More on Productivity

Todd Lewandowski
3 years ago
DWTS: How to Organize Your To-Do List Quickly
Don't overcomplicate to-do lists. DWTS (Done, Waiting, Top 3, Soon) organizes your to-dos.
How Are You Going to Manage Everything?
Modern America is busy. Work involves meetings. Anytime, Slack communications arrive. Many software solutions offer a @-mention notification capability. Emails.
Work obligations continue. At home, there are friends, family, bills, chores, and fun things.
How are you going to keep track of it all? Enter the todo list. It’s been around forever. It’s likely to stay forever in some way, shape, or form.
Everybody has their own system. You probably modified something from middle school. Post-its? Maybe it’s an app? Maybe both, another system, or none.
I suggest a format that has worked for me in 15 years of professional and personal life.
Try it out and see if it works for you. If not, no worries. You do you! Hopefully though you can learn a thing or two, and I from you too.
It is merely a Google Doc, yes.
It's a giant list. One task per line. Indent subtasks on a new line. Add or move new tasks as needed.
I recommend using Google Docs. It's easy to use and flexible for structuring.
Prioritizing these tasks is key. I organize them using DWTS (Done, Waiting, Top 3, Soon). Chronologically is good because it implicitly provides both a priority (high, medium, low) and an ETA (now, soon, later).
Yes, I recognize the similarities to DWTS (Dancing With The Stars) TV Show. Although I'm not a fan, it's entertaining. The acronym is easy to remember and adds fun to something dull.
What each section contains
Done
All tasks' endpoint. Finish here. Don't worry about it again.
Waiting
You're blocked and can't continue. Blocked tasks usually need someone. Write Person Task so you know who's waiting.
Blocking tasks shouldn't last long. After a while, remind them kindly. If people don't help you out of kindness, they will if you're persistent.
Top 3
Mental focus areas. These can be short- to mid-term goals or recent accomplishments. 2 to 5 is a good number to stay focused.
Top 3 reminds us to prioritize. If they don't fit your Top 3 goals, delay them.
Every 1:1 at work is a project update. Another chance to list your top 3. You should know your Top 3 well and be able to discuss them confidently.
Soon
Here's your short-term to-do list. Rank them from highest to lowest.
I usually subdivide it with empty lines. First is what I have to do today, then week, then month. Subsections can be arranged however you like.
Inventories by Concept
Tasks that aren’t in your short or medium future go into the backlog.
Eventually you’ll complete these tasks, assign them to someone else, or mark them as “wont’ do” (like done but in another sense).
Backlog tasks don't need to be organized chronologically because their timing and priority may change. Theme-organize them. When planning/strategic, you can choose themes to focus on, so future top 3 topics.
More Tips on Todos
Decide Upon a Morning Goal
Morning routines are universal. Coffee and Wordle. My to-do list is next. Two things:
As needed, update the to-do list: based on the events of yesterday and any fresh priorities.
Pick a few jobs to complete today: Pick a few goals that you know you can complete today. Push the remainder below and move them to the top of the Soon section. I typically select a few tasks I am confident I can complete along with one stretch task that might extend into tomorrow.
Finally. By setting and achieving small goals every day, you feel accomplished and make steady progress on medium and long-term goals.
Tech companies call this a daily standup. Everyone shares what they did yesterday, what they're doing today, and any blockers. The name comes from a tradition of holding meetings while standing up to keep them short. Even though it's virtual, everyone still wants a quick meeting.
Your team may or may not need daily standups. Make a daily review a habit with your coffee.
Review Backwards & Forwards on a regular basis
While you're updating your to-do list daily, take time to review it.
Review your Done list. Remember things you're proud of and things that could have gone better. Your Done list can be long. Archive it so your main to-do list isn't overwhelming.
Future-gaze. What you considered important may no longer be. Reorder tasks. Backlog grooming is a workplace term.
Backwards-and-forwards reviews aren't required often. Every 3-6 months is fine. They help you see the forest as often as the trees.
Final Remarks
Keep your list simple. Done, Waiting, Top 3, Soon. These are the necessary sections. If you like, add more subsections; otherwise, keep it simple.
I recommend a morning review. By having clear goals and an action-oriented attitude, you'll be successful.

Ethan Siegel
2 years ago
How you view the year will change after using this one-page calendar.
No other calendar is simpler, smaller, and reusable year after year. It works and is used here.
