uniprotparser 1.0.6

Getting Uniprot Data from Uniprot Accession ID through Uniprot REST API

UniProt Database Web Parser Project

TLDR: This parser can be used to parse UniProt accession id and obtain related data from the UniProt web database.

With version 1.0.5, support for asyncio through aiohttp has been added to betaparser. Usage can be seen as follow

from uniprotparser.betaparser import UniprotParser
from io import StringIO
import asyncio
import pandas as pd

async def main():
    example_acc_list = ["Q99490", "Q8NEJ0", "Q13322", "P05019", "P35568", "Q15323"]
    parser = UniprotParser()
    df = []
    #Yield result for 500 accession ids at a time
    async for r in parser.parse_async(ids=example_acc_list):
        df.append(pd.read_csv(StringIO(r), sep="\t"))
    
    #Check if there were more than one result and consolidate them into one dataframe
    if len(df) > 0:
        df = pd.concat(df, ignore_index=True)
    else:
        df = df[0]

asyncio.run(main())

With version 1.0.2, support for the new UniProt REST API have been added under betaparser module of the package.

In order to utilize this new module, you can follow the example bellow

from uniprotparser.betaparser import UniprotParser
from io import StringIO

import pandas as pd
example_acc_list = ["Q99490", "Q8NEJ0", "Q13322", "P05019", "P35568", "Q15323"]
parser = UniprotParser()
df = []
#Yield result for 500 accession ids at a time
for r in parser.parse(ids=example_acc_list):
    df.append(pd.read_csv(StringIO(r), sep="\t"))

#Check if there were more than one result and consolidate them into one dataframe
if len(df) > 0:
    df = pd.concat(df, ignore_index=True)
else:
    df = df[0]

---

To parse UniProt accession with legacy API

from uniprotparser.parser import UniprotSequence

protein_id = "seq|P06493|swiss"

acc_id = UniprotSequence(protein_id, parse_acc=True)

#Access ACCID
acc_id.accession

#Access isoform id
acc_id.isoform

To get additional data from UniProt online database

from uniprotparser.parser import UniprotParser
from io import StringIO
#Install pandas first to handle tabulated data
import pandas as pd

protein_accession = "P06493"

parser = UniprotParser([protein_accession])

#To get tabulated data
result = []
for i in parser.parse("tab"):
    tab_data = pd.read_csv(i, sep="\t")
    last_column_name = tab_data.columns[-1]
    tab_data.rename(columns={last_column_name: "query"}, inplace=True)
    result.append(tab_data)
fin = pd.concat(result, ignore_index=True)

#To get fasta sequence
with open("fasta_output.fasta", "wt") as fasta_output:
    for i in parser.parse():
        fasta_output.write(i)