Update apps

Author: tcbegley

examples/advanced-component-usage/toast.py

@@ -102,6 +102,7 @@ def make_toast(message):
         is_open=True,
         dismissable=True,
         icon="danger",
+        className="mb-2",
     )
 
 

examples/gallery/faithful/app.py

@@ -14,7 +14,7 @@
 import plotly.figure_factory as ff
 from dash import Input, Output, dcc, html
 
-DATA = pd.read_csv("https://cdn.opensource.faculty.ai/old-faithful/data.csv")
+DATA = pd.read_csv("data.csv")
 
 app = dash.Dash(external_stylesheets=[dbc.themes.BOOTSTRAP])
 

examples/gallery/faithful/data.csv

@@ -0,0 +1,273 @@
+eruptions,waiting
+3.6,79
+1.8,54
+3.333,74
+2.283,62
+4.533,85
+2.883,55
+4.7,88
+3.6,85
+1.95,51
+4.35,85
+1.8330000000000002,54
+3.917,84
+4.2,78
+1.75,47
+4.7,83
+2.167,52
+1.75,62
+4.8,84
+1.6,52
+4.25,79
+1.8,51
+1.75,47
+3.45,78
+3.0669999999999997,69
+4.533,74
+3.6,83
+1.9669999999999999,55
+4.083,76
+3.85,78
+4.433,79
+4.3,73
+4.467,77
+3.367,66
+4.033,80
+3.833,74
+2.017,52
+1.867,48
+4.833,80
+1.8330000000000002,59
+4.783,90
+4.35,80
+1.883,58
+4.567,84
+1.75,58
+4.533,73
+3.3169999999999997,83
+3.833,64
+2.1,53
+4.633,82
+2.0,59
+4.8,75
+4.716,90
+1.8330000000000002,54
+4.833,80
+1.733,54
+4.883,83
+3.717,71
+1.6669999999999998,64
+4.567,77
+4.317,81
+2.233,59
+4.5,84
+1.75,48
+4.8,82
+1.817,60
+4.4,92
+4.167,78
+4.7,78
+2.0669999999999997,65
+4.7,73
+4.033,82
+1.9669999999999999,56
+4.5,79
+4.0,71
+1.983,62
+5.067,76
+2.017,60
+4.567,78
+3.883,76
+3.6,83
+4.133,75
+4.333,82
+4.1,70
+2.633,65
+4.067,73
+4.933,88
+3.95,76
+4.5169999999999995,80
+2.167,48
+4.0,86
+2.2,60
+4.333,90
+1.867,50
+4.817,78
+1.8330000000000002,63
+4.3,72
+4.667,84
+3.75,75
+1.867,51
+4.9,82
+2.483,62
+4.367,88
+2.1,49
+4.5,83
+4.05,81
+1.867,47
+4.7,84
+1.7830000000000001,52
+4.85,86
+3.6830000000000003,81
+4.7330000000000005,75
+2.3,59
+4.9,89
+4.417,79
+1.7,59
+4.633,81
+2.3169999999999997,50
+4.6,85
+1.817,59
+4.417,87
+2.617,53
+4.067,69
+4.25,77
+1.9669999999999999,56
+4.6,88
+3.767,81
+1.9169999999999998,45
+4.5,82
+2.267,55
+4.65,90
+1.867,45
+4.167,83
+2.8,56
+4.333,89
+1.8330000000000002,46
+4.383,82
+1.883,51
+4.933,86
+2.033,53
+3.733,79
+4.2330000000000005,81
+2.233,60
+4.533,82
+4.817,77
+4.333,76
+1.983,59
+4.633,80
+2.017,49
+5.1,96
+1.8,53
+5.033,77
+4.0,77
+2.4,65
+4.6,81
+3.5669999999999997,71
+4.0,70
+4.5,81
+4.083,93
+1.8,53
+3.967,89
+2.2,45
+4.15,86
+2.0,58
+3.833,78
+3.5,66
+4.583,76
+2.367,63
+5.0,88
+1.933,52
+4.617,93
+1.9169999999999998,49
+2.083,57
+4.583,77
+3.333,68
+4.167,81
+4.333,81
+4.5,73
+2.417,50
+4.0,85
+4.167,74
+1.883,55
+4.583,77
+4.25,83
+3.767,83
+2.033,51
+4.433,78
+4.083,84
+1.8330000000000002,46
+4.417,83
+2.1830000000000003,55
+4.8,81
+1.8330000000000002,57
+4.8,76
+4.1,84
+3.966,77
+4.2330000000000005,81
+3.5,87
+4.3660000000000005,77
+2.25,51
+4.667,78
+2.1,60
+4.35,82
+4.133,91
+1.867,53
+4.6,78
+1.7830000000000001,46
+4.367,77
+3.85,84
+1.933,49
+4.5,83
+2.383,71
+4.7,80
+1.867,49
+3.833,75
+3.417,64
+4.2330000000000005,76
+2.4,53
+4.8,94
+2.0,55
+4.15,76
+1.867,50
+4.2669999999999995,82
+1.75,54
+4.4830000000000005,75
+4.0,78
+4.117,79
+4.083,78
+4.2669999999999995,78
+3.917,70
+4.55,79
+4.083,70
+2.417,54
+4.183,86
+2.217,50
+4.45,90
+1.883,54
+1.85,54
+4.283,77
+3.95,79
+2.333,64
+4.15,75
+2.35,47
+4.933,86
+2.9,63
+4.583,85
+3.833,82
+2.083,57
+4.367,82
+2.133,67
+4.35,74
+2.2,54
+4.45,83
+3.5669999999999997,73
+4.5,73
+4.15,88
+3.8169999999999997,80
+3.917,71
+4.45,83
+2.0,56
+4.283,79
+4.7669999999999995,78
+4.533,84
+1.85,58
+4.25,83
+1.983,43
+2.25,60
+4.75,75
+4.117,81
+2.15,46
+4.417,90
+1.817,46
+4.467,74