Most of us discard and replace our calendars annually. Each month, we move our calendar ahead another page, thus if we need to know which day of the week corresponds to a given day/month combination, we have to calculate it or flip forward/backward to the corresponding month. Questions like:
What day does this year's American Thanksgiving fall on?
Which months contain a Friday the thirteenth?
When is July 4th? What day of the week?
Alternatively, what day of the week is Christmas?
They're hard to figure out until you switch to the right month or look up all the months.
However, mathematically, the answers to these questions or any question that requires matching the day of the week with the day/month combination in a year are predictable, basic, and easy to work out. If you use this one-page calendar instead of a 12-month calendar, it lasts the whole year and is easy to alter for future years. Let me explain.
The 2023 one-page calendar is above. The days of the month are on the lower left, which works for all months if you know that:
There are 31 days in January, March, May, July, August, October, and December.
All of the months of April, June, September, and November have 30 days.
And depending on the year, February has either 28 days (in non-leap years) or 29 days (in leap years).
If you know this, this calendar makes it easy to match the day/month of the year to the weekday.
Here are some instances. American Thanksgiving is always on the fourth Thursday of November. You'll always know the month and day of the week, but the date—the day in November—changes each year.
On any other calendar, you'd have to flip to November to see when the fourth Thursday is. This one-page calendar only requires:
pick the month of November in the top-right corner to begin.
drag your finger down until Thursday appears,
then turn left and follow the monthly calendar until you reach the fourth Thursday.
It's obvious: 2023 is the 23rd American Thanksgiving. For every month and day-of-the-week combination, start at the month, drag your finger down to the desired day, and then move to the left to see which dates match.
What if you knew the day of the week and the date of the month, but not the month(s)?
A different method using the same one-page calendar gives the answer. Which months have Friday the 13th this year? Just:
begin on the 13th of the month, the day you know you desire,
then swipe right with your finger till Friday appears.
and then work your way up until you can determine which months the specific Friday the 13th falls under.
One Friday the 13th occurred in January 2023, and another will occur in October.
The most typical reason to consult a calendar is when you know the month/day combination but not the day of the week.
Compared to single-month calendars, the one-page calendar excels here. Take July 4th, for instance. Find the weekday here:
beginning on the left on the fourth of the month, as you are aware,
also begin with July, the month of the year you are most familiar with, at the upper right,
you should move your two fingers in the opposite directions till they meet: on a Tuesday in 2023.
That's how you find your selected day/month combination's weekday.
Another example: Christmas. Christmas Day is always December 25th, however unless your conventional calendar is open to December of your particular year, a question like "what day of the week is Christmas?" difficult to answer.
Unlike the one-page calendar!
Remember the left-hand day of the month. Top-right, you see the month. Put two fingers, one from each hand, on the date (25th) and the month (December). Slide the day hand to the right and the month hand downwards until they touch.
They meet on Monday—December 25, 2023.
For 2023, that's fine, but what happens in 2024? Even worse, what if we want to know the day-of-the-week/day/month combo many years from now?
I think the one-page calendar shines here.
Except for the blue months in the upper-right corner of the one-page calendar, everything is the same year after year. The months also change in a consistent fashion.
Each non-leap year has 365 days—one more than a full 52 weeks (which is 364). Since January 1, 2023 began on a Sunday and 2023 has 365 days, we immediately know that December 31, 2023 will conclude on a Sunday (which you can confirm using the one-page calendar) and that January 1, 2024 will begin on a Monday. Then, reorder the months for 2024, taking in mind that February will have 29 days in a leap year.
Please note the differences between 2023 and 2024 month placement. In 2023:
October and January began on the same day of the week.
On the following Monday of the week, May began.
August started on the next day,
then the next weekday marked the start of February, March, and November, respectively.
Unlike June, which starts the following weekday,
While September and December start on the following day of the week,
Lastly, April and July start one extra day later.
Since 2024 is a leap year, February has 29 days, disrupting the rhythm. Month placements change to:
The first day of the week in January, April, and July is the same.
October will begin the following day.
Possibly starting the next weekday,
February and August start on the next weekday,
beginning on the following day of the week between March and November,
beginning the following weekday in June,
and commencing one more day of the week after that, September and December.
Due to the 366-day leap year, 2025 will start two days later than 2024 on January 1st.
Now, looking at the 2025 calendar, you can see that the 2023 pattern of which months start on which days is repeated! The sole variation is a shift of three days-of-the-week ahead because 2023 had one more day (365) than 52 full weeks (364), and 2024 had two more days (366). Again,
On Wednesday this time, January and October begin on the same day of the week.
