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import gradio as gr
import pandas as pd
# from groq import Groq
from dotenv import load_dotenv
from openpyxl import load_workbook
from openpyxl.styles import Alignment
os.environ['REQUESTS_CA_BUNDLE'] = '/usr/local/share/zscaler.crt'
load_dotenv()
def read_excel_and_process(fi):
excel_file = pd.ExcelFile(fi)
new_data = {}
row_names = ['8:30-9:50', '10-11:20', '11:30-12:50', '1-2:20', '2:30-3:50', '4-5:20', '6-7:20', '7:30-8:50']
col_names = ['Time', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday/Sunday']
column_widths = [15, 40, 40, 40, 40, 40, 40]
for t in row_names:
new_data[t] = {}
for d in col_names:
new_data[t][d] = []
for sheet_name in excel_file.sheet_names:
# print(f"Processing sheet: {sheet_name}")
df = excel_file.parse(sheet_name)
# row_index = df.index
# col_names = df.columns
for i in range(0, len(row_names)):
for j in range(1, len(col_names)):
cell_value = df.iat[i, j]
if pd.isna(cell_value):
continue
if str(cell_value).find('Common') > -1:
continue
row_name = row_names[i]
col_name = col_names[j]
new_data[row_name][col_name].append("{}, {}".format(str(cell_value).strip(), str(sheet_name).strip()))
print(f"Sheet: {sheet_name}, Row: {row_name}, Column: {col_name}, Value: {cell_value}")
for t, v in new_data.items():
for d, vv in v.items():
new_data[t][d].sort()
new_data[t][d] = "\n".join(new_data[t][d])
data_2 = []
for t, v in new_data.items():
v['Time'] = t
data_2.append(v)
df = pd.DataFrame.from_dict(data_2)
# df.to_excel("visualization.xlsx", index=False)
with pd.ExcelWriter('visualization.xlsx', engine='openpyxl') as writer:
df.to_excel(writer, sheet_name='Sheet1', index=False)
workbook = writer.book
worksheet = writer.sheets['Sheet1']
for i, width in enumerate(column_widths):
column_letter = chr(65 + i) # change index col to（A, B, C,...）
worksheet.column_dimensions[column_letter].width = width
for cell in worksheet[column_letter]:
cell.alignment = Alignment(wrap_text=True)
return "visualization.xlsx"
# def excel_to_csv(fi):
# df = pd.read_excel(fi)
# clm = []
# for c in df.columns:
# clm.append(c)
# df = df.to_csv(path_or_buf = "here2.csv")
# return gr.Dropdown(choices=clm, value=clm, label="Columns of the file", multiselect=True, allow_custom_value=True), "here2.csv"
with gr.Blocks() as demo:
# with gr.Tab("Course Schedule Visualization"):
gr.Markdown("## Visualize your course schedule.")
ex_fi = gr.File(file_count='single')
result_fi = gr.File(file_count='single')
# upload to process
ex_fi.upload(read_excel_and_process, inputs=ex_fi, outputs=result_fi)
# click to process
# btn_submit = gr.Button("Submit")
# btn_submit.click(text_to_neo4j, inputs=[remarks, columns], outputs=[result_fi,result_ta])/
demo.launch() |