element that conforms to the rest of the list:

```python
In [4]: s.split('?')[1].split('&')[-3:]
Out[4]: ['name=omicron', 'ec=-4.88', 'soc=-2.05']
```

But we're still only interested in the string parts after the `=`, and want to make a sequence of those to combine later. If we only focus on one string `name=omicron`, we can see that we want to call `split('=')` and grab only second element of its return, i.e., `'name=omicron'.split('=')[1]`. But what if we wanted to apply this function to a list of strings?

**Enter the lambda syntax.** With `lambda`, we can convert a function into a one-liner.

```python
lambda x: x.split('=')[1]
```

We can even assign it to a variable and call it like this:

```python
In [5]: my_lambda = lambda x: x.split('=')[1]

In [6]: my_lambda('foo=bar')
Out[6]: 'bar'
```

Also note that it looks like a mathematical function, such as f(x). But like I said earlier, we'll keep assigning expressions to variables to the minimum. It's important to understand that the lambda definition always contains an expression (after the `:`) that is returned upon evaluation.

So back to the last question - how do we apply this function to a list of strings that have `=` in them?

**Enter the map syntax.** `map(func, seq)` applies function `func` to every element in sequence `seq`, and it always returns a sequence (such as a `list` or `tuple`) such that each element is the return of the function applied to that element. It's probably easier to show you:

```python
In [7]: map(my_lambda, ['foo=bar', 'baz=qux', 'ham=spam', 'eggs=bacon'])
Out[7]: ['bar', 'qux', 'spam', 'bacon']
```

Let's use `map` and `lambda` to compose a list of the strings we were interested in, building on the list expression we composed earlier in `[4]`:

```python
In [8]: map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:])
Out[8]: ['omicron', '-4.88', '-2.05']
```

Now use this list as arguments and the string `'{}={}%2C{}'` as the caller to the function `str.format(*args)` to get a string that conforms to the other strings (e.g., `alpha=-3.38%2C-5.38`) in the original list:

```python
In [9]: '{}={}%2C{}'.format(*map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:]))
Out[9]: 'omicron=-4.88%2C-2.05'
```

(`*` is the "splat" operator, which converts a Python list into positional arguments in a function call.)

Before we append this string to the original list, let's get all but the last 3 elements from the original list in `[3]`:

```python
In [10]: s.split('?')[1].split('&')[:-3]
Out[10]: ['alpha=-3.38%2C-5.38', 'beta=-2.75%2C-4.62', 'gamma=-4.63%2C-4.15']
```

We can wrap the expression from `[9]` that returns the new string in brackets to convert it into a single-item list, and append it to the original list using the `+` operator:

```python
In [11]: s.split('?')[1].split('&')[:-3] + ['{}={}%2C{}'.format(*map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:]))]
Out[11]:
['alpha=-3.38%2C-5.38',
 'beta=-2.75%2C-4.62',
 'gamma=-4.63%2C-4.15',
 'omicron=-4.88%2C-2.05']
```

We need to break up each string by `=` and `%2C` now. Hello, `map` and `lambda` again:

```python
In [12]: map(lambda x: [x.split('=')[0]] + x.split('=')[1].split('%2C'), s.split('?')[1].split('&')[:-3] + ['{}={}%2C{}'.format(*map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:]))])
Out[12]:
[['alpha', '-3.38', '-5.38'],
 ['beta', '-2.75', '-4.62'],
 ['gamma', '-4.63', '-4.15'],
 ['omicron', '-4.88', '-2.05']]
```

And the final `map`/`lambda` combo:

```python
In [13]: convert_to_dictlist = lambda s: map(lambda x: {x[0] : {'economic' : x[1], 'social' : x[2]}}, map(lambda x: [x.split('=')[0]] + x.split('=')[1].split('%2C'), s.split('?')[1].split('&')[:-3] + ['{}={}%2C{}'.format(*map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:]))]))
```

Let's try it:

```python
In [14]: convert_to_dictlist(s)
Out[14]:
[{'alpha': {'economic': '-3.38', 'social': '-5.38'}},
 {'beta': {'economic': '-2.75', 'social': '-4.62'}},
 {'gamma': {'economic': '-4.63', 'social': '-4.15'}},
 {'omicron': {'economic': '-4.88', 'social': '-2.05'}}]
```

It worked, and we defined the function in one line.

