That is simply incorrect.
The algorithim will always test all nearby tiles, in order to obtain the weight and if it's passible in the first place. This weight depends on distance as well as traffic designation, and so is not the same for every tile. The distance portion could be computed without querying the tile data, but the passibility and traffic designation cannot, even if it is 1. Algothimically, an impassible tile is identical to a tile with traffic designation infinity. Then the algotithim tries the tile with the lowest weight, and will test the weight of all adjacent tiles to that, expect the ones already tried. It will keep trying the tile with the lowest weight, untill it reaches the goal tile, which should have weight 0. The algorithim internally tracks how it reached each tile, and upon reaching the goal can backtrack to the origin, thus determining the path.
This description of DF pathing is based on Toady's statement that pathing is essentially A*, and my undertanding of the A* algorithim and how it could reasonably be modified.
I believe you are confused with how the heuristic works.
Toady uses modified A* with a
Manhattan Heuristic that is also modified to work 3d.
The heuristic guides where A* tries to path to first, but it does not change the weight of the tiles, the weight of the tiles is compared to the heuristic's expectations. If the heuristic's expected path is at or below the weight it expects in a shortest possible path, it will simply follow that path. If the weight is higher than what it expects, it will start reading and testing other tiles until it cannot find one that actually saves it distance compared to the heuristic's guess. Having a lowest-possible weight prevents the game from testing the weights of adjacent tiles.
If you have a straight horizontal walk from point "A" on the west side of the screen, and a point "B" on the east side, then with all weights being 1, the game will push all the tiles around "A" into the "open list", but not actually read anything but the one tile directly east of it, since heading directly east is the heuristic's best guess. When it hits this east tile, it will push the locations of the three newly adjacent tiles into the "open" list without having to read them at that moment. This will continue until you hit "B". You functionally have to push three times as many tiles into the open list as you have to actually travel, but do not have to actually fetch the data on weights for more than those tiles you need to walk on.
If you have a uniform weight that is higher than what the heuristic expects, however, then the heuristic will see that the path due east will take longer than the heuristic expected, and so try to read the northeast and southeast tiles' information to see if they are going to be weight 1. If the weight is higher than that, they may start searching all the other directions, as well. Each time the game searches these tiles for their weights, all
their adjacent tiles get added, as well. This means that even with a weight of 2, you are adding 5 times as many tiles as you actually need to walk on to the open list, and you are searching 3 times as many tiles for their actual weight information.