Although May begins on Thursday,
August begins this Friday.
March, November, and February all begin on a Saturday.
Beginning on a Sunday in June
Beginning on Monday are September and December,
and on Tuesday, April and July begin.
In 2026 and 2027, the year will commence on a Thursday and a Friday, respectively.
We must return to our leap year monthly arrangement in 2028. Yes, January 1, 2028 begins on a Saturday, but February, which begins on a Tuesday three days before January, will have 29 days. Thus:
Start dates for January, April, and July are all Saturdays.
Given that October began on Sunday,
Although May starts on a Monday,
beginning on a Tuesday in February and August,
Beginning on a Wednesday in March and November,
Beginning on Thursday, June
and Friday marks the start of September and December.
This is great because there are only 14 calendar configurations: one for each of the seven non-leap years where January 1st begins on each of the seven days of the week, and one for each of the seven leap years where it begins on each day of the week.
The 2023 calendar will function in 2034, 2045, 2051, 2062, 2073, 2079, 2090, 2102, 2113, and 2119. Except when passing over a non-leap year that ends in 00, like 2100, the repeat time always extends to 12 years or shortens to an extra 6 years.
The pattern is repeated in 2025's calendar in 2031, 2042, 2053, 2059, 2070, 2081, 2087, 2098, 2110, and 2121.
The extra 6-year repeat at the end of the century on the calendar for 2026 will occur in the years 2037, 2043, 2054, 2065, 2071, 2082, 2093, 2099, 2105, and 2122.
The 2027s calendar repeats in 2038, 2049, 2055, 2066, 2077, 2083, 2094, 2100, 2106, and 2117, almost exactly matching the 2026s pattern.
For leap years, the recurrence pattern is every 28 years when not passing a non-leap year ending in 00, or 12 or 40 years when we do. 2024's calendar repeats in 2052, 2080, 2120, 2148, 2176, and 2216; 2028's in 2056, 2084, 2124, 2152, 2180, and 2220.
Knowing January 1st and whether it's a leap year lets you construct a one-page calendar for any year. Try it—you might find it easier than any other alternative!

Jon Brosio
3 years ago
Every time I use this 6-part email sequence, I almost always make four figures.
(And you can have it for free)
Master email to sell anything.
Most novice creators don't know how to begin.
Many use online templates. These are usually fluff-filled and niche-specific.
They're robotic and "salesy."
I've attended 3 courses, read 10 books, and sent 600,000 emails in the past five years.
Outcome?
This *proven* email sequence assures me a month's salary every time I send it.
What you will discover in this article is that:
A full 6-part email sales cycle
The essential elements you must incorporate
placeholders and text-filled images
(Applies to any niche)
This can be a product introduction, holiday, or welcome sequence. This works for email-saleable products.
Let's start
Email 1: Describe your issue
This email is crucial.
How to? We introduce a subscriber or prospect's problem. Later, we'll frame our offer as the solution.
Label the:
Problem
Why it still hasn't been fixed
Resulting implications for the customer
This puts our new subscriber in solve mode and queues our offer:
Email 2: Amplify the consequences
We're still causing problems.
We've created the problem, but now we must employ emotion and storytelling to make it real. We also want to forecast life if nothing changes.
Let's feel:
What occurs if it is not resolved?
Why is it crucial to fix it immediately?
Tell a tale of a person who was in their position. To emphasize the effects, use a true account of another person (or of yourself):
Email 3: Share a transformation story
Selling stories.
Whether in an email, landing page, article, or video. Humanize stories. They give information meaning.
This is where "issue" becomes "solution."
Let's reveal:
A tale of success
A new existence and result
tools and tactics employed
Start by transforming yourself.
Email 4: Prove with testimonials
No one buys what you say.
Emotionally stirred people buy and act. They believe in the product. They feel that if they buy, it will work.
Social proof shows prospects that your solution will help them.
Add:
Earlier and Later
Testimonials
Reviews
Proof this deal works:
Email 5: Reveal your offer
It's showtime.
This is it. Until now, describing the offer and offering links to a landing page have been sparse in the email pictures.
We've been tense. Gaining steam. Building suspense. Email 5 reveals all.
In this email:
a description of the deal
A word about a promise
recapitulation of the transformation
and make a reference to the urgency Everything should be spelled out clearly:
Email no. 6: Instill urgency
When there are stakes, humans act.
