Aurelia Composition -


i trying create composition not getting i'd expect. in every instance i've tried similar setup different wrong gistrun representative far illustrates @ least "something" wrong.

i've searched high , low more information on specific functionality , syntax of compose can't seem solve issues.

in before mentioned gistrun can see container element not rendered correctly, h1 not rendered , @containerless being ignored.

in similar scenarios i've had containerless ignored on compose element resulting in rendering being ignored , i've had entire thing not working named slots.

i have feeling i'm doing wrong , can't quite figure out is. if knows i'm doing wrong or can point me solution obliged.

part of reason things aren't working expect gist based off of old version of framework. i've updated gist latest version of jeremy danyow's aurelia bundle here: https://gist.run/?id=1b304bb0c6dc98b23f4a3994acc280e4 old version of framework using in gist still used content element content projection.

there couple of reasons gist wouldn't run (aside mentioned above). first, compose element (and custom elements create) not self-closing. per custom element spec. <compose view="test.html" /> wont' work. second, there existing issue regarding containerless elements being used content projection. after talking team, issue unlikely resolved containerless custom elements aren't supported shadow dom v1 spec. if remove containerless attribute compose element, demo works. finally, forgot add <require from="container"></require> @ top of app.html file. aurelia unaware <ck-container> aurelia custom element. unless have globally registered custom element (or other view resource), must require in view wish use it.

now, let's discuss use of containerless. containerless decorator , attribute shouldn't used "clean up" html. should used when absolutely necessary achieve goals. "making html pretty" never absolutely necessary. when use containerless creating custom element cannot ever used standard custom element. again, aurelia team discourages using containerless elements unless necessary.

an example of valid reason use containerless expained in our documentation here: http://aurelia.io/hub.html#/doc/article/aurelia/framework/latest/cheat-sheet/4


-

Comments

Post a Comment

Popular posts from this blog

serialization - Convert Any type in scala to Array[Byte] and back -

i have following question: i have variable value in program declared value. i want convert value byte array.. how can serialize byte array , back? found examples related other types such double or int, not any. this should need. it's pretty similar how 1 in java. import java.io.{bytearrayinputstream, bytearrayoutputstream, objectinputstream, objectoutputstream} object serialization extends app { def serialise(value: any): array[byte] = { val stream: bytearrayoutputstream = new bytearrayoutputstream() val oos = new objectoutputstream(stream) oos.writeobject(value) oos.close stream.tobytearray } def deserialise(bytes: array[byte]): = { val ois = new objectinputstream(new bytearrayinputstream(bytes)) val value = ois.readobject ois.close value } println(deserialise(serialise("my test"))) println(deserialise(serialise(list(1)))) println(deserialise(serialise(map(1 -> 2)))) println(deserialise(seri
Read more

matplotlib support failed in PyCharm on OSX -

any idea how fix ? how can debug might problem ? not seem : https://youtrack.jetbrains.com/issue/py-15520 i in console: python 2.6.9 (unknown, jul 14 2015, 19:46:31) [gcc 4.2.1 compatible apple llvm 6.0 (clang-600.0.39)] on darwin >>> import matplotlib.pyplot plt matplotlib support failed the backend : >>> import matplotlib >>> print(matplotlib.rcparams['backend']) macosx
Read more

python - Matplotlib: TypeError: 'AxesSubplot' object is not callable -

i new programming please pardon me if rookie mistake. i writing python script have defined functions create subplots of distributions. i have slider widget end user change value of variables(mu , sigma) , see effect on distribution. here's code import numpy np print np.__version__ import scipy print scipy.__version__ scipy.stats import norm, lognorm, uniform import matplotlib print matplotlib.__version__ import matplotlib.pyplot plt matplotlib.widgets import slider, button, radiobuttons, checkbuttons #####calculating mean , standard deviation##### global mu_a1 mu_a1 = 1 global mu_b1 mu_b1 = 10 global mu_c1 mu_c1 = -13 global sigma_a1 sigma_a1 = 0.14 global sigma_b1 sigma_b1 = 1.16 global sigma_c1 sigma_c1 = 2.87 mu_x01 = -11 sigma_x01 = 1.9 #####_____##### #####generating random data##### a1 = 0.75*mu_a1 + (1.25 - 0.75)*sigma_a1*np.random.sample(10000) b1 = 8*mu_b1 + (12 - 8)*sigma_b1*np.random.sample(10000) c1 = -12*mu_c1 + 2*sigma_c1*np.random.sample(10000)
Read more