We can use `print json.dumps()` to print it out in a nicer looking format.

```python
In [15]: import json

In [16]: print json.dumps(convert_to_dictlist(s), indent=4)
[
    {
        "alpha": {
            "economic": "-3.38",
            "social": "-5.38"
        }
    },
    {
        "beta": {
            "economic": "-2.75",
            "social": "-4.62"
        }
    },
    {
        "gamma": {
            "economic": "-4.63",
            "social": "-4.15"
        }
    },
    {
        "omicron": {
            "economic": "-4.88",
            "social": "-2.05"
        }
    }
]
```

Nice!!

## The answer

**Disclaimer**

I didn't get this one-liner immediately off the top of my head and on the first try. I use a fantastic REPL/interactive shell called [IPython](https://ipython.org/) (where the `In`/`Out` lines come from) that makes it easy to quickly iterate (no pun intended) on composing Python code. There, I decomposed the problem, made dozens of intermediate variable assignments to heavily abstract, and then substituted the variables with the original statements and expressions they were assigned to.

**The one-liner**

```python
lambda s: map(lambda x: {x[0] : {'economic' : x[1], 'social' : x[2]}}, map(lambda x: [x.split('=')[0]] + x.split('=')[1].split('%2C'), s.split('?')[1].split('&')[:-3] + ['{}={}%2C{}'.format(*map(lambda x: x.split('=')[1], s.split('?')[1].split('&')[-3:]))]))
```

**Expanded for "clarity"**

```python
lambda s:
  map(
    lambda x:
      { x[0]: { 'economic' : x[1], 'social' : x[2] } }
      map(
        lambda x:
          [x.split('=')[0]] + x.split('=')[1].split('%2C'),
            s.split('?')[1].split('&')[:-3] + ['{}={}%2C{}'.format(*
            map(
              lambda x:
              x.split('=')[1],
                s.split('?')[1].split('&')[-3:]
            )
            )
          ]
      )
  }
```

## Resources

Some links about `map` and `lambda` (kinda Python specific) since my explanation didn't do it justice:

A pretty approachable introduction to lambda expressions in Python that demonstrates their usefulness in production code, scoping rules, and addresses common points of confusion: [Yet Another Lambda Tutorial](https://pythonconquerstheuniverse.wordpress.com/2011/08/29/lambda_tutorial/)

Quora: [Is it better to use list comprehensions or map with a lambda function when manipulating elements in a list?](https://www.quora.com/Is-it-better-to-use-list-comprehensions-or-map-with-a-lambda-function-when-manipulating-elements-in-a-list)

_Does your favorite programming language have syntax for map, filter, reduce, and/or lambda expressions?_



One Quora answer that's really stuck with me for the past few months is [Edmond Lau's answer](https://www.quora.com/What-are-the-things-required-to-become-a-hardcore-programmer/answer/Edmond-Lau) to "What are the things required to become a hardcore programmer?" The entire answer is solid, but this is the part I will focus on:

> **4. Optimize your iteration speed.**

> Say it takes you 12 seconds to search and navigate from a function call to where it’s defined. And suppose you have to do similar navigations 60 times per day. That’s 12 minutes per day spent navigating files. If you learn enough keyboard shortcuts in your text editor to navigate to a file in 2 seconds instead of 12, then over the course of a day, you'd save 10 minutes. Every year, you’d save an entire 40-hour work week.

> Find 3 more similar optimizations, and you’d save a month. Imagine what you could do with an extra month per year.

> Or suppose that you’re fixing a bug that requires you to start the app and then navigate through five screens to set up the right conditions to trigger the bug. Could you spend 10 minutes to wire it up so that it goes to the buggy screen on startup? You’d be able to iterate significantly faster on that bug with a small initial investment.

> Systematically ask yourself, “How can I iterate faster?” The payoffs will be enormous.

One of the payoffs, not explicitly mentioned, is that decreasing your iteration time will lower your chances of emptying your mental "cache" or "stack" of things to do, i.e., getting distracted, while you're spending time on minor, unnecessary context switches.

