#monte python

[lethalcontracts]

Remember. Friends dont leave friends behind, just get some rope and drag him. He'll be fiiine.

[foresthuanted]

Pick a movie from the 1970s but I only give you three options

[the-chattering-tower]

I'm doing this at the worst time, but uhh, anyone want some dragons?

First image is all pure progen descendants, ranging from G2 to G5. Second image is randos, mostly just offspring from my pairs that have been ripening since June. Python and Horka are a pair bred only once, and Memory is one of their kids (the other two I kept)

All but the first one (trans coloured pure progen G5) are 10g on the AH for a day, and when their auctions expire, most of them are getting yote as fodder

[fretzine]

Cracking Wordle (kinda) with Monte Carlo Simulations: A Statistical Approach to Predicting the Best Guesses

Wordle, the viral word puzzle game, has captivated millions worldwide with its simple yet challenging gameplay. The thrill of uncovering the five-letter mystery word within six attempts has led to a surge in interest in word strategies and algorithms. In this blog post, we delve into the application of the Monte Carlo method—a powerful statistical technique—to predict the most likely words in Wordle. We will explore what the Monte Carlo method entails, its real-world applications, and a step-by-step explanation of a Python script that harnesses this method to identify the best guesses using a comprehensive list of acceptable Wordle words from GitHub.

Understanding the Monte Carlo Method

What is the Monte Carlo Method?

The Monte Carlo method is a statistical technique that employs random sampling and statistical modeling to solve complex problems and make predictions. Named after the famous Monte Carlo Casino in Monaco, this method relies on repeated random sampling to obtain numerical results, often used when deterministic solutions are difficult or impossible to calculate.

How Does It Work?

At its core, the Monte Carlo method involves running simulations with random variables to approximate the probability of various outcomes. The process typically involves:

Defining a Model: Establishing the mathematical or logical framework of the problem.

Generating Random Inputs: Using random sampling to create multiple scenarios.

Running Simulations: Executing the model with the random inputs to observe outcomes.

Analyzing Results: Aggregating and analyzing the simulation outcomes to draw conclusions or make predictions.

Real-World Applications

The Monte Carlo method is widely used in various fields, including:

Finance: To evaluate risk and uncertainty in stock prices, investment portfolios, and financial derivatives.

Engineering: For reliability analysis, quality control, and optimization of complex systems.

Physics: In particle simulations, quantum mechanics, and statistical mechanics.

Medicine: For modeling the spread of diseases, treatment outcomes, and medical decision-making.

Climate Science: To predict weather patterns, climate change impacts, and environmental risks.

Applying Monte Carlo to Wordle

Objective

In the context of Wordle, our objective is to use the Monte Carlo method to predict the most likely five-letter words that can be the solution to the puzzle. We will simulate multiple guessing scenarios and evaluate the success rates of different words.

Python Code Explanation

Let's walk through the Python script that accomplishes this task.

1. Loading the Word List

First, we need a comprehensive list of acceptable five-letter words used in Wordle. We can obtain the list of all 2315 words that will become the official wordle at some point. The script reads the words from a line-delimited text file and filters them to ensure they are valid.

2. Generating Feedback

To simulate Wordle guesses, we need a function to generate feedback based on the game's rules. This function compares the guessed word to the answer and provides feedback on the correctness of each letter.

3. Simulating Wordle Games

The simulate_wordle function performs the Monte Carlo simulations. For each word in the list, it simulates multiple guessing rounds, keeping track of successful guesses within six attempts.

4. Aggregating Results

The monte_carlo_wordle function aggregates the results from all simulations to determine the most likely words. It also includes progress updates to monitor the percentage of words completed.

5. Running the Simulation

Finally, we load the word list from the text file and run the Monte Carlo simulations. The script prints the top 10 most likely words based on the simulation results.