examples/gallery/telephones-by-region/app.py

@@ -10,7 +10,7 @@
 import plotly.graph_objs as go
 from dash import Input, Output, dcc, html
 
-data = pd.read_csv("https://cdn.opensource.faculty.ai/world-phones/data.csv")
+data = pd.read_csv("data.csv")
 
 app = dash.Dash(external_stylesheets=[dbc.themes.BOOTSTRAP])
 

examples/gallery/telephones-by-region/data.csv

@@ -0,0 +1,8 @@
+Year,N.Amer,Europe,Asia,S.Amer,Oceania,Africa,Mid.Amer
+1951,45939,21574,2876,1815,1646,89,555
+1956,60423,29990,4708,2568,2366,1411,733
+1957,64721,32510,5230,2695,2526,1546,773
+1958,68484,35218,6662,2845,2691,1663,836
+1959,71799,37598,6856,3000,2868,1769,911
+1960,76036,40341,8220,3145,3054,1905,1008
+1961,79831,43173,9053,3338,3224,2005,1076

examples/gallery/wordcloud/app.py

@@ -6,30 +6,27 @@
 
 import base64
 import io
-from functools import lru_cache
-from urllib.request import urlopen
+from functools import cache
 
 import dash
 import dash_bootstrap_components as dbc
 from dash import Input, Output, dcc, html
 from wordcloud import WordCloud
 
-BASE_URL = "https://cdn.opensource.faculty.ai/wordcloud"
-
-DOCUMENT_URLS = {
-    "midsummer": f"{BASE_URL}/a-midsummer-nights-dream.txt",
-    "venice": f"{BASE_URL}/the-merchant-of-venice.txt",
-    "randj": f"{BASE_URL}/romeo-and-juliet.txt",
+DOCUMENT_PATHS = {
+    "midsummer": "data/a-midsummer-nights-dream.txt",
+    "venice": "data/the-merchant-of-venice.txt",
+    "randj": "data/romeo-and-juliet.txt",
 }
 
 
 # use lru_cache to memoise the frequencies
-@lru_cache(maxsize=3)
+@cache
 def load_word_frequencies(book):
-    url = DOCUMENT_URLS[book]
+    path = DOCUMENT_PATHS[book]
     WC = WordCloud(width=1000, height=600)
-    with urlopen(url) as f:
-        text = f.read().decode("utf-8")
+    with open(path) as f:
+        text = f.read()
     return WC.process_text(text)
 
 
@@ -104,6 +101,7 @@ def load_word_frequencies(book):
     ],
 )
 def make_wordcloud(book, min_freq, max_vocab):
+    print(book)
     # filter frequencies based on min_freq and max_vocab
     sorted_frequencies = sorted(
         load_word_frequencies(book).items(), key=lambda x: x[1], reverse=True