u/jacklychi

Exactly, you need to do your own research and figure out what is best.

Interesting, what are "magic link logins", how do you not use passwords?

If it does get expensive, is it easy to migrate to another platform? do they give access to all the user data in their db that you can export?

So Google would count as an OIDC federation.

so why do they say for the 50k free MAUs table:

For users who sign in directly with their credentials from a User Pool or with social identity providers such as Apple, Google, Facebook and Amazon, there are volume-based pricing tiers for MAUs above the free tier, as shown in the table below.

I guess it is included in the 50k then?

stick to the OIDC spec and keep things loosely coupled

what does this mean?

why?

I believe I did it several years ago without calling, is this something new?

Online guides say you only do it with Questrade, but they may be outdated...

how do you journal with RBC DI? I never saw that option

ok I hope so. And will there be interest fees for the short position? (I have a leveraged account with "short" option enabled).

"Shorter code = better/faster code".

I thought so too before.

Nowadays I would go an extra mile to avoid an additional DB or API hit.

Also, readability is important. Adding another variable MAX_ATTEMPTS=10, is better than just plugging the "10" randomly without anyone understanding it.

To put it simple, if you are iterating your own list of some sort, and with each iteration, you need to do something in the DB, then it will result in a DB call in each iteration.

Lets say you got a CSV with products and their countries and categories. And you want to check in your DB if each product exists, if its country exists, and if its category exists, it will result in 3 DB hits (assuming they all in 3 different tables). Then if you got 1000 products, it will result in 3000 DB hits in total.

Storing the products, countries, and categories querysets in a dictionary will speed it up by 1000x.

Django querysets are "lazy".

Meaning that countries=Country.objects.all() doesn't actually fetch the database.

Only when you try to access an object in countries, only then it will make the database call.

So for example, if you iterrate all objects for country in Country.objects.all(), it should work fine, and result in 1 database call.

However, if you have a get() (or first() or last()) somewhere in there, that get will result in an additional database call.

In my case, I had my own local my_countries list, and I wanted to check it against the database, so for each object in my_countries will result in a separate database query countries.get(my_countries_obj). It was an absolute killer (with larger more complicated data sets).

I learned that if I need to run several operations on a queryset, I should map all my filtered query results to a dictionary like this:

countries = {country.name: country for country in Country.objects.all()}

It can save thousands of database hits and speed up long loops by x100 times.

EDIT: let me explain further

Django querysets are "lazy".

Meaning that countries=Country.objects.all() doesn't actually fetch the database.

Only when you try to access an object in countries, only then it will make the database call.

So for example, if you iterrate all objects for country in Country.objects.all(), it should work fine, and result in 1 database call.

However, if you have a get() (or first() or last()) somewhere in there, that get will result in an additional database call.

In my case, I had my own local my_countries list, and I wanted to check it against the database, so for each object in my_countries will result in a separate database query countries.get(my_countries_obj). It was an absolute killer (with larger more complicated data sets).

Looks like a promo for SE Rank, whatever that garbage tool is...

And looking closer at your post history, you are constantly pitching it, never directly, but you weirdly mention it like it is on par with the big players.

This ban has nothing to do with privacy. If you look at Facebook's lobbying expenses, you will find the real answer.

Facebook agrees too.

Facebook revenues and stock has been crashing for the past couple of years. Biggest reason is that TikTok takes a huge market share. They just can't compete fairly.

Facebook also has one of the biggest lobbying spend in the USA.

If you connect the dots a bit, I think you will determine the real reason TikTok is getting banned.

How about we let the consumer choose which product they prefer, rather than paying off government senator boomers who have no sense of how technology actually works?

Every corporation gets greedy and selfish as they get richer.

Google started with "Don't be Evil" at the beginning. No more mention of that these days.

One thing not to do in the presales process, is give your customers some garbage survey.

Unless you are the one paying them, or they got real incentive, you can't expect people to fall into your little convenient funnel without providing any value.

Capturing CX journey must be done internally, in the background, seamlessly. Your engineers should set it up.

Can confirm. The noose system is horrible. At least not for the long term use.

AHREFS used to be really good at scouting those 1000s of crappy negative SEO profile links.

Nowadays Google simply ignores those links. No need to even disavow them.

So I don't think AHREFS has a huge edge over SEMRush anymore. Just switch to them. You won't miss anything important.

The best SEOs are too busy making money from their high-ranking websites.

Those listed in the comments are probably selling a course, links, or something else related to SEO.

They probably also got all censored screenshots with no live publicly ranking sites we can all see. They are pretty much sneaky salesmen, not SEOs.

So always use common sense when following their stuff.

Surfer is a fancy word-counter and keyword-density calculator. Nothing AI about it. Save your money on that one.

OpenAI can be easily detected (systematically) if the content was written by that. So use at your own risk.

thanks so much, worked perfectly.