-
-
Notifications
You must be signed in to change notification settings - Fork 0
/
diagram.py
119 lines (98 loc) · 3.62 KB
/
diagram.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
# Copyright (C) 2023-2024 Sebastien Rousseau.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from diagrams import Diagram, Cluster
from diagrams.custom import Custom
from diagrams.azure.compute import FunctionApps
# Define custom components
class Transcription(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
class Analysis(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
class Reports(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
class Storage(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
class SpeechTextServer(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
class Translations(Custom):
def __init__(self, label, icon_path):
super().__init__(label, icon_path)
# Define the graph attributes
graph_attr = {
"bgcolor": "#fafafa",
"fontcolor": "#0171e3",
"fontname": "Arial",
"fontsize": "50",
"pad": "0.618",
"rankdir": "LR",
"concentrate": "true",
}
# Create the diagram with the filename specifying the output format
with Diagram(
"Audio Analyser Architecture",
show=False,
filename='audio-analyser-architecture',
graph_attr=graph_attr
):
# Define the "Source" cluster
with Cluster("Source"):
audio_recorder = FunctionApps(
"Audio files",
) # Create an audio recorder component
# Define the "Targets" cluster with a top-to-bottom direction
with Cluster("Targets", direction="TB"):
# Define the "Data Flow" cluster
with Cluster("Data Flow"):
analyze = Analysis(
"Analysis",
"./icons/analyze.png"
) # Create an analysis component
recommend = Reports(
"Reports",
"./icons/recommend.png"
) # Create a reports component
transcribe = Transcription(
"Transcription",
"./icons/transcribe.png"
) # Create a transcription component
translate = Translations(
"Translations",
"./icons/translate.png"
) # Create a translations component
# Define the "Data Lake" cluster
with Cluster("Data Lake"):
store = Storage(
"Storage",
"./icons/store.png"
) # Create a storage component
# Define the "Event Driven" cluster
with Cluster("Event Driven"):
# Define the "Processing" cluster
with Cluster("Processing"):
# Connect data flow components
transcribe >> analyze >> recommend >> translate
# Define the "Serverless" cluster
with Cluster("Serverless"):
# Create a server component
server = SpeechTextServer("Server", "./icons/server.png")
# Connect the audio recorder to transcription component
audio_recorder >> transcribe
# Connect storage to transcription component (reversed arrow)
store << transcribe