Update st.cache

apps/h_index.py

@@ -9,7 +9,7 @@ if "dsl" not in st.session_state:
     st.session_state["dsl"] = scholarpy.Dsl()
 
 
-@st.cache
+@st.cache_data
 def the_H_function(sorted_citations_list, n=1):
     """from a list of integers [n1, n2 ..] representing publications citations,
     return the max list-position which is >= integer
@@ -41,7 +41,7 @@ def dim_login(key=None, endpoint=None):
         raise Exception("Failed to login to Dimensions")
 
 
-@st.cache
+@st.cache_data
 def get_pubs_df(dsl, researcher_id):
 
     q = """search publications where researchers.id = "{}" return publications[id+title+doi+times_cited] sort by times_cited limit 1000"""
@@ -50,7 +50,7 @@ def get_pubs_df(dsl, researcher_id):
     return pubs.as_dataframe()
 
 
-@st.cache
+@st.cache_data
 def get_citations(df):
     return list(df.fillna(0)["times_cited"])
 

apps/journal.py

@@ -25,13 +25,13 @@ def read(filename_dot_csv):
     return df
 
 
-@st.cache
+@st.cache_data
 def get_token():
 
     return os.environ.get("DIM_TOKEN")
 
 
-@st.cache
+@st.cache_data
 def get_journals():
 
     with open("data/journals.json") as f:
@@ -40,7 +40,7 @@ def get_journals():
     return journals
 
 
-@st.cache
+@st.cache_data
 def read_excel(sheet_name):
 
     df = pd.read_excel(

apps/researcher.py

@@ -9,7 +9,7 @@ if "dsl" not in st.session_state:
     st.session_state["dsl"] = scholarpy.Dsl()
 
 
-@st.cache(allow_output_mutation=True)
+@st.cache_data
 def get_geonames():
     return scholarpy.get_geonames()
 
@@ -57,8 +57,7 @@ def annual_collaborators(pubs, col="year"):
 def annual_citations(pubs, col="year"):
     if pubs is not None:
         df = pubs.groupby([col]).sum()
-        df2 = pd.DataFrame(
-            {"year": df.index, "citations": df["times_cited"].values})
+        df2 = pd.DataFrame({"year": df.index, "citations": df["times_cited"].values})
         fig = px.bar(
             df2,
             x="year",
@@ -107,8 +106,7 @@ def app():
 
                 info_df = json_to_df(id_info, transpose=True)
                 info_df.rename(
-                    columns={info_df.columns[0]: "Type",
-                             info_df.columns[1]: "Value"},
+                    columns={info_df.columns[0]: "Type", info_df.columns[1]: "Value"},
                     inplace=True,
                 )
                 with row1_col1:
@@ -132,14 +130,12 @@ def app():
 
                     with row1_col2:
                         st.header("Researcher statistics")
-                        columns = ["pubs", "collaborators",
-                                   "institutions", "cities"]
+                        columns = ["pubs", "collaborators", "institutions", "cities"]
                         selected_columns = st.multiselect(
                             "Select attributes to display:", columns, columns
                         )
                         if selected_columns:
-                            fig = scholarpy.annual_stats_barplot(
-                                df1, selected_columns)
+                            fig = scholarpy.annual_stats_barplot(df1, selected_columns)
                             st.plotly_chart(fig)
                         leafmap.st_download_button(
                             "Download data",
@@ -171,8 +167,7 @@ def app():
                         )
 
                         st.header("Publication counts with collaborators")
-                        collaborators = dsl.search_researcher_collaborators(
-                            id, pubs)
+                        collaborators = dsl.search_researcher_collaborators(id, pubs)
                         markdown = f"""
                         - Total number of collaborators: **{len(collaborators)}**
                         """

multiapp.py

@@ -1,8 +1,9 @@
 """Frameworks for running multiple Streamlit applications as a single app.
 """
+
 import streamlit as st
 
-# app_state = st.experimental_get_query_params()
+# app_state = st.query_params
 # app_state = {k: v[0] if isinstance(v, list) else v for k, v in app_state.items()} # fetch the first item in each query string as we don't have multiple values for each query string key in this example
 
 
@@ -41,7 +42,7 @@ class MultiApp:
         self.apps.append({"title": title, "function": func})
 
     def run(self):
-        app_state = st.experimental_get_query_params()
+        app_state = st.query_params
         app_state = {
             k: v[0] if isinstance(v, list) else v for k, v in app_state.items()
         }  # fetch the first item in each query string as we don't have multiple values for each query string key in this example

streamlit_app.py

@@ -27,13 +27,13 @@ apps = {
     "researcher": {"title": "Researcher", "icon": "person-circle"},
     "orcid": {"title": "ORCID", "icon": "person-square"},
     "organization": {"title": "Organization", "icon": "building"},
-    "google": {"title": "Google Scholar", "icon": "google"},
+    # "google": {"title": "Google Scholar", "icon": "google"},
 }
 
 
 titles = [app["title"] for app in apps.values()]
 icons = [app["icon"] for app in apps.values()]
-params = st.experimental_get_query_params()
+params = st.query_params
 
 if "page" in params:
     default_index = int(titles.index(params["page"][0].lower()))