I'm a student currently at my second software internship. As someone who's been developing stuff for just a little under two years, I'm not the fastest, but I've still managed to accumulate a list of small, medium, and large techniques that speed up my development. I feel like adopting _every_ technique possible (like learning how to use the Dvorak keyboard, for me) would be impractical, so these are the ones that keep me fast but sane. It also goes without saying that different tricks will work for different people, so I hope my tips are general enough for most budding developers.

(_By the way, most of these work best if you work in a Unix environment. Most of my work these days is done on OS X and when I'm ssh'd into Linux boxes._)
<br>
<br>

## Small things

**Select all/copy/paste** (well-known)

`[Cmd-a]`/`[Cmd-c]`/`[Cmd-v]`

**Quickly navigate and select text**

Using keyboard shortcuts such as `[Cmd-Left/Right]+[Shift-Cmd-Right/Left]` to highlight a line. Experiment with these!

**Get to the beginning of a line in the shell**

`[Ctrl-a]`

**New tab/Close tab in most programs that have tabs**

`[Cmd-t]`/`[Cmd-w]`

**Issue the last command in `sudo` mode**

`sudo !!`

At first, I thought it was a funny alias my mentor made, as in, "sudo, darn it!". But `!!` (read: "[bang-bang](http://ss64.com/bash/bang.html)") is a great thing to know!!

**Launch Sublime Text from the command line**

If I'm not using [Vim](http://www.vim.org/download.php) or [MacDown](http://macdown.uranusjr.com/), I open up Sublime like so:

`subl README.md`

You can either add an alias to the Sublime app in your shell profile or add a symlink to it in one of the `/bin` folders of your `PATH`.

_More: [Stack Overflow link](http://stackoverflow.com/questions/16199581/opening-sublime-text-on-command-line-as-subl-on-mac-os)_

**Take advantage of Spotlight (or [Alfred](https://www.alfredapp.com/))**

It takes me less than a second to launch the most-used applications on my desktop. To do that, all I have to do is type `[Cmd-Space]` anywhere and the first few letters, if not just the first letter, of the application.
<br>
<br>

## Medium things

**Use oh-my-zsh**

[Oh My Zsh](https://github.com/robbyrussell/oh-my-zsh) is an easy-to-install framework for installing and managing `zsh`, an alternative shell to `bash`. The most useful feature for me is its fast autocompletion and ability to simply tab through autocompletion results. It also makes your shell look fancy :)

_More: [Difference between bash and zsh](https://www.quora.com/What-is-the-difference-between-bash-and-zsh)_

**Use a good `.vimrc` if you use Vim**

I'm pretty lazy and use the one by "amix" out of the box. If I cared more to study Vimscript, I could roll my own and be an `3l33t h4x0r`, but this will do.

_More: [The ultimate vimrc](https://github.com/amix/vimrc)_

**Add stuff to your `.bash_profile`/`.bashrc`/`.zshrc`**

```bash
alias workonproj="ssh -t rainier.ababao@xyz.example.com 'cd ~/project_directory; bash'"
```

It's quite nice to open up the shell and type in a short alias to ssh into a server.

```bash
export GITPAT="xyz"
```

If I have GitHub two-factor auth enabled, I'm required to use a "personal access token" to authenticate pushes if I cloned by HTTPS instead of SSH. In that case, I can just `echo $GITPAT` since it's an environment variable in my private shell profile, and copy-paste it whenever I have to authenticate. However, I stopped doing this when I learned about triggers for my terminal...

_More: [Learning the Shell](http://linuxcommand.org/lc3_learning_the_shell.php)_

**Take advantage of iTerm2**

For command line work, I use iTerm2 instead of Terminal. There are a lot of great things about it, and one of them is triggers. A trigger is a regex that iTerm2 listens for, followed by an action, like automatically entering text as if the user had typed it in themselves. I have a trigger set up so that when `\[sudo\] password for rainier.ababao` appears, the password manager opens and I just press `[Enter]` for iTerm2 to put in my password.

_More: [iTerm2 triggers](https://www.iterm2.com/documentation-triggers.html)_
<br>
<br>

## Large things

**Improve your words per minute (WPM)**

Learn to keep your fingers on the home row and touch-type! It will be slow at first, but you'll see gains from 40 WPM to 100-120 WPM within a few months if you practice _every day_. That's at least _doubling_ one's typing speed!

