Hello,
I’ve gone through the docs for using dcc.upload and have been able to reproduce the example. However, when I try uploading my .txt file, I get text that just says “There was an error processing this file.” but there is no traceback to go along with it since that’s part of the code. I believe this may have to do with the encoding piece and was wondering if there is a way to upload without this piece. I’m normally used to accessing this data in Jupyter with Pandas, but it doesn’t seem to translate into Dash the way I usually do it. Any help would be greatly appreciated.
My code:
app.layout = html.Div([
html.B('Please upload patient SNP data below. The file format should be .txt'),
html.Br(),
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
# Allow multiple files to be uploaded
multiple=True
),
html.Div(id='output-data-upload'),
])
def parse_contents(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
try:
if 'txt' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8'), delimiter = r'\s+'))
#dtype={'rsid':'str', 'chromosome':'object', 'position':'int', 'genotype':'str'}, comment='#'))
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded))
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
return html.Div([
html.H5(filename),
#html.H6(datetime.datetime.fromtimestamp(date)),
dash_table.DataTable(
data=df.to_dict('records'),
columns=[{'name': i, 'id': i} for i in df.columns]
),
html.Div(
[dcc.Markdown('''**There are {:.0f} matching SNPS**'''.format(len(df)))]
),
html.Hr(), # horizontal line
# For debugging, display the raw contents provided by the web browser
html.Div('Raw Content'),
html.Pre(contents[0:200] + '...', style={
'whiteSpace': 'pre-wrap',
'wordBreak': 'break-all'
})
])
@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 not None:
children = [
parse_contents(c, n) for c, n in
zip(list_of_contents, list_of_names)]
return children
How I normally convert the .txt file when using pandas:
data = pd.read_csv('my_genome.txt', sep='\t', dtype={'rsid':'str', 'chromosome':'object', 'position':'int', 'genotype':'str'}, comment='#')
the .txt file looks like this:
'# This data file generated by 23andMe at: Mon Mar 23 11:18:23 2020
'#
'# This file contains raw genotype data, including data that is not used in 23andMe reports.
'# This data has undergone a general quality review however only a subset of markers have been
'# individually validated for accuracy. As such, this data is suitable only for research,
'# educational, and informational use and not for medical or other use.
'#
'# Below is a text version of your data. Fields are TAB-separated
'# Each line corresponds to a single SNP. For each SNP, we provide its identifier
'# (an rsid or an internal id), its location on the reference human genome, and the
'# genotype call oriented with respect to the plus strand on the human reference sequence.
'# We are using reference human assembly build 37 (also known as Annotation Release 104).
'# Note that it is possible that data downloaded at different times may be different due to ongoing
'# improvements in our ability to call genotypes. More information about these changes can be >found at:
'# https://you.23andme.com/p/dfad0fe3300c6e2e/tools/data/download/
'#
'# More information on reference human assembly builds:
'# GRCh37 - hg19 - Genome - Assembly - NCBI
'#
rsid chromosome position genotype
rs548049170 1 69869 TT
rs13328684 1 74792 –
rs9283150 1 565508 AA
i713426 1 726912 AA
rs116587930 1 727841 GG
rs3131972 1 752721 GG