Creating and marketing with haste raises the stakes. Urgency makes a prospect act because they'll miss out or gain immensely.
Urgency converts. Use:
short time
Screening
Scarcity
Urgency and conversions. Limited-time offers are easy.
TL;DR
Use this proven 6-part email sequence (that turns subscribers into profit):
Introduce a problem
Amplify it with emotions
Share transformation story
Prove it works with testimonials
Value-stack and present your offer
Drive urgency and entice the purchase
You might also like

Nabil Alouani
3 years ago
Why Cryptocurrency Is Not Dead Despite the FTX Scam
A fraud, free-market, antifragility tale
Crypto's only rival is public opinion.
In less than a week, mainstream media, bloggers, and TikTokers turned on FTX's founder.
While some were surprised, almost everyone with a keyboard and a Twitter account predicted the FTX collapse. These financial oracles should have warned the 1.2 million people Sam Bankman-Fried duped.
After happening, unexpected events seem obvious to our brains. It's a bug and a feature because it helps us cope with disasters and makes our reasoning suck.
Nobody predicted the FTX debacle. Bloomberg? Politicians. Non-famous. No cryptologists. Who?
When FTX imploded, taking billions of dollars with it, an outrage bomb went off, and the resulting shockwave threatens the crypto market's existence.
As someone who lost more than $78,000 in a crypto scam in 2020, I can only understand people’s reactions. When the dust settles and rationality returns, we'll realize this is a natural occurrence in every free market.
What specifically occurred with FTX? (Skip if you are aware.)
FTX is a cryptocurrency exchange where customers can trade with cash. It reached #3 in less than two years as the fastest-growing platform of its kind.
FTX's performance helped make SBF the crypto poster boy. Other reasons include his altruistic public image, his support for the Democrats, and his company Alameda Research.
Alameda Research made a fortune arbitraging Bitcoin.
Arbitrage trading uses small price differences between two markets to make money. Bitcoin costs $20k in Japan and $21k in the US. Alameda Research did that for months, making $1 million per day.
Later, as its capital grew, Alameda expanded its trading activities and began investing in other companies.
Let's now discuss FTX.
SBF's diabolic master plan began when he used FTX-created FTT coins to inflate his trading company's balance sheets. He used inflated Alameda numbers to secure bank loans.
SBF used money he printed himself as collateral to borrow billions for capital. Coindesk exposed him in a report.
One of FTX's early investors tweeted that he planned to sell his FTT coins over the next few months. This would be a minor event if the investor wasn't Binance CEO Changpeng Zhao (CZ).
The crypto space saw a red WARNING sign when CZ cut ties with FTX. Everyone with an FTX account and a brain withdrew money. Two events followed. FTT fell from $20 to $4 in less than 72 hours, and FTX couldn't meet withdrawal requests, spreading panic.
SBF reassured FTX users on Twitter. Good assets.
He lied.
SBF falsely claimed FTX had a liquidity crunch. At the time of his initial claims, FTX owed about $8 billion to its customers. Liquidity shortages are usually minor. To get cash, sell assets. In the case of FTX, the main asset was printed FTT coins.
Sam wouldn't get out of trouble even if he slashed the discount (from $20 to $4) and sold every FTT. He'd flood the crypto market with his homemade coins, causing the price to crash.
SBF was trapped. He approached Binance about a buyout, which seemed good until Binance looked at FTX's books.
Binance's tweet ended SBF, and he had to apologize, resign as CEO, and file for bankruptcy.
Bloomberg estimated Sam's net worth to be zero by the end of that week. 0!
But that's not all. Twitter investigations exposed fraud at FTX and Alameda Research. SBF used customer funds to trade and invest in other companies.
Thanks to the Twitter indie reporters who made the mainstream press look amateurish. Some Twitter detectives didn't sleep for 30 hours to find answers. Others added to existing threads. Memes were hilarious.
One question kept repeating in my bald head as I watched the Blue Bird. Sam, WTF?
Then I understood.
SBF wanted that FTX becomes a bank.
Think about this. FTX seems healthy a few weeks ago. You buy 2 bitcoins using FTX. You'd expect the platform to take your dollars and debit your wallet, right?
No. They give I-Owe-Yous.
FTX records owing you 2 bitcoins in its internal ledger but doesn't credit your account. Given SBF's tricks, I'd bet on nothing.
What happens if they don't credit my account with 2 bitcoins? Your money goes into FTX's capital, where SBF and his friends invest in marketing, political endorsements, and buying other companies.