(_Edit_: This isn't to suggest that efficient coding has much to do with how fast you can type, but rather that this reduces the repetitive task of looking for unnaturally-placed characters on the keyboard.)

_Some fun: [play.typeracer.com](http://play.typeracer.com/)_

**Master a text editor**

I started forcing myself to use Vim last year and have since gotten faster editing with it than with any other text editor. Vim comes installed with `vimtutor`, a classic interactive tutorial for the editor.

The common thread in a lot of these micro-optimizations is keeping your fingers on the keyboard and away from the mouse.
<br>
<br>
_What are your favorite optimizations? Feel free to DM or tweet [@rainieratx](https://twitter.com/rainieratx) with corrections and suggestions._



In my parallel computing class this semester, we have to write reports with timing results and some analysis using LaTeX. Since we already cook up Makefiles to compile our MPI C programs, why don't we construct our reports the same way too?

Here is a Makefile I wrote to compile my programs and construct the PDF for my report:

```make
LATEXTMP=*.aux *.log *.toc
EXECS=ex6 ex7
MPICC?=mpicc
LATEXCMP=pdflatex

all: ${EXECS}

ex6: ex6.c
    ${MPICC} -o ex6 ex6.c

ex7: ex7.c
    ${MPICC} -o ex7 ex7.c

report: report.tex
    ${LATEXCMP} report.tex

clean:
    rm ${EXECS} ${LATEXTMP}
```

If you are familiar with Make, this set of rules should be fairly straightforward to follow. I also find this useful for getting rid of the temporary files that pdflatex generates, without say, fat-fingering a regex upon `rm`.

If this is new to you, the [GNU Make Manual](https://www.gnu.org/software/make/manual/make.html#Introduction) is a well-written tutorial to start.

Make Make great again! 😛

_What kind of automation tools do you use for tasks that aren't typically automated?_



I didn't really talk before I was 4 years old. In fact, I learned how to read before I could converse with others. According to my parents, a doctor said that I would have to attend a special school for not knowing how to speak properly.

Some kind of speech impediment carried on through the beginning of high school. I stuttered whenever I was in social situations, even the most casual ones, and still do occasionally. The following is a list of things that have particularly helped me overcome stuttering.

**Joining the debate team**. I wanted to _decimate_ my stuttering. The first time I walked into the debate classroom, I watched our school's two senior A-debaters _spread_, or "speed read", about nuclear weapon possession policies at over 300 WPM.

*(Aside: The reason why debaters talk really fast is because their speeches are time-constrained, and they need to develop arguments as efficiently as possible. This is the nearly *pure-logos* model of debate that is present in many competitive debate circuits. Some people think it is bad, and others think it is good. I would argue that it is good because it fosters critical thinking skills (the human brain can process up to 800 WPM, BTW), creates time for arguments to be developed more thoroughly, and even if there were a good reason for it being bad, the best debaters still have to "adapt" their style to the many "lay" judges who prefer more pathos and slower talking anyway.)*

I thought debate was cool. It was a domain outside of the sciences that I wasn't good at yet (I was terrible for a while), and it was very competitive. The camaraderie and trophies were thrilling, and I got to be out of town nearly every weekend. **I ended up qualifying for debate nationals in 12th grade and [teaching high schoolers](https://youtu.be/jawI1nBR_9E?t=6m57s) how to debate** at UT Austin's camp that summer, so it was an early resume-padder too.

Due to the research that debate evidence required, I picked up a lot of random domain knowledge in politics, philosophy and argumentation. Most importantly though, it helped me to be a more logical and persuasive communicator, a trait that has become indispensible in my career. **From speaking to recruiters to career fair, talking my way through techincal interviews with engineers, to making friends in college**, I would have a significantly different experience if it weren't for speech and debate.

