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import io
import time
import pandas as pd
import streamlit as st
# @st.cache_data
# def convert_dfs(dfs: list[pd.DataFrame], sheet_names: list[str]) -> bytes:
# # IMPORTANT: Cache the conversion to prevent computation on every rerun
# # Create a BytesIO object
# bytes_io = io.BytesIO()
# # Write the dataframes to the BytesIO object
# with pd.ExcelWriter(bytes_io, engine="xlsxwriter") as writer:
# for df, sheet_name in zip(dfs, sheet_names):
# df.to_excel(writer, sheet_name=sheet_name, index=True)
# # Get the bytes data
# bytes_data = bytes_io.getvalue()
# # Close the BytesIO object
# bytes_io.close()
# return bytes_data
def get_formats(workbook):
return {
"green": workbook.add_format(
{"bg_color": "#37CC73", "bold": True, "border": 1}
),
"blue": workbook.add_format({"bg_color": "#1A64FF", "bold": True, "border": 1}),
"blue_light": workbook.add_format(
{"bg_color": "#00B0F0", "bold": True, "border": 1}
),
"beurre": workbook.add_format(
{"bg_color": "#FFE699", "bold": True, "border": 1}
),
"orange": workbook.add_format(
{"bg_color": "#F47F31", "bold": True, "border": 1}
),
"purple5": workbook.add_format(
{"bg_color": "#E03DCD", "bold": True, "border": 1}
),
"purple6": workbook.add_format(
{"bg_color": "#AE83F8", "bold": True, "border": 1}
),
"gray": workbook.add_format({"bg_color": "#D9D9D9", "bold": True, "border": 1}),
"red": workbook.add_format({"bg_color": "#FF0000", "bold": True, "border": 1}),
}
def get_format_map_by_format_type(formats: dict, format_type: str) -> dict:
if format_type == "GSM_Analysis":
return {
# "name": formats["blue"],
"amrSegLoadDepTchRateLower": formats["beurre"],
"amrSegLoadDepTchRateUpper": formats["beurre"],
"dedicatedGPRScapacity": formats["beurre"],
"defaultGPRScapacity": formats["beurre"],
"number_trx_per_cell": formats["blue_light"],
"number_trx_per_bcf": formats["blue_light"],
"number_tch_per_cell": formats["blue"],
"number_sd_per_cell": formats["blue"],
"number_bcch_per_cell": formats["blue"],
"number_ccch_per_cell": formats["blue"],
"number_cbc_per_cell": formats["blue"],
"number_total_channels_per_cell": formats["blue"],
"number_signals_per_cell": formats["blue"],
"hf_rate_coef": formats["purple5"],
"GPRS": formats["purple5"],
"TCH Actual HR%": formats["green"],
"Offered Traffic BH": formats["green"],
"Max_Traffic BH": formats["green"],
"Avg_Traffic BH": formats["green"],
"Max_tch_call_blocking BH": formats["green"],
"Avg_tch_call_blocking BH": formats["green"],
"number_of_days_with_tch_blocking_exceeded": formats["green"],
"Max_sdcch_real_blocking BH": formats["green"],
"Avg_sdcch_real_blocking BH": formats["green"],
"number_of_days_with_sdcch_blocking_exceeded": formats["green"],
"TCH UTILIZATION (@Max Traffic)": formats["orange"],
"Target FR CHs": formats["purple6"],
"Target HR CHs": formats["purple6"],
"Target TCHs": formats["purple6"],
"Target TRXs": formats["purple6"],
"Numberof required TRXs": formats["purple6"],
}
elif format_type == "database":
return {
"code": formats["blue"],
"Azimut": formats["green"],
"Longitude": formats["green"],
"Latitude": formats["green"],
"Hauteur": formats["green"],
"number_trx_per_cell": formats["blue_light"],
"number_trx_per_bcf": formats["blue_light"],
"number_trx_per_site": formats["blue_light"],
}
# elif format_type == "LTE":
# return {
# "DL PRB Utilization": formats["orange"],
# "UL PRB Utilization": formats["orange"],
# "RSRP": formats["blue_light"],
# "RSRQ": formats["blue_light"],
# "Throughput (Mbps)": formats["green"],
# }
else:
return {} # No formatting if format_type not matched
def _apply_custom_formatting(
writer, df: pd.DataFrame, sheet_name: str, format_type: str
):
workbook = writer.book
worksheet = writer.sheets[sheet_name]
formats = get_formats(workbook)
format_map = get_format_map_by_format_type(formats, format_type)
for col_idx, col_name in enumerate(df.columns):
fmt = format_map.get(col_name)
if fmt:
worksheet.write(0, col_idx + 1, col_name, fmt)
def _write_to_excel(
dfs: list[pd.DataFrame], sheet_names: list[str], index=True, format_type: str = None
) -> bytes:
bytes_io = io.BytesIO()
with pd.ExcelWriter(bytes_io, engine="xlsxwriter") as writer:
for df, name in zip(dfs, sheet_names):
# df.index.name = "index"
df.to_excel(writer, sheet_name=name, index=index)
if format_type:
_apply_custom_formatting(writer, df, name, format_type)
return bytes_io.getvalue()
@st.cache_data
def convert_dfs(dfs: list[pd.DataFrame], sheet_names: list[str]) -> bytes:
return _write_to_excel(dfs, sheet_names, index=True)
@st.cache_data
def convert_gsm_dfs(dfs, sheet_names) -> bytes:
return _write_to_excel(dfs, sheet_names, index=True, format_type="GSM_Analysis")
@st.cache_data
def convert_database_dfs(dfs, sheet_names) -> bytes:
return _write_to_excel(dfs, sheet_names, index=True, format_type="database")
def save_dataframe(df: pd.DataFrame, sheet_name: str):
"""
Save the dataframe to a csv file.
Args:
df (pd.DataFrame): The dataframe to save.
sheet_name (str): The name of the sheet.
"""
df.to_csv(f"data2/{sheet_name}_{time.time()}.csv", index=False, encoding="latin1")
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