Upload app.py

app.py

@@ -77,10 +77,6 @@ def salary(work_year,
              job_title,
              country)-> str:
 
-    other_param = {}
-
-    other_param['gdp'] = get_gdp_by_country_code(country, work_year, 'NY.GDP.MKTP.CD')
-    other_param['cpi'] = get_gdp_by_country_code(country, work_year, 'FP.CPI.TOTL')
 
     jobs =   ['analytics_engineer',
              'applied_scientist',
@@ -119,7 +115,7 @@ def salary(work_year,
     role_flag = {}
 
     for name in role:
-        if role in job_title.lower():
+        if name in job_title.lower():
             role_flag[name]= True
         else:
             role_flag[name] = False
@@ -138,7 +134,6 @@ def salary(work_year,
         'L': 2,
     }
 
-    other_param['company_size'] = company_size_dic[company_size]
 
     experience_level_map = {
         'EN': 0,
@@ -147,33 +142,50 @@ def salary(work_year,
         'EX': 3
     }
 
-    other_param['experience_level'] = experience_level_map[experience_level]
 
-    params = {}
 
-    params.update(other_param)
-    params.update(jobs_flag)
+
+
+    params = {}
+    params['work_year'] = work_year
+    params['experience_level'] = experience_level_map[experience_level]
+    params['company_size'] = company_size_dic[company_size]
     params.update(currency_flag)
     params.update(role_flag)
+    params.update(jobs_flag)
+    params['gdp'] = get_gdp_by_country_code(country, work_year, 'NY.GDP.MKTP.CD')
+    params['cpi'] = get_gdp_by_country_code(country, work_year, 'FP.CPI.TOTL')
 
 
-    df = pd.DataFrame(params)
+
+    df = pd.DataFrame([params])
     print("Predicting")
     print(df)
+    print(df.columns)
 
     res = model.predict(df)
 
     print(f"{labels[res[0]]} $")
     return f"{labels[res[0]]} $"
 
-job_title_options = [
-        'Analytics Engineer', 'Applied Scientist', 'BI Developer',
-        'Business Intelligence Analyst', 'Business Intelligence Engineer',
-        'Data Analyst', 'Data Architect', 'Data Engineer', 'Data Manager',
-        'Data Science Consultant', 'Data Science Manager', 'Data Scientist',
-        'ML Engineer', 'Machine Learning Engineer', 'Machine Learning Scientist',
-        'Research Analyst', 'Research Engineer', 'Research Scientist'
-    ]
+job_title_options = ['analytics_engineer',
+             'applied_scientist',
+             'bi_developer',
+             'business_intelligence_analyst',
+             'business_intelligence_engineer',
+             'data_analyst',
+             'data_architect',
+             'data_engineer',
+             'data_manager',
+             'data_science_consultant',
+             'data_science_manager',
+             'data_scientist',
+             'ml_engineer',
+             'machine_learning_engineer',
+             'machine_learning_scientist',
+             'research_analyst',
+             'research_engineer',
+             'research_scientist']
 
 demo = gr.Interface(
     fn=salary,
@@ -182,12 +194,12 @@ demo = gr.Interface(
     allow_flagging="never",
     inputs=[
         gr.components.Number(label='work_year'),
-        gr.components.Select(label='experience_level', options=['EN', 'MI', 'SE', 'EX']),
-        gr.components.Select(label='company_size', options=['S', 'M', 'L']),
-        gr.components.Select(label='currency', options=['EUR', 'GBP', 'USD']),
-        gr.components.Select(label='job_title', options=job_title_options),
-        gr.components.TextInput(label='country')
+        gr.components.Radio(label='experience_level', choices=['EN', 'MI', 'SE', 'EX']),
+        gr.components.Radio(label='company_size', choices=['S', 'M', 'L']),
+        gr.components.Radio(label='currency', choices=['EUR', 'GBP', 'USD']),
+        gr.components.Dropdown(label='job_title', choices=job_title_options),
+        gr.components.Textbox(label='country', info='2 letter code', value='US')
     ],
     outputs=gr.Text())
 
-demo.launch(debug=True)
+demo.launch(debug=True, share=True)