The Top 50 Words (Based on this approach)

For this article I amended the code so that each simulation runs 1000 times instead of 100 to increase accuracy. I have also amended the script to return the top 50 words. Without further ado, here is the list of words most likely to succeed based on this Monte Carlo method:

trope: 10 successes

dopey: 9 successes

azure: 9 successes

theme: 9 successes

beast: 8 successes

prism: 8 successes

quest: 8 successes

brook: 8 successes

chick: 8 successes

batch: 7 successes

twist: 7 successes

twang: 7 successes

tweet: 7 successes

cover: 7 successes

decry: 7 successes

tatty: 7 successes

glass: 7 successes

gamer: 7 successes

rouge: 7 successes

jumpy: 7 successes

moldy: 7 successes

novel: 7 successes

debar: 7 successes

stave: 7 successes

annex: 7 successes

unify: 7 successes

email: 7 successes

kiosk: 7 successes

tense: 7 successes

trend: 7 successes

stein: 6 successes

islet: 6 successes

queen: 6 successes

fjord: 6 successes

sloth: 6 successes

ripen: 6 successes

hutch: 6 successes

waver: 6 successes

geese: 6 successes

crept: 6 successes

bring: 6 successes

ascot: 6 successes

lumpy: 6 successes

amply: 6 successes

eerie: 6 successes

young: 6 successes

glyph: 6 successes

curio: 6 successes

merry: 6 successes

atone: 6 successes

Edit: I ran the same code again, this time running each simulation 10,000 times for each word. You can find the results below:

bluer: 44 successes

grown: 41 successes

motel: 41 successes

stole: 41 successes

abbot: 40 successes

lager: 40 successes

scout: 40 successes

smear: 40 successes

cobra: 40 successes

realm: 40 successes

queer: 39 successes

plaza: 39 successes

naval: 39 successes

tulle: 39 successes

stiff: 39 successes

hussy: 39 successes

ghoul: 39 successes

lumen: 38 successes

inter: 38 successes

party: 38 successes

purer: 38 successes

ethos: 38 successes

abort: 38 successes

drone: 38 successes

eject: 38 successes

wrath: 38 successes

chaos: 38 successes

posse: 38 successes

pudgy: 38 successes

widow: 38 successes

email: 38 successes

dimly: 38 successes

rebel: 37 successes

melee: 37 successes

pizza: 37 successes

heist: 37 successes

avail: 37 successes

nomad: 37 successes

sperm: 37 successes

raise: 37 successes

cruel: 37 successes

prude: 37 successes

latch: 37 successes

ninja: 37 successes

truth: 37 successes

pithy: 37 successes

spiky: 37 successes

tarot: 36 successes

ashen: 36 successes

trail: 36 successes

Conclusion

The Monte Carlo method provides a powerful and flexible approach to solving complex problems, making it an ideal tool for predicting the best Wordle guesses. By simulating multiple guessing scenarios and analyzing the outcomes, we can identify the words with the highest likelihood of being the solution. The Python script presented here leverages the comprehensive list of acceptable Wordle words from GitHub, demonstrating how statistical techniques can enhance our strategies in the game.

Of course, by looking at the list itself it very rarely would allow a player to input the top 6 words in this list and get it right. It's probalistic nature means that although it is more probable that these words are correct, it is not learning as it goes along and therefore would be considered "dumb".

Benefits of the Monte Carlo Approach

Data-Driven Predictions: The Monte Carlo method leverages extensive data to make informed predictions. By simulating numerous scenarios, it identifies patterns and trends that may not be apparent through simple observation or random guessing.

Handling Uncertainty: Wordle involves a significant degree of uncertainty, as the correct word is unknown and guesses are constrained by limited attempts. The Monte Carlo approach effectively manages this uncertainty by exploring a wide range of possibilities.

Scalability: The method can handle large datasets, such as the full list of acceptable Wordle words from GitHub. This scalability ensures that the predictions are based on a comprehensive dataset, enhancing their accuracy.

Optimization: By identifying the top 50 words with the highest success rates, the Monte Carlo method provides a focused list of guesses, optimizing the strategy for solving Wordle puzzles.

Practical Implications

The application of the Monte Carlo approach to Wordle demonstrates its practical value in real-world scenarios. The method can be implemented using Python, with scripts that read word lists, simulate guessing scenarios, and aggregate results. This practical implementation highlights several key aspects:

Efficiency: The Monte Carlo method streamlines the guessing process by focusing on the most promising words, reducing the number of attempts needed to solve the puzzle.

User-Friendly: The approach can be easily adapted to provide real-time feedback and progress updates, making it accessible and user-friendly for Wordle enthusiasts.

Versatility: While this essay focuses on Wordle, the Monte Carlo method’s principles can be applied to other word games and puzzles, showcasing its versatility.

