Point.has_extended_global_df()

Returns true if the point has a dependency on external variables in the current data flow graph and outside of that, false otherwise.

has_extended_global_df() → bool

Query Example

from glider import *


def query():
  instructions_extended = (
    Instructions()
    .exec(10, 10)
    .filter(lambda x: x.has_extended_global_df())
  )

  print(len(instructions_extended))

  return instructions_extended

Output Example

has_extended_global_df vs has_global_df

Let's dive into the difference between has_extended_global_df() and has_global_df().

The function has_extended_global_df() works recursively, whereas has_global_df() does not. In the previous example, as well as in the example using has_global_df(), no significant differences were observed. However, in the example below, we can clearly see the distinction between the two functions.

The following query demonstrates the difference: has_global_df() returns 259 instructions, while has_extended_global_df() returns 261 instructions.

Here is a query to highlight the difference:

from glider import *


def query():
  instructions_extended = ( # 261
    Instructions()
    .exec(500)
    .filter(lambda x: x.has_extended_global_df())
  )

  foo1 = set(instructions_extended)

  instructions = ( # 259
    Instructions()
    .exec(500)
    .filter(lambda x: x.has_global_df())
  )

  foo2 = set(instructions)

  res = []

  difference = foo1 - foo2

  for ins in difference:
    res.append(ins)

  return res

Here is the output