for - from - Fair Share Commons discussion thread - Marie - discussing the use of the word "capital" in "spiritual capital" - webcast - Great Simplification - On the Origins of Energy Blindness - Steve Keen - Energy Blindness

for - from - recommendation - from - Michel Bauwens - on Fair Share Commons chat thread, 2024 Oct 17 - context Karl Marx liberation of the individual - to - substack article - Why Human (Contributive) Labor remains the creative principle of human society - Michel Bauwens article details - title: From Modes of Production to the Resurrection of the Body: A Labor Theory of Revolutionary Subjectivity & Religious Ideas" (2016) - author: Benjamin Suriano

to - Substack article - Why Human (Contributive) Labor remains the creative principle of human society - Michel Bauwens - https://hyp.is/go?url=https%3A%2F%2F4thgenerationcivilization.substack.com%2Fp%2Fwhy-human-contributive-labor-remains&group=world

for - capitalism - etymology - modern - book Capitalism: The Word and the Thing - Michael Sonenscher - from - Discussion of "spiritual capitalism" on Kansas Missouri Fair Shares Commons chat thread - to - youtube - New Books Network - interniew - Captialism: The word and the thing - Michael Sonenscher

Summary - Michael Sonenscher discusses the modern evolution of the word "capitalism". Adding the suffix "ism" to a word implies a compound term. - Capitalism is a complex, compound concept whose connotations from the use in 18th and 19th century France and England is quite different from today's. - How meaning evolved can give us insight into our use of it today.

to - youtube - New Books Network - interniew - Captialism: The word and the thing - Michael Sonenscher - https://hyp.is/ftWWfoxQEe-FkUuIeSoZCA/www.youtube.com/watch?v=ZpNaxyPpOf0

Very interesting Twitter thread

Reducing the performance hit of copying data between processes:

Option #1: Just use threads

Processes have overhead, threads do not. And while it’s true that generic Python code won’t parallelize well when using multiple threads, that’s not necessarily true for your Python code. For example, NumPy releases the GIL for many of its operations, which means you can use multiple CPU cores even with threads.

``` # numpy_gil.py import numpy as np from time import time from multiprocessing.pool import ThreadPool

arr = np.ones((1024, 1024, 1024))

start = time() for i in range(10): arr.sum() print("Sequential:", time() - start)

expected = arr.sum()

start = time() with ThreadPool(4) as pool: result = pool.map(np.sum, [arr] * 10) assert result == [expected] * 10 print("4 threads:", time() - start) ```

When run, we see that NumPy uses multiple cores just fine when using threads, at least for this operation:

$ python numpy_gil.py Sequential: 4.253053188323975 4 threads: 1.3854241371154785

Pandas is built on NumPy, so many numeric operations will likely release the GIL as well. However, anything involving strings, or Python objects in general, will not. So another approach is to use a library like Polars which is designed from the ground-up for parallelism, to the point where you don’t have to think about it at all, it has an internal thread pool.

Option #2: Live with it

If you’re stuck with using processes, you might just decide to live with the overhead of pickling. In particular, if you minimize how much data gets passed and forth between processes, and the computation in each process is significant enough, the cost of copying and serializing data might not significantly impact your program’s runtime. Spending a few seconds on pickling doesn’t really matter if your subsequent computation takes 10 minutes.

Option #3: Write the data to disk

Instead of passing data directly, you can write the data to disk, and then pass the path to this file: * to the subprocess (as an argument) * to parent process (as the return value of the function running in the worker process).

The recipient process can then parse the file.

``` import pandas as pd import multiprocessing as mp from pathlib import Path from tempfile import mkdtemp from time import time

def noop(df: pd.DataFrame): # real code would process the dataframe here pass

def noop_from_path(path: Path): df = pd.read_parquet(path, engine="fastparquet") # real code would process the dataframe here pass

def main(): df = pd.DataFrame({"column": list(range(10_000_000))})

with mp.get_context("spawn").Pool(1) as pool:
    # Pass the DataFrame to the worker process
    # directly, via pickling:
    start = time()
    pool.apply(noop, (df,))
    print("Pickling-based:", time() - start)

    # Write the DataFrame to a file, pass the path to
    # the file to the worker process:
    start = time()
    path = Path(mkdtemp()) / "temp.parquet"
    df.to_parquet(
        path,
        engine="fastparquet",
        # Run faster by skipping compression:
        compression="uncompressed",
    )
    pool.apply(noop_from_path, (path,))
    print("Parquet-based:", time() - start)

if name == "main": main() `` **Option #4:multiprocessing.shared_memory`**

Because processes sometimes do want to share memory, operating systems typically provide facilities for explicitly creating shared memory between processes. Python wraps this facilities in the multiprocessing.shared_memory module.