Specific Weaknesses in the Context of Wordle

Non-Deterministic Nature: The Monte Carlo method provides probabilistic predictions rather than deterministic solutions. This means that it cannot guarantee the correct Wordle word but rather offers statistically informed guesses. There is always an element of uncertainty.

2. Dependence on Word List Quality: The accuracy of predictions depends on the comprehensiveness and accuracy of the word list used. If the word list is incomplete or contains errors, the predictions will be less reliable.

3. Time Consumption: Running simulations for a large word list (e.g., thousands of words) can be time-consuming, especially on average computing hardware. This can limit its practicality for users who need quick results.

4. Simplified Feedback Model: The method uses a simplified model to simulate Wordle feedback, which may not capture all nuances of human guessing strategies or advanced linguistic patterns. This can affect the accuracy of the predictions.

The House always wins with Monte Carlo! Is there a better way?

There are several alternative approaches and techniques to improve the Wordle guessing strategy beyond the Monte Carlo method. Each has its own strengths and can be tailored to provide effective results. Here are a few that might offer better or complementary strategies:

1. Machine Learning Models

Using machine learning models can provide a sophisticated approach to predicting Wordle answers:

Neural Networks: Train a neural network on past Wordle answers and feedback. This approach can learn complex patterns and relationships in the data, potentially providing highly accurate predictions.

Support Vector Machines (SVMs): Use SVMs for classification tasks based on features extracted from previous answers. This method can effectively distinguish between likely and unlikely words.

2. Heuristic Algorithms

Heuristic approaches can provide quick and effective solutions:

Greedy Algorithm: This method chooses the best option at each step based on a heuristic, such as maximizing the number of correct letters or minimizing uncertainty. It's simple and fast but may not always find the optimal solution.

Simulated Annealing: This probabilistic technique searches for a global optimum by exploring different solutions and occasionally accepting worse solutions to escape local optima. It can be more effective than a greedy algorithm in finding better solutions.

3. Bayesian Inference

Bayesian inference provides a probabilistic approach to updating beliefs based on new information:

Bayesian Models: Use Bayes’ theorem to update the probability of each word being correct based on feedback from previous guesses. This approach combines prior knowledge with new evidence to make informed guesses.

Hidden Markov Models (HMMs): HMMs can model sequences and dependencies in data, useful for predicting the next word based on previous feedback.

4. Rule-Based Systems

Using a set of predefined rules and constraints can systematically narrow down the list of possible words:

Constraint Satisfaction: This approach systematically applies rules based on Wordle feedback (correct letter and position, correct letter but wrong position, incorrect letter) to filter out unlikely words.

Decision Trees: Construct a decision tree based on the feedback received to explore different guessing strategies. Each node represents a guess, and branches represent the feedback received.

5. Information Theory

Using concepts from information theory can help to reduce uncertainty and optimize guesses:

Entropy-Based Methods: Measure the uncertainty of a system using information entropy and make guesses that maximize the information gained. By choosing words that provide the most informative feedback, these methods can quickly narrow down the possibilities.

Whether you're a Wordle enthusiast or a data science aficionado, the Monte Carlo method offers a fascinating glimpse into the intersection of statistics and gaming. Happy Wordle solving!

[oolavie]

It's written, that's why...

[panelshowsource]

random things to watch over the holiday break

happy holidays friends (⸝⸝^ᴗ^⸝⸝)❄️ as many of us have time off from our normal schedules, are taking long-haul flights or car drives, and will be spending hours in broom closets to avoid our terrifying families, i figure this is the perfect time to look back on the year and put together some watch links for over the break ❄️❄️❄️

—

panel shows

the christmas special of never mind the buzzcocks is always...something else

speaking of, icymi in a panel show miracle earlier this year an anonymous source provided beautiful archival copies of the first 12 series of nmtb — so this is the perfect time to revisit its classic era!!

junior taskmaster just wrapped up its first season! very wholesome, for the whole family (don't forget to check out the taskmaster podcast discussions for each episode, hosted by ed gamble!)

there were some great eps of cats does countdown this year but this one was probably my standout<3

because this series is on sky so we have to be careful circulating it, not everyone got a chance to watch rob beckett's smart tv when it aired this year! some of the panel guests include natasia demetriou, nicola coughlan, david tennant, romesh, and alan davies, among others

idk if this is controversial but i think the australian guy mont spelling bee MIGHT be better than the new zealand version... i'm not sure yet... i need someone else to watch every single episode and tell me what my opinion should be. i also want to thank this show for teaching me how to spell vinaigrette

this, this, and this were some of my favourite episodes of wilty this year!! btw the 2024 christmas episode just dropped!

