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import base64
from pathlib import Path
from typing import Any
import pandas as pd
import streamlit as st
def get_pdf_iframe(pdf_to_process: str) -> str:
base64_pdf = base64.b64encode(Path(pdf_to_process).read_bytes()).decode("utf-8")
pdf_display = f"""
<iframe src="data:application/pdf;base64,{base64_pdf}
" width="100%" height="1000px" type="application/pdf"></iframe>
"""
return pdf_display
def set_algorithm_name(my_key: str) -> None:
st.session_state["algorithm_name"] = st.session_state[my_key]
@st.cache_data
def to_csv_file(df: pd.DataFrame) -> bytes:
# Populate the columns with the metadata, if available
# They may not be available if the user skipped the metadata page
# by not clicking on Submit
if "metadata" in st.session_state:
df = df.assign(company=st.session_state["metadata"]["company_name"])
df = df.assign(sector=st.session_state["metadata"]["sector"])
df = df.assign(year=st.session_state["metadata"]["year"])
df = df.assign(currency=st.session_state["metadata"]["currency"])
df = df.assign(unit=st.session_state["metadata"]["unit"])
df = df.assign(headquarter=st.session_state["metadata"]["headquarter"])
else:
df = df.assign(company="")
df = df.assign(sector="")
df = df.assign(year="")
df = df.assign(currency="")
df = df.assign(unit="")
df = df.assign(headquarter="")
return df.to_csv(index=False).encode("utf-8")
def set_state(key: Any, value: Any) -> None:
"""
Sets the session_state[key] to value.
key can be a list to reach nested values.
Ex: ["key1", "key2"] to reach session_state["key1"]["key2"] value.
"""
if isinstance(key, list):
key_list = key
nested_key_string = "session_state"
nested_value = st.session_state
for k in key_list[:-1]:
try:
nested_key_string += f"['{k}']"
nested_value = nested_value[k]
except KeyError as e:
raise KeyError(f"{nested_key_string} does not exist") from e
nested_value[key_list[-1]] = value
else:
st.session_state[key] = value
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