However, unlike threads, where the same memory address space allows trivially sharing Python objects, in this case you’re mostly limited to sharing arrays. And as we’ve seen, NumPy releases the GIL for expensive operations, which means you can just use threads, which is much simpler. Still, in case you ever need it, it’s worth knowing this module exists.

Note: The module also includes ShareableList, which is a bit like a Python list but limited to int, float, bool, small str and bytes, and None. But this doesn’t help you cheaply share an arbitrary Python object.

A bad option for Linux: the "fork" context

You may have noticed we did multiprocessing.get_context("spawn").Pool() to create a process pool. This is because Python has multiple implementations of multiprocessing on some OSes. "spawn" is the only option on Windows, the only non-broken option on macOS, and available on Linux. When using "spawn", a completely new process is created, so you always have to copy data across.

On Linux, the default is "fork": the new child process has a complete copy of the memory of the parent process at the time of the child process’ creation. This means any objects in the parent (arrays, giant dicts, whatever) that were created before the child process was created, and were stored somewhere helpful like a module, are accessible to the child. Which means you don’t need to pickle/unpickle to access them.

Sounds useful, right? There’s only one problem: the "fork" context is super-broken, which is why it will stop being the default in Python 3.14.

Consider the following program:

``` import threading import sys from multiprocessing import Process

def thread1(): for i in range(1000): print("hello", file=sys.stderr)

threading.Thread(target=thread1).start()

def foo(): pass

Process(target=foo).start() ```

On my computer, this program consistently deadlocks: it freezes and never exits. Any time you have threads in the parent process, the "fork" context can cause in potential deadlocks, or even corrupted memory, in the child process.

You might think that you’re fine because you don’t start any threads. But many Python libraries start a thread pool on import, for example NumPy. If you’re using NumPy, Pandas, or any other library that depends on NumPy, you are running a threaded program, and therefore at risk of deadlocks, segfaults, or data corruption when using the "fork" multiprocessing context. For more details see this article on why multiprocessing’s default is broken on Linux.

You’re just shooting yourself in the foot if you take this approach.

• Tasks (network, file, etc.) that needs less than 10_000 I/O interactions per second. The number is higher than you would expect, because threads are surprisingly cheap nowadays, and you can spawn a lot of them without bloating memory too much. The limit is more the price of context switching. This is not a scientific number, it's a general direction that you should challenge by measuring your own particular case.
• When you need to share data between the tasks.
• When you are not CPU bound.
• When you are OK to execute tasks a bit slower to you ensure you are not blocking any of them (E.G: user UI and a long calculation).
• When you are CPU bound, but the CPU calculations are delegating to a C extension that releases the GIL, such as numpy. Free parallelism on the cheap, yeah!

E.G: a web scraper, a GUI to zip files, a development server, sending emails without blocking web page rendering, etc.

The critical comment this was apparently in reply to was apparently deleted

• for: extinction, climate departure, Jane Goodall, quote, tapestry, thread,
• quote
  • we humans depend on the natural world
  • but what we depend on is healthy ecosystems that are made up of a complex mix of plants and animal species
  • each one has a role to play and I see it as like a beautiful living tapestry and as an animal or plant species disappears from that ecosystem it's like pulling out a thread
  • and if enough threads are pulled then the tapestry will hang in tatters and the ecosystem will disappear
• author
  • Jane Goodall

Yet another example of why it's dumb for Microsoft to lock Community threads. This is in the Bing search results as the top article for my issue with 1,911 views. Since 2011 though, there have been new developments! The new Media Player app in Windows 10 natively supports Zune playlist files! Since the thread is locked, I can't put this news in a place where others following my same search path will find it.

Guess that's why it makes sense to use Hypothes.is 🤷‍♂️

This is so stupid. I have a relevant question/comment to add to the thread, but someone has decided that no more value can come of this thread - yet it's in search results, so new people are seeing it all the time.

If people don't want notifications on an old thread, they should mute notifications on it - not declare it dead because they bore easily.