there were a lot of wild lineups on mel giedoryc: unforgivable this year, but i'd recommend just starting with the first episode of the latest series because..well you'll understand when you see it

this year i made three big lists of random panel show moments that, in my humble opinion, you will love wasting your holidays hours clicking through: part 1 / part 2 / part 3

misc. tv

the royal variety performance 2024

the completely made up adventures of dick turpin was renewed for s2 so make sure to catch up!!! it's SO stupid hahaha

on a similar, less stupid note, ludwig will also be back for s2!

we're all still missing sean lock, who passed away three years ago, so it's never a bad time to revisit 15 storeys high — especially now that we have upgraded rips!

listen jon and lucy may be divorced but that doesn't make meet the richardsons any less iconic and the last two episodes just released!

s2 of alma's not normal is out this year and doing such amazing things for our sophie willan!!

this was a bit under the radar but backstage with katherine ryan was really fun! i love the mostly-documentary concept and it's one of my favourite things to see the backstage culture between these random comedians (judi x ivo killed me)

rhod gilbert's stand up to cancer documentary was really beautiful ;;

am i being unreasonable? (written by & starring daisy may cooper, from this country) is one of my underrated scripted comedies of the year

paddy mcguinness on who do you think you are

in the new jimmy carr-hosted game show battle in a box, pairs of celebs (mostly comedians) are trapped in an empty box for 24 hours, forced to play a series of mental and physical challenges. if you like the lineup then it's worth checking out!

it's christmas. just follow tradition and watch fry & laurie.

standup

ahir shah – ends (2024)

fern brady – austistic bikini queen (2024)

harriet kemsley – everything always works out for me (2024)

lucy beaumont – live from the royal court theatre (2024)

john kearns – the varnishing days (2023–4)

rhys james – spilt milk (2024)

suzi ruffell – snappy (2024)

tony law – the law also rises (2024)

films

monty python and the holy grail (1975) dir. terry gilliam, terry jones

withnail and i (1987) dir. bruce robinson

gosford park (2001) dir. robert altman

the personal history of david copperfield (2019) dir. armando iannucci

how to have sex (2023) dir. molly manning walker

rye lane (2023) dir. raine allen-miller

scrapper (2023) dir. charlotte regan

kneecap (2024) dir. rich peppiatt

youtube

been enjoying the dish podcast this year!! some of my favourite episodes include claudia winkleman, jordan north & william hanson, saoirse-monica jackson, gordon ramsay, sandi toksvig, richard e. grant, matthew macfadyen, and stephen fry

sandi toksvig hugging guests (2024 edition)

obsessed with this house tour with richard e grant

phil wang was on jolly?? it was fun to see his house

don't sleep on the taskmaster outtakes content!

radio & podcasts

green wing came back for a 6-part radio series and warmed all of our hearts<3

some of my favourite episodes of off menu this year: elis james, john robins, sam campbell, frankie boyle, lucy beaumont, jess knappett, joe wilkinson, tommy tiernan, ardal o'hanlon, huge davies (one of the all-time clips), danny dyer (this one is truly crazy on the ears can't recommend it enough)

the horne section podcast was back for a few episodes!!! if you've never listened before, start with this classic episode you're welcome

susie dent and phil wang have adorable chemistry on this new radio game show

david o'doherty and max rushden started a new podcast about what people did yesterday that has had lots of fun guests! start here if you need to give it a taste

a few RHLSTP episodes worth giving a listen: lee mack, bob mortimer, armando iannucci, rob brydon, peter serafinowicz, ade edmondson, fern brady, among others. if you find your patience waning, he's doing a couple of 'best of 2024' eps! richard's really been focused on his book podcast this year

books

frankie boyle & charlie skelton – a short history of the apocalypse: the vital guide to your future survival (2024)

miranda hart – i haven't been entirely honest with you (2024)

richard osman – we solve murders (2024)

—

i could go on forever but i've got to stop somewhere heh... looking forward to big fat quiz and more mindless telly in 2025! have a wonderful holiday x sarah

PANEL SHOW WATCH LINKS • NON-PANEL SHOW WATCH LINKS ♥ https://ko-fi.com/panelshowsource

[bassiascoparia]

Percy Jackson's fridge horror

What gets to me about Percy Jackson and the sequel series is that there's so much fridge horror in it.

