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@bpostlethwaite
Last active February 10, 2020 19:05
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Fast Finance - Fast App
import base64
import io
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
import dash_table
import pandas as pd
external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(
children=[
html.H1(children="Hello Subscriptions!"),
dcc.Upload(
id="upload-data",
children=html.Div(["Drag and Drop or ", html.A("Select Files")]),
style={
"height": "180px",
"lineHeight": "180px",
"borderWidth": "1px",
"borderStyle": "dashed",
"borderRadius": "5px",
"textAlign": "center",
"margin": "40px",
},
# Allow multiple files to be uploaded
multiple=True,
),
html.Div(id="output-data-upload", style={"margin": "40px"}),
]
)
def parse_contents(contents, filename):
content_type, content_string = contents.split(",")
decoded = base64.b64decode(content_string)
if "csv" in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode("utf-8")),
names=["date", "desc", "debit", "credit", "balance"],
)
elif "xls" in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(
io.BytesIO(decoded), names=["date", "desc", "debit", "credit", "balance"]
)
return df
@app.callback(
Output("output-data-upload", "children"),
[Input("upload-data", "contents")],
[State("upload-data", "filename")],
)
def update_output(list_of_contents, list_of_names):
if list_of_contents is None:
raise PreventUpdate
try:
dfs = [parse_contents(c, n) for c, n in zip(list_of_contents, list_of_names)]
except Exception as e:
print(e)
return html.Div(["There was an error processing this file."])
df = pd.concat(dfs)
df = df.dropna(subset=["debit"])
df["date"] = pd.to_datetime(df["date"])
months = df.date.dt.month.unique()
if len(months) < 4:
return html.Div(["You must have at least 2 full months of data"])
months = months[1:-1]
first_month, months = months[0], months[1:]
m1 = df[df["date"].dt.month == first_month]["desc"]
is_rep = m1.isin(m1)
for m in months:
next_month = df[df["date"].dt.month == m]["desc"]
is_rep = is_rep & m1.isin(next_month)
rep = df[df["desc"].isin(m1[is_rep])]
rep = rep.drop(columns=["credit", "balance"])
rep["date"] = rep["date"].dt.strftime("%B %d, %Y")
return dash_table.DataTable(
id="table",
columns=[{"name": i, "id": i} for i in rep.columns],
data=rep.to_dict("records"),
)
if __name__ == "__main__":
app.run_server(debug=True)
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