Over its two-year existence, FTX invested in 130 companies. Once they make a profit on their purchases, they'll pay you and keep the rest.
One detail makes their strategy dumb. If all FTX customers withdraw at once, everything collapses.
Financially savvy people think FTX's collapse resembles a bank run, and they're right. SBF designed FTX to operate like a bank.
You expect your bank to open a drawer with your name and put $1,000 in it when you deposit $1,000. They deposit $100 in your drawer and create an I-Owe-You for $900. What happens to $900?
Let's sum it up: It's boring and headache-inducing.
When you deposit money in a bank, they can keep 10% and lend the rest. Fractional Reserve Banking is a popular method. Fractional reserves operate within and across banks.
Fractional reserve banking generates $10,000 for every $1,000 deposited. People will pay off their debt plus interest.
As long as banks work together and the economy grows, their model works well.
SBF tried to replicate the system but forgot two details. First, traditional banks need verifiable collateral like real estate, jewelry, art, stocks, and bonds, not digital coupons. Traditional banks developed a liquidity buffer. The Federal Reserve (or Central Bank) injects massive cash into troubled banks.
Massive cash injections come from taxpayers. You and I pay for bankers' mistakes and annual bonuses. Yes, you may think banking is rigged. It's rigged, but it's the best financial game in 150 years. We accept its flaws, including bailouts for too-big-to-fail companies.
Anyway.
SBF wanted Binance's bailout. Binance said no, which was good for the crypto market.
Free markets are resilient.
Nassim Nicholas Taleb coined the term antifragility.
“Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile. Let us call it antifragile. Antifragility is beyond resilience or robustness. The resilient resists shocks and stays the same; the antifragile gets better.”
The easiest way to understand how antifragile systems behave is to compare them with other types of systems.
Glass is like a fragile system. It snaps when shocked.
Similar to rubber, a resilient system. After a stressful episode, it bounces back.
A system that is antifragile is similar to a muscle. As it is torn in the gym, it gets stronger.
Time-changed things are antifragile. Culture, tech innovation, restaurants, revolutions, book sales, cuisine, economic success, and even muscle shape. These systems benefit from shocks and randomness in different ways, but they all pay a price for antifragility.
Same goes for the free market and financial institutions. Taleb's book uses restaurants as an example and ends with a reference to the 2008 crash.
“Restaurants are fragile. They compete with each other. But the collective of local restaurants is antifragile for that very reason. Had restaurants been individually robust, hence immortal, the overall business would be either stagnant or weak and would deliver nothing better than cafeteria food — and I mean Soviet-style cafeteria food. Further, it [the overall business] would be marred with systemic shortages, with once in a while a complete crisis and government bailout.”
Imagine the same thing with banks.
Independent banks would compete to offer the best services. If one of these banks fails, it will disappear. Customers and investors will suffer, but the market will recover from the dead banks' mistakes.
This idea underpins a free market. Bitcoin and other cryptocurrencies say this when criticizing traditional banking.
The traditional banking system's components never die. When a bank fails, the Federal Reserve steps in with a big taxpayer-funded check. This hinders bank evolution. If you don't let banking cells die and be replaced, your financial system won't be antifragile.
The interdependence of banks (centralization) means that one bank's mistake can sink the entire fleet, which brings us to SBF's ultimate travesty with FTX.
FTX has left the cryptocurrency gene pool.
FTX should be decentralized and independent. The super-star scammer invested in more than 130 crypto companies and linked them, creating a fragile banking-like structure. FTX seemed to say, "We exist because centralized banks are bad." But we'll be good, unlike the centralized banking system.
FTX saved several companies, including BlockFi and Voyager Digital.
FTX wanted to be a crypto bank conglomerate and Federal Reserve. SBF wanted to monopolize crypto markets. FTX wanted to be in bed with as many powerful people as possible, so SBF seduced politicians and celebrities.
Worst? People who saw SBF's plan flaws praised him. Experts, newspapers, and crypto fans praised FTX. When billions pour in, it's hard to realize FTX was acting against its nature.
Then, they act shocked when they realize FTX's fall triggered a domino effect. Some say the damage could wipe out the crypto market, but that's wrong.
Cell death is different from body death.
FTX is out of the game despite its size. Unfit, it fell victim to market natural selection.
Next?
The challengers keep coming. The crypto economy will improve with each failure.
Free markets are antifragile because their fragile parts compete, fostering evolution. With constructive feedback, evolution benefits customers and investors.