For those of you who don't know, fridge horror is something that seemingly innocent but has very disturbing undertones.

Like the climbing walls in CHB. What do you MEAN that they clash together, hurting the campers who haven't reached the top, and that there's also fucking lava which BURNS THE CAMPERS, NO LESS. And that Chiron allows it?

AND THAT HE FUCKING INSTALLED IT?

And there's lava below? Do you know how serious fucking lava burns are? They're horrible. Campers might have even died before.

And there's a full lava and earthquake mode too, and boulders roll down on the campers, which is pretty serious and can make for some fatal injuries. Jesus, Rick, what the hell were you thinking?

I wonder if Luke saw the horror of this and if this was a small part that motivated him to join Kronos. I really do wonder.

And in ToA, the Three Legged Death Race?

Chiron wants to reward who come back..........alive. Because it's so dangerous that it has fucking exploding Chainsaw Frisbees and iron orbs falling from the ceiling. And apparently it's so dangerous that you can find fucking Python in there too. Oh hey Python, wazzup old mate-AAAAAAHHHHHHH-gets swallowed and painfully digested.

And this is all because a MILLENIA OLD TUTOR WHO SHOULD KNOW BETTER AND A FUCKING GOD WHO'S SUPPOSED TO PROTECT THESE CHILDREN couldn't say no to a fucking eight year old who came up with the terribly dangerous and impractical idea for this race. An eight year old, folks.

Chiron is........a terrible person for this. No, fucking seriously. He sent those kids in knowing that they might die and have serious trauma if not. How anyone can like Chiron after this is beyond me. No wonder Luke joined Kronos. Such a shame he lost, though.

And Paolo Montes' limbs just casually being ripped off and then reattached? What the fuck was this, Rick? A child's limbs, that too, sawed off! Dismemberment is so comedic, especially when it happens to an unprepared child!

FUCKING NEWS FLASH, RICK, THAT'S NOT WHAT HAPPENS! DISMEMBERMENT IS SERIOUS AND PERMANENT TRAUMA! IT'S NOT JUST REATTACHING LIMBS AND OH EVERYTHING IS SUNSHINE AGAIN.

Feel free to add your own fridge horror that you've noticed.

[harrisonstories]

So here's something interesting...

The Beatles Derek Taylor Never-Before-Heard Collection of Lost Beatles Recordings: Including the 1967 Kenwood Sessions and John Lennon Private Recordings

This is the track listing from the description:

Tape 1: Unheard Beatles Sgt Pepper Rehearsals from Kenwood late 66 early 67

Run time is 56 minutes, songs include:

Revolution #9, mainly John in many accents, George can be heard, Paul too, Ringo one time, Terry Doran is also heard being interviewed by John, Terry Doran was ‘The Man From The Motor Trade’ on Sgt Pepper, every identical animal sound effect from Good Morning Good Morning is featured throughout, probably pre-dates Pepper and John has the sound effects saved, cockerel, hens, sheep, horse, pigs, cat, dogs etc, the very ones used on Pepper. Sitar drones almost all the way through by George, Piano backdrop also

Track Listing:

That much Control

Monte Carlo rally sound effects Terry Doran is Jack Brabham Formula 1 racer

Cat Feeding Services (Monty Python esque sketch)

A million miles away, John Indian accent Beatles far east tours in 66

Crazy banjo song, JL bellows

I’m aware of the situation monologue

Swing your partners

Lennon.McCartney complaining about the heat

John and George shouting over a very loud backing track

John/Paul counting in 123 testing, JL turns it into a poem.

Dear Prudence very early demo John wrote it way before 1968

British Police are pigs, in an Indian accent

Tape 2: George Harrison With the Bonzo Dog Doo-Dah Band and Jimmy Page.

15 tracks, 59 minutes George with his Thames Valley muso friends, Jimmy Page, Jon Lord, Joe Brown, Sam Brown, Bonzo Dog Doo-Dah band (Neil Innes, Legs Larry Smith, Vivian Stanshall) Alvin Lee, all songs written by the Bonzos and George, all recorded at FP.

