going to shrink any further:  she felt a little nervous about
this; `for it might end, you know,' said Alice to herself, `in my
going out altogether, like a candle.  I wonder what I should be
like then?'  And she tried to fancy what the flame of a candle is
like after the candle is blown out, for she could not remember
ever having seen such a thing.

  After a while, finding that nothing more happened, she decided

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

 Features like transitive dependencies and the new parent specification mechanism. The problem we run into is
 that currently we have information about a project scattered across the project.xml and the
 various properties files. What needs to be done is to encapsulate all of this in the POM.

 Typically users parameterize the use of plugins, or have custom values like ${user.name}

       for the change (usually before you start working on it).  Trivial changes like typos do not
       require a JIRA issue. Your pull request should address just this issue, without
       pulling in other changes.
 - [ ] Each commit in the pull request should have a meaningful subject line and body.
 - [ ] Format the pull request title like `[MNG-XXX] SUMMARY`,
       where you replace `MNG-XXX` and `SUMMARY` with the appropriate JIRA issue.

    For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.

    And be compatible with all of them at the same time.

Create a utility function to hash a password coming from the user.

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
def main():
    def iterfile():  # (1)
        with open(some_file_path, mode="rb") as file_like:  # (2)
            yield from file_like  # (3)

	cases := []string{
		`select * from s3object where Name like 'abcd'`,
		`select Name like 'abc' from s3object`,
		`select * from s3object where Name not like 'abc'`,
		`select * from s3object where Name like 'abc' escape 't'`,
		`select * from s3object where Name like 'a\%' escape '?'`,
		`select * from s3object where Name not like 'abc\' escape '?'`,
		`select * from s3object where Name like 'a\%' escape LOWER('?')`,

	}

	if name != "groupby" || total != 60 {
		t.Errorf("name should be groupby, but got %v, total should be 60, but got %v", name, total)
	}

	if err := DB.Model(&User{}).Select("name, sum(age) as total").Where("name LIKE ?", "groupby%").Group("name").Having("name = ?", "groupby1").Row().Scan(&name, &total); err != nil {
		t.Errorf("no error should happen, but got %v", err)
	}

	if name != "groupby1" || total != 660 {

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself....

In many cases your application could need some external settings or configurations, for example secret keys, database credentials, credentials for email services, etc.

Most of these settings are variable (can change), like database URLs. And many could be sensitive, like secrets.

For this reason it's common to provide them in environment variables that are read by the application.

## Environment Variables

!!! tip