One could start a new thread talking about it, but that just daisy chains the topic across multiple threads.

Reddit is dumb for having this "feature" and it originated to censor people, which is abhorrent.

Why is it necessary to pause Can't new person post their question/comment even if it's in reply to comment #10 and the latest comment happens to be comment #56? There's no rule against replying/discussing something that is not the very latest thing to be posted in a discussion!

Possibly due to lack of a threaded discussion feature in GitHub? I think so.

Threads would allow replies to "quick person" A to go under their comment, without flooding the top level with comments... thus alowing "new person" B to post a new comment, which in so doing creates a new thread, which can have its own discussion.

ReconfigBehSci [@SciBeh]. (2021, December 20). This thread is sobering and informative with respect to what overloading health services means in terms of individual experience...worth popping into google translate fir non-German speakers [Tweet]. Twitter. https://twitter.com/SciBeh/status/1472983739890348045

!- definition : golden thread * Hannah Arendt writes: "It is nothing more than to think what we are doing". * To think, voice and enact each time anew is the vehicle of the human takeover, securing the continuity of the golden thread used to govern society * The golden thread runs in the usually unperceived gaps betgween thoughts, communications and decisions that are preconditioned, preprogramed and prethought.

ReconfigBehSci [@SciBeh]. (2021, December 10). Useful thread! [Tweet]. Twitter. https://twitter.com/SciBeh/status/1469208352819404805

James Ward on Twitter. (n.d.). Twitter. Retrieved April 21, 2022, from https://twitter.com/JamesWard73/status/1470680953643319305

Seth Trueger en Twitter. (n.d.). Twitter. Retrieved April 20, 2022, from https://twitter.com/MDaware/status/1496670775058829312

Kristian G. Andersen on Twitter. (n.d.). Twitter. Retrieved 3 December 2021, from https://twitter.com/K_G_Andersen/status/1465822536629821442

In parchment manuscripts one will often see small pin prick holes in the parchment which indicates that a hole in the animal skin was repaired during processing. Usually after curing and before use the thread from the repair is removed leaving only the small holes.

Rarely, but occasionally, the thread will still remain in the final manuscript. An example of this is LJS 418, f 3r where one can see the thread left in the page.

Che trasformazione portano effettivamente gli #NFT ?

Grazie agli #NFT la #blockchain passa dall'ambito strettamente finanziario a quello artistico e creativo.

Chi impone regole a questi ambiti allora, dovrebbe tener conto che la #blockchain è davvero il futuro di internet e che cercare di applicare ad essa delle regole troppo strette è folle.

Proprio per questo legame indissolubile col concetto di proprietà un token #NFT di un bene che si rivela remunerativo in qualche modo, si rivela accesso ad una parte di questa remunerazione. Ad esempio: il token di una canzone è accesso ai diritti d'autore della canzone in questione.

Che ruolo c'è tra l' #NFT e la #community che ruota intorno a loro?

Si tratta di quello stesso legame che c'è alla base del #contrattosociale

Le #community intorno agli #NFT infatti rendono gli #NFT di valore perché esse stesse ci credono, nel momento in cui la #community muore allora anche lo specifico #NFT perde di valore.

Nel caso delle #cryptomonete questo valore è tratto dagli enti che le creano e decidono di mantenerle.

Quale è un presupposto fondamentale dell' #NFT ?

È il fatto che il vero controllo è esercitato sulla proprietà della risorsa e non sulla risorsa stessa. Una volta che le viene associato il token la proprietà diventa programmabile, verificabile, divisibile, duratura ecc.

Cos'è un #NFT ?

È un token presente sulla #blockchain che rappresenta la proprietà di una risorsa esterna alla blockchain stessa.

Questo token è verificato da un contratto tra il suo creatore e la community

I guess @7alhashmi deleted their comment that this was in reply to??

Lewis Goodall on Twitter: “Here we go. He’s not messing about: ‘The truth is, senior ministers, senior officials, senior advisors like me fell disastrously short of the standards that the public has the right to expect in a crisis like this. When the public needed us most the government failed.’ https://t.co/lV7QqIpTDY” / Twitter. (n.d.). Retrieved May 27, 2021, from https://twitter.com/lewis_goodall/status/1397471561205092352

Ashish K. Jha, MD, MPH. (2020, December 1). There is something funny happening with COVID hospitalizations Proportion of COVID pts getting hospitalized falling A lot Just recently My theory? As hospitals fill up, bar for admission rising A patient who might have been admitted 4 weeks ago may get sent home now Thread [Tweet]. @ashishkjha. https://twitter.com/ashishkjha/status/1333636841271078912