Track Listing:

George into talk while playing guitar, introducing a new song

Brazil take 1 written for the Handmade films project Brazil (never went to production)

Brazil take 2

Brazil Take 3

Sooty Goes to Hawaii

Mandalay monologue for handmade films production of the same name

Sooty Goes to Hawaii #2

Sooty Goes to Hawaii #3

Operatic Aria sung by Georges father-in-law and Olivia Harrisons dad Zeke Harrison, I doubt that Olivia has heard this

Bullshot theme song for Handmade films completed production.

Hare Krishna chant by everyone

Chant 2

While my Guitar Gently weeps with Jimmy Page on guitar

Same with Alvin Lee on guitar

if I Needed Someone

Tape 3: George with Bonzo Dog Doo-Dah Band band, all co-written 25.30 mins, 16 tracks

Track Listing:

Intro Legs Larry Smith

Do You Remember

Nothing Ever Changes

Urban Spaceman

Isle of Money (I Love Money)

Can you Groove (George)

There’s a Bright Golden Boil on my Penis

I Like Cesar

Misery Farm

Julie

Danda

When You Gotta Poop

Now You’re Asleep

Telling me The End

Viv Has Gone to Heaven

Mandalay Monologue #2

Tape 4: John Interviews Yoko 1969

Recorded by John in 1969, 45 minutes, John questions Yoko’s motives for being with him, discusses very personal matters, very revealing.

Tape 5: Yoko with Dr. Artur Janov

Yoko’s Primal Scream therapy 1 hr 40 mins, of very personal therapy, Yoko discusses John, music and very personal issues including John’s friendship with George.

Tape 6: “One From The Nursery” Unreleased John Ono Lennon Album

John and Kyoko Cox Tittenhurst Park

Run time is 47 minutes

4 tracks

Lots of John talking and playing acoustic guitar (sounds like his J60E) recorded at Christmas time, Various songs stand out, all written by John & Kyoko

John, I Love You

I Wish You Were my Father.

[fullscoreshenanigans]

Tagged by @esthelle18 (thanks again!)

Rules: 1. Fit as many characters as you can into the template— but they have to be your FAVORITE characters. 2. You can fill in the blanks with names, images, or both. 3. Finally, tag between 3 and 9 other users!

Limiting myself to one character per series:

Top row, left to right: Leon S. Kennedy (Resident Evil), Elster/LSTR-512 (Signalis), Isabella (The Promised Neverland)

Middle Row: Haruhi Fujioka (Ouran High School Host Club), Mae Borowski (Night in the Woods), Grace Monroe (Infinity Train)

Bottom Row: Python (Fire Emblem Echos: Shadows of Valentia), The Count of Monte Cristo (Gankutsuou), Mabel Pines (Gravity Falls)

Tagging: @darklight-owl @evthesoup @gatekeepurr @graphx @naehja @najuwu @questiontocertaintyofreality @whywoulditho @zazora @ anyone else who's interested

Template below the cut:

[andmaybegayer]

Last Monday of the Week 2023-11-06

It was Bandcamp Friday so I'll open with a rundown.

Listening: One song per album let's go

Do The Hate by MiSLeD, off TERRORTORIES, a deeply uncomfortable sounding song.

I originally picked up MiSLeD's acoustic album a few Fridays ago and took a while to come around on their unbelievably blunt and hyperlocal style. A sledgehammer through Johannesburg concrete, I have come to love 'em. Do the Hate has an aggressive chant that makes it genuinely kind of uncomfortable to listen to and also extremely fun to yell along with.

The Length of the Chain by Chamber Mage, off their 2022 demo tape and thus far their only album release unless you go see them live.

I picked these guys up off I think the Topic Lords podcast? Solid reliable heavy metal. Can't wait to see their first full album, they're from Denver so if you're from that part of the world definitely find out if they're playing.

All On Fire by Double Sun, from the album of the same name, Pretoria boys playing bluesy punk.

One of the last bands I saw in Johannesburg before I moved. I had the three-part Dead Wreck Beach stuck in my head for a good long while. I'm still not sure what it is about Gauteng that produces so many psychedelic punk bands but I'm not complaining.

Two Jack de Quidt albums, soundtracks from Friends at the Table which I have been getting really into.

