abarrettwilsdon
abarrettwilsdon on Hacker News
Establishing a (standard sized) ESOP is good for the company long term.
If you would like better/different terms, you'll need at least one other firm to offer you a term sheet as leverage.
This comment has quite the Dropbox 'build such a system yourself quite trivially' comment energy
They try to predict flu strains because it is prohibitive to identify and produce vaccines for every strain in time for flu season each year.
By your assertion, the entire notion of yearly flu shots would be irrelevant.
I would pay _so_ much money to never have to use Cloudwatch and AWS Cost Management again. Thankfully, I qualify for the vantage free tier for quite a while longer.
Never mind Github, Gitlab, Pivotal Labs, Netflix, and Yahoo/Verizon
and they're not even open sourcing it, they're just bragging about it
why is this on HN at all
* data modeling
* warehousing, ETL, monitoring, observability
* the BD necessary to make a standard actually standard
* what aspects to compromise on, if necessary
* network effects
* regulatory moats
ed: the original "DaaS Bible" post is quite a bit more useful
https://github.com/segmentio/daydream
Probably the best you're going to get - most things worth scraping are worth money, and as such are not freely available
I find the choice of Flask + Zappa a little weird - I much prefer serverless.com for infra as code - but it makes sense after staring at it long enough
They look very similar? But they're different? According to the docs this one is more focused on advanced patterns? Does a person need to buy the first to get value from the second?
Very confusing UX IMO
The broader OSINT has used dorking for a decade plus (e.g. exploit-db.com goes back to 2003).
The goal in writing this was to democratize access beyond those who use it regularly for work
`No results found for "the SERP should stay the same".`
Then defaults to providing the SERP for the fallback query:
`Results for the SERP should stay the same (without quotes):`
That SERP should change when this HN thread is indexed though
You can more or less replicate the functionality with intext:specific.url/subsite
Will update and credit you.
e.g. the search of another article "set up Google Sheets APIs (and treat Sheets like a database)"
turns up my site and a couple Twitter threads talking about it (plus a phishing site which has scraped and republished it). I presume that will stay the same b/c it's such a specific title phrase (but not because searches are necessarily deterministic)
The permutation searches are tricky because you don't know if a lack of results means the email does not exist, or just hasn't been posted anywhere indexed
Will update and credit
generally "phrase" works well too
(also: you'll want to remove the space between site: and news.ycombinator.com)
Even if someone did sign up for the paid tier, they are strongly incentivized to cancel and keep to code
Seeing folks mention the NOT operator (-). It's quite powerful! For example, you can do:
intext:"Powered by intercom" -site:intercom.com will find all the sites that use the Intercom widget
or ~blog bread baking -inurl:checkout -intext:checkout will find bread blogs (or similar) without commercial intent
I put together a list of the two dozen or so most useful templates of this, for folks who are interested: https://www.alec.fyi/dorking-how-to-find-anything-on-the-int...
It is just stunning how much better it is learning Dynamo/NoSQL in general from this than effectively any other source. Anyone who's had to rely on AWS docs knows how face-meltingly dense they can be.
I went back and refactored all my previous Dynamo work last night, and the difference was night and day. I'm planning to migrate some relational structures later this week, as well.
Is good book.
(You can also recreate this functionality locally with a few lines of Python):
import pandas as pd
import os
list_of_files = [f for f in os.listdir('.') if os.path.isfile(f) and ".csv" in f]
print(f"Files that will be concatenated are: {list_of_files}")
original_df = pd.DataFrame()
for file in list_of_files:
df = pd.read_csv(file, keep_default_na=False)
original_df = pd.concat([original_df, df], axis=0, ignore_index=True)
original_df.to_csv(f"Output file.csv", index=False)Feels like paying $49/mo is too high for a marketer to try out, but too low for the fact you can run an effective DDoS of some sites with it
I'd suggest changing the buckets - up to 10 monitored pages on free, a Silver Tier of maybe $29/mo of up to 100 pages + frequency of as low as hourly, a Gold Tier of maybe $99/mo of up to 1000 pages w/ minute frequency, Zapier integration, better support, etc, and then a call-for-quote tier like you already have
[1] www.flipcause.com
Some searches, like 'deep learning', 'venture capital', and 'NLP' don't display any results. Not sure if this is a problem with the search functionality or with your database (probably the former). Some searches display a lack of context - for example, searching 'AI' returns a top result of "Air travelers" because the string "ai" is in "air".
You might consider checking out a product like Algolia to scale your search.
Awesome concept though! Excited to see it grow