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Update app.py

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  1. app.py +78 -52
app.py CHANGED
@@ -2,66 +2,92 @@ import streamlit as st
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  import pandas as pd
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  import os
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- st.set_page_config(page_title="F-16 Information", page_icon=":airplane:", layout="wide")
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- # Create a DataFrame for the F-16 (no need for CSV if only one aircraft)
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- f16_data = {
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- "Aircraft Name": "General Dynamics F-16 Fighting Falcon",
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- "Image URL": "data:image/jpeg;base64,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", # Replace with the actual filename (for Hugging Face) or URL
11
- "Origin": "United States",
12
- "Manufacturer": "General Dynamics",
13
- "First Flight": 1974,
14
- "Introduction": 1979,
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- "Role": "Multirole fighter",
16
- "Variants": "F-16A, F-16B, F-16C, F-16D",
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- "Crew": 1,
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- "Capacity": "N/A",
19
- "Length (m)": 15.03,
20
- "Wingspan (m)": 9.96,
21
- "Height (m)": 5.09,
22
- "Max Speed (km/h)": 2414,
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- "Range (km)": 3400,
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- "Service Ceiling (m)": 15240,
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- "Description": "The General Dynamics F-16 Fighting Falcon is a multirole fighter aircraft originally developed by General Dynamics for the United States Air Force. It is a highly versatile aircraft and has been exported to many countries."
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
26
  }
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- aircraft_info = pd.DataFrame([f16_data]).iloc[0] # Convert the dictionary to match the previous code
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29
- st.title("F-16 Information")
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31
- st.subheader(aircraft_info["Aircraft Name"])
 
32
 
33
- image_path = aircraft_info["Image URL"]
 
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35
- if image_path:
36
- if os.path.exists(image_path):
37
- st.image(image_path, use_column_width=True, caption=aircraft_info["Aircraft Name"])
38
- else:
39
- try:
 
40
  st.image(image_path, use_column_width=True, caption=aircraft_info["Aircraft Name"])
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- except Exception as e:
42
- st.error(f"Error displaying image: {e}. Check the URL/path in the CSV.") # Modified error message
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- else:
44
- st.warning("No image URL provided for this aircraft.")
 
 
 
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- col1, col2 = st.columns(2)
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48
- with col1:
49
- st.write(f"**Origin:** {aircraft_info['Origin']}")
50
- st.write(f"**Manufacturer:** {aircraft_info['Manufacturer']}")
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- st.write(f"**First Flight:** {aircraft_info['First Flight']}")
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- st.write(f"**Introduction:** {aircraft_info['Introduction']}")
53
- st.write(f"**Role:** {aircraft_info['Role']}")
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55
- with col2:
56
- st.write(f"**Variants:** {aircraft_info['Variants']}")
57
- st.write(f"**Crew:** {aircraft_info['Crew']}")
58
- st.write(f"**Capacity:** {aircraft_info['Capacity']}")
59
- st.write(f"**Length:** {aircraft_info['Length (m)']} m")
60
- st.write(f"**Wingspan:** {aircraft_info['Wingspan (m)']} m")
61
- st.write(f"**Height:** {aircraft_info['Height (m)']} m")
62
- st.write(f"**Max Speed:** {aircraft_info['Max Speed (km/h)']} km/h")
63
- st.write(f"**Range:** {aircraft_info['Range (km)']} km")
64
- st.write(f"**Service Ceiling:** {aircraft_info['Service Ceiling (m)']} m")
65
 
66
- with st.expander("Detailed Description"):
67
- st.write(aircraft_info["Description"])
 
2
  import pandas as pd
3
  import os
4
 
5
+ st.set_page_config(page_title="Fighters Information", page_icon=":airplane:", layout="wide")
6
 