FTX shows that customers don't like being scammed, so the crypto market's health depends on them. Charlatans and con artists are eliminated quickly or slowly.
Crypto isn't immune to collapse. Cryptocurrencies can go extinct like biological species. Antifragility isn't immortality. A few more decades of evolution may be enough for humans to figure out how to best handle money, whether it's bitcoin, traditional banking, gold, or something else.
Keep your BS detector on. Start by being skeptical of this article's finance-related claims. Even if you think you understand finance, join the conversation.
We build a better future through dialogue. So listen, ask, and share. When you think you can't find common ground with the opposing view, remember:
Sam Bankman-Fried lied.

Farhad Malik
3 years ago
How This Python Script Makes Me Money Every Day
Starting a passive income stream with data science and programming
My website is fresh. But how do I monetize it?
Creating a passive-income website is difficult. Advertise first. But what useful are ads without traffic?
Let’s Generate Traffic And Put Our Programming Skills To Use
SEO boosts traffic (Search Engine Optimisation). Traffic generation is complex. Keywords matter more than text, URL, photos, etc.
My Python skills helped here. I wanted to find relevant, Google-trending keywords (tags) for my topic.
First The Code
I wrote the script below here.
import re
from string import punctuation
import nltk
from nltk import TreebankWordTokenizer, sent_tokenize
from nltk.corpus import stopwords
class KeywordsGenerator:
def __init__(self, pytrends):
self._pytrends = pytrends
def generate_tags(self, file_path, top_words=30):
file_text = self._get_file_contents(file_path)
clean_text = self._remove_noise(file_text)
top_words = self._get_top_words(clean_text, top_words)
suggestions = []
for top_word in top_words:
suggestions.extend(self.get_suggestions(top_word))
suggestions.extend(top_words)
tags = self._clean_tokens(suggestions)
return ",".join(list(set(tags)))
def _remove_noise(self, text):
#1. Convert Text To Lowercase and remove numbers
lower_case_text = str.lower(text)
just_text = re.sub(r'\d+', '', lower_case_text)
#2. Tokenise Paragraphs To words
list = sent_tokenize(just_text)
tokenizer = TreebankWordTokenizer()
tokens = tokenizer.tokenize(just_text)
#3. Clean text
clean = self._clean_tokens(tokens)
return clean
def _clean_tokens(self, tokens):
clean_words = [w for w in tokens if w not in punctuation]
stopwords_to_remove = stopwords.words('english')
clean = [w for w in clean_words if w not in stopwords_to_remove and not w.isnumeric()]
return clean
def get_suggestions(self, keyword):
print(f'Searching pytrends for {keyword}')
result = []
self._pytrends.build_payload([keyword], cat=0, timeframe='today 12-m')
data = self._pytrends.related_queries()[keyword]['top']
if data is None or data.values is None:
return result
result.extend([x[0] for x in data.values.tolist()][:2])
return result
def _get_file_contents(self, file_path):
return open(file_path, "r", encoding='utf-8',errors='ignore').read()
def _get_top_words(self, words, top):
counts = dict()
for word in words:
if word in counts:
counts[word] += 1
else:
counts[word] = 1
return list({k: v for k, v in sorted(counts.items(), key=lambda item: item[1])}.keys())[:top]
if __name__ == "1__main__":
from pytrends.request import TrendReq
nltk.download('punkt')
nltk.download('stopwords')
pytrends = TrendReq(hl='en-GB', tz=360)
tags = KeywordsGenerator(pytrends)\
.generate_tags('text_file.txt')
print(tags)Then The Dependencies
This script requires:
nltk==3.7
pytrends==4.8.0Analysis of the Script
I copy and paste my article into text file.txt, and the code returns the keywords as a comma-separated string.
To achieve this:
A class I made is called KeywordsGenerator.
This class has a function:
generate_tagsThe function
generate_tagsperforms the following tasks:
retrieves text file contents
uses NLP to clean the text by tokenizing sentences into words, removing punctuation, and other elements.
identifies the most frequent words that are relevant.
The
pytrendsAPI is then used to retrieve related phrases that are trending for each word from Google.finally adds a comma to the end of the word list.
4. I then use the keywords and paste them into the SEO area of my website.
These terms are trending on Google and relevant to my topic. My site's rankings and traffic have improved since I added new keywords. This little script puts our knowledge to work. I shared the script in case anyone faces similar issues.
I hope it helps readers sell their work.

Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2