**Playing games**. My friends introduced the game of [Taboo](<https://en.wikipedia.org/wiki/Taboo_(game)>) to me in 12th grade, and I was hooked. Players have their partners guess the word on the player's card without using the word itself or five additional words listed on the card. I liked it a lot because it forced me to describe ideas with both time and strict word constraints. I also started playing [Catch Phrase](<https://en.wikipedia.org/wiki/Catch_Phrase_(game)>) last summer, which has similar rules with more lax constraints. I have had a lot of fun with this game in particular, so much that I've been itching to code it up or discuss various tactics in depth.

Finally, I came up with this sort of ironic game while my girlfriend and I were out for dinner. While waiting for her, I went to the first link when Googling "funny long jokes". This "game" involves looking up a funny long joke (typically a story), summarizing it in your head, recalling its details without referencing the text, and delivering it (even embellishing it) in a way that people will "get". It's fantastic because it's fun socializing practice (however shallow it is 😛), and it also builds up your short-term memory.

_Can you think of other ways to improve speech?_



In 2015 I...

**"Figured out" the kind of people I want to spend time with.** It's a well-known adage that "you are the average of the top five people you spend time with". Ignoring cases like, raising four babies or something, there is definitely some truth to this in college. In Fall 2014, I joined two student orgs. In one of them, I quickly figured out that the majority were mainly preoccupied with gossip and padding their resumes, so I did not re-apply to be a member the next semester. The other was [Lambda Alpha Nu](https://texaslan.org), a brand-new co-ed tech-interest fraternity. I was in the very first "Alpha Class" following its establishment.

The organization has left a huge impact on my career aspirations. With the founders (now alumni) working at high-impact tech companies and beginning startups, I feel like a career dedicated to computer science is my opportunity to optimize the balance between largest net positive impact on the world and my own personal enjoyment of the field during my relatively short time here on Earth.

**Got lucky and had a lot of interviews.** From the entire year, I completed 31 interviews and 4 coding challenges. Over two-dozen of them were during September and October 2015.

Truth be told, it was a less-than-optimal strategy! But I knew that I wouldn't practice or gain confidence unless I actually interviewed with companies, no matter how much I actually wanted to work for them.

**Went to the Bay Area three times and the Northeast once.** I had the privilege of traveling out of state several times in 2015. I flew out for 2 interviews and 2 hackathons.

In late March I went to [Weebly](http://officesnapshots.com/2015/08/17/weebly-san-francisco-offices/)'s beautiful office in San Francisco for an on-site trial for their software engineering internship. Considering I had never made a web app backend before 🙃, this was a _huge_ learning experience. Needless to say, I wasn't extended an offer, but it was an experience that _really_ inspired me to try to get an internship in the Bay Area.

As an early 20th birthday present from my parents, I visited the [6Sense](https://6sense.com/) HQ in the heart of [SoMa](https://www.google.com/maps/d/u/0/viewer?mid=z0K33fLxahaU.kMBt4r4w_lUI&hl=en) to attend their first data science-oriented hackathon! I had a lovely experience and it was the first hackathon where I won a prize. They even got me [cake](https://www.instagram.com/p/6tudxgJgxx/) for my birthday.

In November, I went to the [Clover](https://clover.com) HQ in Sunnyvale for the 1st Annual Clover Network Invitational! From Thursday through Saturday we:

- Had two practice interviews with immediate feedback followed by the real interview on the last day.
- Had a resume-building workshop where I was fortunate enough to be reviewed by their head of product!
- Hacked with a few other students and one of the Clover engineers, a UTCS alum!
- Gorged on catered lunches and dinners, followed by adventures in SF and more food.

The week after Clover, I went to a small school in Princeton, NJ to participate in HackPrinceton. It helped reinforce my belief that if the endgame is working at \$COOL*TECH_COMPANY, starting a successful startup, or building an awesome network, you don't *have* to be at an Ivy, I was in a good place all along! But even more importantly, I realized how important resources and a network is to young engineers, better understood how \_privileged* I am without patting myself on the back, but also how good it feels to be a mentor.

**Went to a lot of hackathons.** Nine, to be exact. A large reason of why I went to a lot of hackathons earlier this year is because I felt somewhat behind. I started learning how to code in September 2014 when I began my computer science major, and when I joined Lambda Alpha Nu, I felt behind as a lot of my new friends were landing all these glamorous internships. Understandably, they had been coding much longer than I have, and because of how time works, will always have been coding longer than I have, as long as all of us are alive. But after this interview season and coding nearly every day of my life this year, I feel confident enough to try to be a mentor more often.