First up, The Tower, As Built By The Divine Candidate Chital, from the soundtrack for COUNTER/weight, meditative track to match the meditative and still incomplete two-player game The Tower.

Apperances of The Tower in F@TT games are always great. It's a game that the GM and composer have been working on forever and they get really, really into it.

Next, gotta be Marielda, from the season of the same name. The clarinet from this is so memorable.

The intro tracks to every game are obviously the ones you hear the most, and they're all bangers.

All Through the Night [Patrick's Version], from the Titus Andronicus demotape for their most recent album The Will to Live. Rough cuts from studio sessions.

I adore The Will to Live, when I'm honest I really don't care much for most of Titus Andronicus's work other than The Monitor and now The Will to Live. These are good at capturing what I like about live performances: performers going ham and not necessarily performing well but definitely performing the most.

And lastly, Threshold from sungazer, off the album Perihelion. This was an experimental piece combining rhythms at both extremes of human perception, with the overall rhythm of the song being as slow as possible with individual bars being impossibly fast.

There's a whole Adam Neely video on it, because he's one part of sungazer.

Alright on to the rest of the show:

Reading: Back into The Count of Monte Cristo, rapidly seeing the roots of many other stories I've read crystalize into this genre, most notable Eoin Colfer's Airman.

Watching: The various Hackaday talks that have been uploaded over the past week, some good ones lately like A Hacker's Guide to Audio and Video Formats.

Playing: on Saturday evening I finished making dinner and sat down to play Titanfall 2 from the start because for some reason my save was incomplete and I figured I'd just start over. And then it was two in the morning and I had beaten Titanfall 2. Great game.

Making: Abortive attempts at designing some adapters for my vacuum cleaner because I realized I took my reference images wrong and had to start over, fortunately before I wasted any filament.

Also Hack Week at work, so I'm working on some original code with two much, much more experienced python developers, which if nothing else is a good learning experience.

Tools and Equipment: Modern text editor configuration systems can be rigged to almost completely bootstrap themselves if given an internet connection. You should use this to your advantage. I use lazy.nvim in bootstrap mode now and it's so easy.

Side note, nvim's lua configuration mode is real nice, major improvement over vimscript when you want to do anything complicated. Sorry Tim Pope.

[astrumavis]

Explain to me why I, as a biochemistry student, need to understand the different types of sorting algorithms and how to write a code in the language C (not C++ or Python, just C) to calculate the area of a shape based on Monte Carlo integration (among others). Why.

I am going fucking insane where are my MOLECULES !!!!

[milfjagger]

in the spirit of just saying things recreationally i have two very specific types of childhood film nostalgia and one is watching things with my grandparents (mum’s side) i.e. tom thumb (1958), the count of monte cristo (2002), robin hood: prince of thieves and weird old british kids shows like tales from the riverbank. and the other is watching things with my granny/cousins (dad’s side) i.e. the mummy (1999), the 80s bbc narnia series, the monty python cast adaptation of the wind in the willows (1996) and this really bad but nonetheless formative cartoon film of the princess and the goblin

[forthesanityofstorytellers]

A Pumpkin game - Watch the Pumpkin

Honestly it was a tie so I'm just putting up a bit for both options, lol

🎃🎃🎃🎃

When you see a field of pumpkins, you're compelled to stop and at least look at it. …Turns out if you stare long enough, something weird will happen. Also turns out, the shovel may not be the best option. I mean, it depends on what you do with it.

Would you like to play?

You see a field of pumpkins.

You bend down to look at one of the pumpkins. The smallest one close to you begins to wiggle on it's own.

You wait and stare at it. The pumpkin comes alive, popping up from the ground with a wide grin torn out from it's center.

[To see what happens if you run away Monte Python style, click here!]

[nysocboy]

Asteroid City: Bleak play-within-a-play-within-a-play, with one teensy gay kiss and a lot of Ionesco

Movie night was Asteroid City (2023), which I thought would be about atomic testing in Nevada in the 1950s.  Instead, I was watching the Theater of the Absurd.  Maybe Ionesco, where your mother turns into a giraffe and offers you brownies,  or a Monte Python episode where one sketch bleeds into another, so Vikings are suddenly talking to the Minister of Finance about the hippodrome tariff. 

As far as I can tell, there are two plays with plays.

