summaryrefslogtreecommitdiff
path: root/lib/imgradient_params_defaults.py
diff options
context:
space:
mode:
Diffstat (limited to 'lib/imgradient_params_defaults.py')
-rw-r--r--lib/imgradient_params_defaults.py42
1 files changed, 42 insertions, 0 deletions
diff --git a/lib/imgradient_params_defaults.py b/lib/imgradient_params_defaults.py
index 140939f..d0ba3ac 100644
--- a/lib/imgradient_params_defaults.py
+++ b/lib/imgradient_params_defaults.py
@@ -130,6 +130,48 @@ class ImGradientParams_FromDefaults(Pb_Api_Params):
{ "value" : "mirrored", "weight" : 1 },
{ "value" : "noise", "weight" : 1 },
]
+
+#I just needed a place to encapsulate the params and the weights, and methods to access them. I guess I didn't really know the right answer
+#as far as the structure, so I tried to just imagine something somewhat related to what you were talking about before.
+#do I need separate classes for the two methods below?
+#well lets dicusss this a bit more, so services each have own param set, they are sort of original from service itself, so i guess there should be a way to get
+#"fresh" copy of parameters accepted by this service, instead of rewriting code each time. do you mean just a list of the keynames? yeah and thier values
+#the keys don't have default values necessarily. they just each have a range of accepted values. Basically just html forms hmm sort of like
+#writing a bot that fills in some forms on the internet, like a bot to brute force a credit card form or something, funny example, but I guess a good one
+#each parameter has values that are within an accepted range, like First Name would need to come from a list of frist names, and CC number would need to bevel
+#intelligible ints, the first four should correspond with a known bank, etc. you understand what I mean? yeah
+ok so since all services are about same, just a bunch of parameters and known values we can make base class for parameteres. it would look like:
+
+
+class ApiParams(object):
+ def params():
+ def randomize():
+ def build():
+
+class ImGradientParams(ApiParams):
+ def __init__():
+ self.params = {
+ "width": # well here it's int i suppose, need somethig esle
+ "gradienttype": [
+ { "value "...}
+ ]
+ }
+
+class ImGradientPb_Api():
+ def params():
+ return new ImGradientParams()
+ def call(params):
+ return image();
+
+
+api = ImGradientPb_Api()
+image_params = api.params()
+image_params.gradient_type("mirror")
+image_params.randomize()
+image = api.call(image _params)
+# something like this, yeah I think so...lol I tried to do something like this
+
+
def from_random(self):
return {
"username" : USERNAME,