- **HackDFW 2015** - worked on MakeRoute, a PHP/MySQL web app that determines nice restaurants on the route between two places.
- **SXSW Music Hackathon** - worked on an Android app that filters an Rdio API playlist based on your heart rate determined by the Microsoft Band.
- **ATX Hack4Change Civic Hackathon** - worked on an Android backend with Parse and game logic for a collection of nutrition-oriented games aimed at toddlers, called Monstralia by the HealthStart Foundation.
- **athenahealth MDP Hackathon** - worked on HealthCruncher, a Python/Flask web API that calculates heart disease and diabetes predisposition probability with a basic machine learning model.
- **6Sense DataHack** - built text-graph/"Fran", a library for parsing text backup files and generating a weighted graph based on people they mentioned in texts.
- **HackTX 2015** - I played around with the Yelp dataset and learned how to use RethinkDB, a key-value store that is probably better than MongoDB.
- **Clover Network Invitational** - See above.
- **HackPrinceton 2015** - built Feelsbook. I teamed up with two NYU engineering freshmen named Claryssa and Minah who were hackathon newbies to help them get their feet wet in web development. We built a Python/Flask-based social networking site-like newsfeed that pooled data from the Indico, Clarifai, and Microsoft facial emotion recognition APIs to ask the user just what _exactly_ was on their mind, whether something was wrong, what made them joyful, and so on, and filtered tweets based on their face as well.

The hackathon community's been so instrumental in my development that I decided to join the leadership team for HackTX, which was my very first hackathon in 2014 (when I had just learned about for-loops). The organizing community of HackTX are all very amazing people.

I had a very productive, mindful, and _lucky_ 2015. In 2016, I want to be humbler, feel more secure about my abilities (which involves improving them), maintain and create honest, impactful relationships with people.

_How was your 2015, and what are your plans for 2015 + 1?_



### Well, maybe a little bit of profit.

**text-graph** is a data visualization of a network graph of based on 18,000 texts, with weighted edges representing sentiment degree between named entities.

This is a port of a write-up for a project I made at 6Sense Data Hack in San Francisco. This won _Judges' Favorite Hack_ and my round-trip flight ticket's (AUS - SFO) worth, which is why I said a little bit of profit. It was also featured on their [company blog](https://6sense.com/2015/08/datahack-2015-65-coders-14-teams-and-a-lot-of-data/).

## Setup

For a lot of data science-oriented tasks, the [Anaconda](https://www.anaconda.com/distribution/) distribution of Python will be awesome. [PyCharm](https://www.jetbrains.com/pycharm/) for static type-checking and quickly accessing docstrings, since I'm using a lot of unfamiliar libraries.

## Data wrangling

- Grab texts from Go SMS Pro (an alternative text-messaging app) backups (XML format)
- Parse XML tree using `cElementTree` from the `xml` Python lib to get contact names, text, etc.
- Create in-memory data structures in Python using data from the XML tree:

```python
class TextCorpus(object):
    """It's a graph."""

    def __init__(self):
        self.contacts = get_contact_objs()
        self.contact_names = names.values()
        self.global_adj_list = [item for sublist in
                                            map(lambda x: getattr(x, 'adj_list'), self.contacts)
                                                for item in sublist]
        self.global_pair_map = dict(zip(map(lambda x: getattr(x, 'name'), self.contacts),
                                                map(lambda x: getattr(x, 'adj_list'), self.contacts)))
        self.global_pair_flat_list = map(lambda x: getattr(x, 'adj_list'), self.contacts)

class Contact(object):
    """A Contact obj reprs one of the people I've contacted."""

    def __init__(self, fn):
        self.name = get_name_from_fn(fn)
        self.messages = get_texts(fn, False)
        self.messages_str_list = map(lambda x: getattr(x, 'body'), self.messages)
        self.links = get_mentions_msg_list(self.messages_as_str_list)
        self.unweighted_links = tuple(set(get_mentions_msg_list(self.messages_as_str_list)))
        self.weighted_links = Counter(get_mentions_msg_list(self.messages_as_str_list))
        self.adjacency_list = map(lambda x: tuple([self.name, x]),
                                            list(set(get_mentions_msg_list(self.messages_as_str_list))))
        self.sentiment_links = get_sentiment_link_dict(self.weighted_links, self.name)
        self.avg_sentiment = 0.5 if len(self.sentiment_links) is 0
                                 else float(sum(self.sentiment_links.values())) / len(self.sentiment_links)
```

## Anonymizing data

There's definitely a concern for privacy since these are texts between my friends...

