Move functions to separate file

Middle_School_Card_Search.py

@@ -1,37 +1,7 @@
 import streamlit as st
 import pandas as pd
-import urllib.parse
 import streamlit_common.footer
-
-
-def compose_scryfall_url(x: str) -> str:
-    return f"https://scryfall.com/search?q=prefer%3Aoldest%20!%22{urllib.parse.quote_plus(x)}%22"
-
-
-def row_to_link(x: pd.DataFrame) -> None:
-    cardname = x["name"]
-    if x.name_ja is not "":
-        cardname = f"{cardname} / {x.name_ja}"
-    st.markdown(f"- [{cardname}]({x.link})")
-
-
-def get_legal_cardnames(cardname: str, mslist_df: pd.DataFrame) -> list:
-    english_match = mslist_df[mslist_df["name"].str.lower() == cardname.lower()]
-    cardname_en_list = None
-    if english_match.shape[0] > 0:
-        cardname_en_list = english_match["name"].to_list()
-        cardname_ja_list = english_match["name_ja"].to_list()
-    japanese_match = mslist_df[mslist_df["name_ja"] == cardname]
-    if japanese_match.shape[0] > 0:
-        cardname_en_list = japanese_match["name"].to_list()
-        cardname_ja_list = japanese_match["name_ja"].to_list()
-    if cardname_en_list is not None and len(cardname_en_list) > 0:
-        return [
-            cardname_en_list[0] or None,
-            cardname_ja_list[0] or None,
-        ]
-    return None
-
+import streamlit_common.lib as lib
 
 mslist_path = "output/middleschool.csv"
 number_shown_results = 20
@@ -54,7 +24,7 @@ mslist_df.fillna("", inplace=True)
 st.write(mslist_df.shape[0], "cards are legal")
 
 name_input = st.text_input(f"Search by card name").strip()
-exact_match = get_legal_cardnames(name_input, mslist_df)
+exact_match = lib.get_legal_cardnames(name_input, mslist_df)
 results_en_df = mslist_df[
     mslist_df["name"].str.contains(name_input.lower(), case=False)
 ]
@@ -68,12 +38,12 @@ if name_input:
         if exact_match[1] is not None:
             cardname = f"{cardname} / {exact_match[1]}"
         st.write(
-            f"✅ [{cardname}]({compose_scryfall_url(exact_match[0])}) is an exact match"
+            f"✅ [{cardname}]({lib.compose_scryfall_url(exact_match[0])}) is an exact match"
         )
     st.write(results_df.shape[0], f'cards found by "{name_input}"')
     if results_df.shape[0] > number_shown_results:
         st.write(f"Top {number_shown_results} results:")
-    results_df["link"] = results_df["name"].apply(compose_scryfall_url)
-    results_df[:number_shown_results].transpose().apply(row_to_link)
+    results_df["link"] = results_df["name"].apply(lib.compose_scryfall_url)
+    results_df[:number_shown_results].transpose().apply(lib.row_to_link)
 
 streamlit_common.footer.write_footer()

pages/1_Check_Card_List.py

@@ -1,23 +1,7 @@
 import streamlit as st
 import pandas as pd
-import re
 import streamlit_common.footer
-
-
-def remove_number_of_copies(line: str) -> str:
-    if len(line.strip()) < 1:
-        return None
-    pattern = re.compile("^([0-9]+) +")
-    return pattern.sub("", line)
-
-
-def is_cardname_legal(cardname: str, mslist_df: pd.DataFrame) -> bool:
-    if mslist_df[mslist_df["name"].str.lower() == cardname.lower()].shape[0] > 0:
-        return True
-    if mslist_df[mslist_df["name_ja"] == cardname].shape[0] > 0:
-        return True
-    return False
-
+import streamlit_common.lib as lib
 
 mslist_path = "output/middleschool.csv"
 
@@ -46,13 +30,13 @@ input_list = col1.text_area(
 cardnames = []
 
 for line in input_list.split("\n"):
-    cardname = remove_number_of_copies(line)
+    cardname = lib.remove_number_of_copies(line)
     if cardname is not None:
-        cardnames.append(remove_number_of_copies(cardname))
+        cardnames.append(lib.remove_number_of_copies(cardname))
 
 input_cards = pd.DataFrame(cardnames, columns=["cardname"])
 input_cards["legal"] = input_cards["cardname"].apply(
-    is_cardname_legal, args=[mslist_df]
+    lib.is_cardname_legal, args=[mslist_df]
 )
 
 col2.write("##### Middle School legality")

streamlit_common/lib.py

@@ -0,0 +1,48 @@
+import streamlit as st
+import pandas as pd
+import re
+import urllib.parse
+
+
+def compose_scryfall_url(x: str) -> str:
+    return f"https://scryfall.com/search?q=prefer%3Aoldest%20!%22{urllib.parse.quote_plus(x)}%22"
+
+
+def row_to_link(x: pd.DataFrame) -> None:
+    cardname = x["name"]
+    if x.name_ja is not "":
+        cardname = f"{cardname} / {x.name_ja}"
+    st.markdown(f"- [{cardname}]({x.link})")
+
+
+def get_legal_cardnames(cardname: str, mslist_df: pd.DataFrame) -> list:
+    english_match = mslist_df[mslist_df["name"].str.lower() == cardname.lower()]
+    cardname_en_list = None
+    if english_match.shape[0] > 0:
+        cardname_en_list = english_match["name"].to_list()
+        cardname_ja_list = english_match["name_ja"].to_list()
+    japanese_match = mslist_df[mslist_df["name_ja"] == cardname]
+    if japanese_match.shape[0] > 0:
+        cardname_en_list = japanese_match["name"].to_list()
+        cardname_ja_list = japanese_match["name_ja"].to_list()
+    if cardname_en_list is not None and len(cardname_en_list) > 0:
+        return [
+            cardname_en_list[0] or None,
+            cardname_ja_list[0] or None,
+        ]
+    return None
+
+
+def remove_number_of_copies(line: str) -> str:
+    if len(line.strip()) < 1:
+        return None
+    pattern = re.compile("^([0-9]+) +")
+    return pattern.sub("", line)
+
+
+def is_cardname_legal(cardname: str, mslist_df: pd.DataFrame) -> bool:
+    if mslist_df[mslist_df["name"].str.lower() == cardname.lower()].shape[0] > 0:
+        return True
+    if mslist_df[mslist_df["name_ja"] == cardname].shape[0] > 0:
+        return True
+    return False