7
+ # Create a DataFrame for the F-16 and F-15
8
+ aircraft_data = {
9
+ "F-16": {
10
+ "Aircraft Name": "General Dynamics F-16 Fighting Falcon",
11
+ "Image URL": "f16.jpg", # Replace with the actual filename (for Hugging Face) or URL
12
+ "Origin": "United States",
13
+ "Manufacturer": "General Dynamics",
14
+ "First Flight": 1974,
15
+ "Introduction": 1979,
16
+ "Role": "Multirole fighter",
17
+ "Variants": "F-16A, F-16B, F-16C, F-16D",
18
+ "Crew": 1,
19
+ "Capacity": "N/A",
20
+ "Length (m)": 15.03,
21
+ "Wingspan (m)": 9.96,
22
+ "Height (m)": 5.09,
23
+ "Max Speed (km/h)": 2414,
24
+ "Range (km)": 3400,
25
+ "Service Ceiling (m)": 15240,
26
+ "Description": "The General Dynamics F-16 Fighting Falcon is a multirole fighter aircraft originally developed by General Dynamics for the United States Air Force. It is a highly versatile aircraft and has been exported to many countries."
27
+ },
28
+ "F-15": {
29
+ "Aircraft Name": "McDonnell Douglas F-15 Eagle",
30
+ "Image URL": "f15.jpg", # Replace with the actual filename (for Hugging Face) or URL
31
+ "Origin": "United States",
32
+ "Manufacturer": "McDonnell Douglas (now Boeing)",
33
+ "First Flight": 1972,
34
+ "Introduction": 1976,
35
+ "Role": "Air superiority fighter",
36
+ "Variants": "F-15A, F-15B, F-15C, F-15D, F-15E",
37
+ "Crew": 1 (F-15C/E), 2 (F-15B/D) ",
38
+ "Capacity": "N/A",
39
+ "Length (m)": 19.43,
40
+ "Wingspan (m)": 13.05,
41
+ "Height (m)": 5.63,
42
+ "Max Speed (km/h)": 3000+,
43
+ "Range (km)": 4445,
44
+ "Service Ceiling (m)": 18000+,
45
+ "Description": "The McDonnell Douglas F-15 Eagle is an American twin-engine, all-weather tactical fighter aircraft designed by McDonnell Douglas. It is among the most successful modern fighters, with over 100 victories in air-to-air combat without a loss."
46
+ }
47
  }
 
48
 
49
+ st.title("Fighter Information")
50
 
51
+ aircraft_names = list(aircraft_data.keys()) # Get the names of the aircraft
52
+ selected_aircraft = st.selectbox("Select an Aircraft", aircraft_names)
53
 
54
+ if selected_aircraft:
55
+ aircraft_info = pd.DataFrame([aircraft_data[selected_aircraft]]).iloc[0] # Select data for the chosen aircraft
56
 
57
+ st.subheader(aircraft_info["Aircraft Name"])
58
+
59
+ image_path = aircraft_info["Image URL"]
60
+
61
+ if image_path:
62
+ if os.path.exists(image_path):
63
  st.image(image_path, use_column_width=True, caption=aircraft_info["Aircraft Name"])
64
+ else:
65
+ try:
66
+ st.image(image_path, use_column_width=True, caption=aircraft_info["Aircraft Name"])
67
+ except Exception as e:
68
+ st.error(f"Error displaying image: {e}. Check the URL/path in the CSV.") # Modified error message
69
+ else:
70
+ st.warning("No image URL provided for this aircraft.")
71
 
72
+ col1, col2 = st.columns(2)
73
 
74
+ with col1:
75
+ st.write(f"**Origin:** {aircraft_info['Origin']}")
76
+ st.write(f"**Manufacturer:** {aircraft_info['Manufacturer']}")
77
+ st.write(f"**First Flight:** {aircraft_info['First Flight']}")
78
+ st.write(f"**Introduction:** {aircraft_info['Introduction']}")
79
+ st.write(f"**Role:** {aircraft_info['Role']}")
80
 
81
+ with col2:
82
+ st.write(f"**Variants:** {aircraft_info['Variants']}")
83
+ st.write(f"**Crew:** {aircraft_info['Crew']}")
84
+ st.write(f"**Capacity:** {aircraft_info['Capacity']}")
85
+ st.write(f"**Length:** {aircraft_info['Length (m)']} m")
86
+ st.write(f"**Wingspan:** {aircraft_info['Wingspan (m)']} m")
87
+ st.write(f"**Height:** {aircraft_info['Height (m)']} m")
88
+ st.write(f"**Max Speed:** {aircraft_info['Max Speed (km/h)']} km/h")
89
+ st.write(f"**Range:** {aircraft_info['Range (km)']} km")
90
+ st.write(f"**Service Ceiling:** {aircraft_info['Service Ceiling (m)']} m")
91
 
92
+ with st.expander("Detailed Description"):
93
+ st.write(aircraft_info["Description"])