1. In an old-fashioned black and white tv studio, a narrator tells us that what we are witnessing is a story, not real. The curtain opens to reveal:

2. The Playwright (Edward Norton) auditioning an actor for the lead in his play (Jason Schwartzman), who brings him ice cream, changes into a different costume, and delivers a nonsequiter monologue.  

They kiss..  But don't get excited: it's in the distance, and never referenced again, while there are three or four heterosexual romances coming up. We cut to the main story:

A lot of people arrive for the Junior Stargazers' Convention in Asteroid City, Nevada , where an asteroid crashed to Earth (they mean a meteor).  During the opening speeches, an alien descends from a spaceship and grabs the asteroid.  Everyone is put under quarantine, while the government tries to convince them that nothing happened.  After a week, the government is about to lift the quarantine, but the alien returns and gives the asteroid back.  The quarantine is on, but everyone riots, and the next day they are gone.  Maybe it was all a dream.

While all this is going on, there are several soap opera stories.  Steinbeck (Jason Schwartzman again, I think) arrives with his son and three young daughters.  He was going to leave the son and go on to his wealthy father-in-law's house to bury his wife's ashes, but his car broke down.  During the quarantine his three daughters, who are witches, bury the ashes in the desert and perform a spell to resurrect her.  She isn't actually resurrected, but she apparently appears in a flashback or flash-sideways scene.

I figured that Steinbeck must be the famous novelist and nude model, who was active in Hollywood at the time, so I went scurrying to wikipedia for his biography.  It doesn't match.

Steinbeck falls in love with the famous actress in cabin next door.  Mostly they gaze at each other morosely for interminable minutes and say nonsequiters, but -- grossness alert -- she takes off all her clothes, top and bottom  both. 

Meanwhile his son  Woodrow (Jake Ryan), a 40-year old playing 14, falls in love with her daughter.

And someone, I don't know who, buys a parcel of land out of a vending machine.

And a Dad and son have to live in a tent, because their cabin burned down.

Eventually the story spills out into the playwright's world (where we find out that he died in an auto accident), and then to the studio. Along the way there are several nonsequiter scenes that don't fit anywhere. 

1. An actress on a train receives a note apologizing and saying they work well together.  Woodrow, the boy delivering the note, spends the night with her.

2. A woman tells a guy who lives on sound stages that she wants a divorce; they kiss.

3. A man says he needs some air ("You won't get it -- it's all soundstages") goes out onto the balcony of a soundstage street, where he interacts with the woman on the balcony of the sound stage next door. They stare at each other morosely and say nonsequiters.

4. A lot of people in various situations tell us: "You can't wake up if you don't fall asleep," over and over until it becomes painful.

Maybe our takeaway is that life is meaningless, so art should be, too. 

The full review, with more non sequiters and a lot of nude photos, is on RG Beefcake and Boyfriends

[panelshowsource]

helloooo everyone happy tuesday (barely)!

first, some recent uploads on googledrive:

all of guy mont spelling be, nz and au (new eps!)

new audiobooks by bob mortimer and rhys nicholson

john kearns – the varnishing days

jessie cave – an ecstatic display (recorded at the fringe 2024)

note that you can find the last leg in paris here, plus taskmaster nz here and here, and i want to mention again that the googledrive i share on my main account has some beautiful rips of great british comedy/-adjacent films i highly recommend: withnail and i, boiling point, gosford park, monty python and the holy grail, the personal history of david copperfield, the full monty, and more

second, i'm moving this week!!! i'm still an nyc girlie of courseee, but now i'll be in park slope 🥹 if anyone is nearby, give us a shout!! i may be a little slow uploading this week, but i should have wifi every day and be able to make sure the new gmsb and tut episodes are up within a day or so~ and i'll be back to posting gifs shortly!

third, thank you so much to everyone who sent me a tip on my new kofi page 🥹😭 they were very generous, not to mention they paid for half of the googledrive for this month! so thoughtful, thank u again ❤️

[starshard17]

A few years ago I had some medical complications and with those complications I had ✨️excruciating✨️ pain so I was prescribed insanely strong pain meds

Every time I took those meds I would get super high. Like... I'd be higher than a kite.

And then my family decided it'd be a good idea to show me Monte Python and the Holy Grail

And they make references to it very often, but I do not remember a thing from that movie. Supposedly, my reactions were very good ✌️

But yeah. What a movie to watch when high right 💀