r/BehSciAsk—Behavioural science one year on. (n.d.). Reddit. Retrieved May 2, 2021, from https://www.reddit.com/r/BehSciAsk/comments/mw8mdr/behavioural_science_one_year_on/

not exact match for: removing comment from thread makes other comments not make sense with that context missing

https://github.com/rails/sprockets/issues/162 was already closed as duplicated (so this just creates another duplicate).

Technically this could be added there.

Oh, I see, it was from so long ago (2015), that it would probably be frowned upon to reopen such an old issue.

Kenneth Fordyce. (2020, November 3). @devisridhar @georgeeaton Yet another article packed full of wise words: E.g., ‘in some ways, the people pushing for “herd immunity” are forcing us into these lockdown-release cycles because you end up in a reactive position by underestimating the spread of the virus and the hospitalisation rate’ [Tweet]. @FordyceKenneth. https://twitter.com/FordyceKenneth/status/1323544552112852992

Dr Ellie Murray. (2020, December 3). Some really great resources & discussions in this thread. The tl;dr is (1) yes, the vaccine trials included some people who had previously had COVID; and (2) in general vaccination plans will include those who have previously been sick/infected. Thanks all! [Tweet]. @EpiEllie. https://twitter.com/EpiEllie/status/1334545373126389766

Andrew💙Croxford. (2020, December 3). NEW THREAD: possible development of anti-Syncytin responses after immunization with the SARS-CoV-2 spike protein-coding mRNA vaccines, based on a ‘homologous’ region shared between these proteins. [Tweet]. @andrew_croxford. https://twitter.com/andrew_croxford/status/1334593606196187136

Seth Trueger. (2020, November 24). @MDaware: @Arkaneth interestingly covid & MVC deaths are roughly comparable (1.35 vs 1.4 million) but this is an area where the US has… [Tweet]. https://twitter.com/MDaware/status/1331326825411252225?s=20

Engelhardt, R., Hendricks, V. F., & Stærk-Østergaard, J. (2020). The Wisdom and Persuadability of Threads. ArXiv:2008.05203 [Physics]. http://arxiv.org/abs/2008.05203

Bloom Lab. (2020, June 18). "We've experimentally measured how all amino-acid mutations to the #SARSCoV2 spike RBD affect ACE2 binding and expression of folded protein in a deep mutational scanning study led by @tylernstarr & Allie Greaney:https://biorxiv.org/content/10.1101/2020.06.17.157982v1 Why is this important? (1/n)" Twitter. https://twitter.com/jbloom_lab/status/1273468539484213248

Bergstrom, C. T. (2020, June 14). "1. Another day, another blog post of #COVID19 misinformation making the rounds." Twitter. https://twitter.com/CT_Bergstrom/status/1272007583222513664

Dean, N. E. PhD (2020, June 09). "A general comment about science communications. Scientists are rarely trained to talk to the public. It's hard to explain complicated concepts simply. It's easier to retreat to our familiar technical language." Twitter. https://twitter.com/nataliexdean/status/1270164164955250690

Africa Health Research Institute. (2020, May 25). "New work from AHRI about the effect of the Level 5 #Covid19SA lockdown on access to healthcare has found a largely resilient primary healthcare system in rural KZN among adults, but some early warning signs for child health. https://ahri.org/new-covid-19-lockdown-study-shows-drop-in-child-health-visits-but-resilience-of-hiv-care-systems-in-rural-kzn/ @kznhealth" Twitter. https://twitter.com/AHRI_News/status/1264880940482007040

Cheshire, J. (2020, May 18). "John Snow's map of cholera looked as dull as (cholera filled) dishwater compared to his competitors...His brilliance was a solid data collection & then a simple map presenting what he knew. Each death marked in black and white. Here's a lesson for COVID-19 dataviz... 1/11" Twitter. https://twitter.com/spatialanalysis/status/1262338373253042178

Angner, E. (2020, May 11). "Terrific assessment of projections of demand for Swedish ICU beds. The first two panels are model-based projections by academics; the third is a simple extrapolation by the public-health authority; the fourth is the actual outcome /1." Twitter. https://twitter.com/SciBeh/status/1260121561861939200

This is better than creating a duplicate new thread.

There is no better place to respond to an existing topic than in the existing thread for that topic.

More formal and detailed version of above. Besides, the difference of being important and being interesting should be noted too. Maybe search for a thread.

The Sharing Scientist on Twitter

Carl T. Bergstrom on Twitter

John Burn-Murdoch on Twitter

Susan Michie - Twitter

Thread by @STWorg: “Live” update of analysis of 2K UK respondents and their views on privacy-encroaching tracking policies: stephanlewandowsky.github.io/UKsoci…. (n.d.). Retrieved April 17, 2020, from https://threadreaderapp.com/thread/1245060279047794688.html

David Garcia on Twitter

Guido Salvaneschi on Twitter referencing thread by Neil Ferguson