For each `Contact` in `TextCorpus`, grab their `TextMessage` objs. If a contact name is in the body of the text, perform a hex digest of the name and `humanize` the hash.

```python
import humanhash
import hashlib

class TextMessage(object):
    """A TextMessage obj's attrs correspond to the XML tags I care about."""

    def __init__(self, msg_id, posix, sent, body, sender):
        self.msg_id = msg_id
        self.posix = posix
        self.sent = sent
        self.body = 'neutral' if body is None else anonymize(body.lower())
        self.mentions = get_mentions(self.body)
        self.sender = sender if self.sent is False else 'rainier'

def anonymize(msg):
    """Anonymizes a single text body.
    e.g. 'Alice: Bob is awesome' -> 'zero-phone-quantum-anchorage: waffle-panda-theory-rushmore is awesome'
    """
    for orig, hmhashed in names.iteritems():
        msg = msg.replace(orig, hmhashed)
    return msg

def digest_and_humanize(word):
    m = hashlib.md5()
    m.update(word)
    return humanhash.humanize(m.hexdigest())
```

## Sentiment analysis

In the interest of time at the hackathon, I used pre-trained models from [Indico](http://indico.io)'s high-quality sentiment API on short texts. They report about a 93% accuracy rate on the IMDB movie review corpus.

_Aside: There are lots of papers and tutorials on sentiment analysis algorithms using machine learning. Some 'not really machine learning' methods involve using a list of 'happy' words such as 'awesome' and 'great' to increase the sentiment. Could also classifiers such as Naïve Bayes or topic modeling techniques_. But anyway...

Since I can only freely hit the Indico API 100,000 times, I had to find a way to store API call results persistently, and also unit test. I could have used a database, but for now, `pandas` has good tools for parsing CSVs.

```python
from texts.config import INDICO_API_KEY

def indico_batch_sentiment():
    """a ONE-OFF method to call the indico.io API to HQ batch sentiment 18192 texts.

    Stores it as sentiments.csv in the working dir.
    """
    with open('sentiments.csv', 'wb') as f:
        texts = []
        writer = csv.writer(f)
        with open('texts/filenames.txt', 'r') as filenames:
            fn_list = map(str.strip, [filename for filename in filenames])
            fn_list = map(lambda x: 'texts/texts/' + x, fn_list)
            for fn in fn_list:
                texts.append(get_texts(fn)) # returns TextMessage object
        texts = [item for sublist in texts for item in sublist]
        with open('indico_sentiment_hq_errors.txt', 'w') as error_log:
            for text in texts:
                sentiment_result = None
                try:
                    sentiment_result = sentiment_hq(text.body.encode(), api_key=INDICO_API_KEY)
                except BaseException as e:
                    error_log.write(str(e))
                finally:
                    writer.writerow([unicode(s).encode('utf-8') for s in
                                     [text.msg_id, text.posix, repr(text.sent),
                                      text.body, repr(text.mentions), sentiment_result]])
```

## Static visualization

![Graph viz should be here](/images/text-graph.png)

## Ways to improve

- Didn't include emoji 👀 or use a different encoding for them because it was breaking Python's standard library csv file IO. Of course, I was going back and forth between `pandas` and `csvfile`. Could be factored into sentiment somehow...
- I have a contact named Will... maybe y'all could guess what happened then, or what _will_ happen if people use that word...
- I could have gotten Facebook's data dump or backed up all my texts from this year as well. But I think at like 18200 texts my computer could handle enough. For a larger scale operation I could use an AWS instance or something.

The code is [here](https://github.com/rainiera/text-graph). Even though I haven't touched it in a while, I'm always dreaming of things to add on to it.
