Copy over function for reading csv.

Callout to get states and counties.
Merge state and county list. moved merge logic to counties method, dont care much for reusability right now I dont think.
Make class models' properties strings due to dumb leading 0s from geo api.

rules-engine/scripts/validate_counties.py

@@ -0,0 +1,145 @@
+import csv
+import json
+import os
+import pathlib
+from pydantic import BaseModel
+from typing import List
+import requests
+from requests import Response
+import io
+
+DESIGN_TEMP_DIR = pathlib.Path(__file__).parent / ".." / ".." / "design_temp"
+CENSUS_DOCS_BASE_URL = "https://www2.census.gov/geo/docs/reference"
+CENSUS_STATE_PATH = "/state.txt"
+CENSUS_COUNTY_PATH = "/codes2020/national_county2020.txt"
+CENSUS_DELIMETER = '|'
+NEW_LINE = '\n'
+NEW_HEADERS=["state_id","state_name","state_abbr","county_fp","county_ns","county_name","county_design_temp"]
+
+class State(BaseModel):
+    state_id: str
+    state_abbr: str
+    state_name: str
+
+#STATE(the 2 letter abbr)|STATEFP(the id)|COUNTYFP(3 digit code)|COUNTYNS(8digit unique)|COUNTYNAME
+class County(BaseModel):
+    state_id: str
+    state_abbr: str
+    state_name: str
+    county_fp: str
+    county_ns: str
+    county_name: str
+
+class DTBC(BaseModel):
+    state: str
+    county: str
+    temp: int
+
+_counties = {}
+_states={}
+_design_temp={}
+def load_design_temp_data():
+    result = {}
+
+    with open(DESIGN_TEMP_DIR / "design_temp_by_county.csv") as f:
+        reader = csv.DictReader(f)
+        for row in reader:
+            item = DTBC(
+                state=row["state"], county=row["county"],temp=row["design_temp"]
+            )
+            if row["state"] in result:
+                # result[row["state"]].append(row["county"])
+                result[row["state"]].append(item) 
+            else:
+                # result[row["state"]] = [row["county"]]
+                result[row["state"]] = [item]
+
+
+
+    return result
+
+def fetch_census_counties():
+    census_url = CENSUS_DOCS_BASE_URL + CENSUS_COUNTY_PATH
+
+    response = requests.get(census_url)
+    ret = {}
+    reader = csv.DictReader(f=io.StringIO(response.text),delimiter=CENSUS_DELIMETER)
+
+    for row in reader:
+        sid = row["STATEFP"]
+        sn = _states[sid].state_name
+        item = County(
+            state_id=sid, state_abbr=_states[sid].state_abbr, state_name=sn,county_fp=row["COUNTYFP"], county_ns=row["COUNTYNS"],county_name=row["COUNTYNAME"]
+        )
+        _counties[sn].append(item)
+
+
+
+    # this way sucks. would need to loop over each county when combining with states values.
+    # for row in reader:
+    #     item = County(
+    #         state_id=row["STATEFP"], county_fp=row["COUNTYFP"], county_ns=row["COUNTYNS"],county_name=row["COUNTYNAME"]
+    #     )
+    #     ret.append(item)
+    # return ret
+
+def fetch_census_states():
+    states_url = CENSUS_DOCS_BASE_URL + CENSUS_STATE_PATH
+
+    response = requests.get(states_url)
+    reader = csv.DictReader(f=io.StringIO(response.text),delimiter=CENSUS_DELIMETER)
+
+    for row in reader:
+        _counties[row["STATE_NAME"]] = []
+        item = State(
+            state_id=row["STATE"], state_abbr=row["STUSAB"], state_name=row["STATE_NAME"]
+        )
+        _states[row["STATE"]] = item
+    return _states
+    # This way blows. maybe a dict instead
+    # for row in reader:
+    #     item = State(
+    #         state_id=row["STATE"], state_abbr=row["STUSAB"], state_name=row["STATE_NAME"]
+    #     )
+    #     ret.append(item)
+    # return ret
+    # return process(response)
+
+    # woof, no need for this. just use fancy dictreader on response text property.
+    # token_count = start_p = end_p = idx = 0
+    # line = []
+
+    # for c in response.iter_content():
+    #     line.append(c)
+    #     if c == CENSUS_DELIMETER:
+    #         token_count += 1
+    #     elif c == NEW_LINE:
+    #         token_count = start_p = end_p = 0
+
+
+
+
+states = fetch_census_states()
+counties = fetch_census_counties()
+# print(_counties)
+dtbc = load_design_temp_data()
+# print(dtbc)
+with open("merged_structure_temps.csv", "w", newline="") as oFile:
+    writer = csv.DictWriter(oFile, fieldnames=NEW_HEADERS)
+    writer.writeheader()
+    for s, cbs in _counties.items():
+        # print(f"S: {s} => CBS: {cbs}")
+        for d in dtbc[s]:
+            for c in cbs:
+                if d.county in c.county_name:
+                    ostr=f"{c.state_id},{s},{c.state_abbr},{c.county_fp},{c.county_ns},{d.county}"
+                    print(ostr) # Writer here
+        # exit()
+#avoid all this bs by doing it in the counties fetch
+# intermediate=[]
+# for id,state in states.items():
+#     print(_counties[id])
+#     for c in _counties[id]:
+#         print(str(c.state_id))
+#     exit()
+    # for county in counties