Spaces:
Sleeping
Sleeping
File size: 6,318 Bytes
c2a02c6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 |
import re
import time
import json
import zlib
from xml.etree import ElementTree
from urllib.parse import urlparse, parse_qs, urlencode
import requests
from requests.adapters import HTTPAdapter, Retry
from unipressed import IdMappingClient
## Code adapted from UniProt documentation.
def get_pdb_ids_2(protein_id):
POLLING_INTERVAL = 5
API_URL = "https://rest.uniprot.org"
retries = Retry(total=5, backoff_factor=0.25, status_forcelist=[500, 502, 503, 504])
session = requests.Session()
session.mount("https://", HTTPAdapter(max_retries=retries))
def check_response(response):
try:
response.raise_for_status()
except requests.HTTPError:
print(response.json())
raise
def submit_id_mapping(from_db, to_db, ids):
request = requests.post(
f"{API_URL}/idmapping/run",
data={"from": from_db, "to": to_db, "ids": ids},
)
check_response(request)
return request.json()["jobId"]
def get_next_link(headers):
re_next_link = re.compile(r'<(.+)>; rel="next"')
if "Link" in headers:
match = re_next_link.match(headers["Link"])
if match:
return match.group(1)
def check_id_mapping_results_ready(job_id):
while True:
request = session.get(f"{API_URL}/idmapping/status/{job_id}")
check_response(request)
j = request.json()
if "jobStatus" in j:
if j["jobStatus"] == "RUNNING":
print(f"Retrying in {POLLING_INTERVAL}s")
time.sleep(POLLING_INTERVAL)
else:
raise Exception(j["jobStatus"])
else:
return bool(j["results"] or j["failedIds"])
def get_batch(batch_response, file_format, compressed):
batch_url = get_next_link(batch_response.headers)
while batch_url:
batch_response = session.get(batch_url)
batch_response.raise_for_status()
yield decode_results(batch_response, file_format, compressed)
batch_url = get_next_link(batch_response.headers)
def combine_batches(all_results, batch_results, file_format):
if file_format == "json":
for key in ("results", "failedIds"):
if key in batch_results and batch_results[key]:
all_results[key] += batch_results[key]
elif file_format == "tsv":
return all_results + batch_results[1:]
else:
return all_results + batch_results
return all_results
def get_id_mapping_results_link(job_id):
url = f"{API_URL}/idmapping/details/{job_id}"
request = session.get(url)
check_response(request)
return request.json()["redirectURL"]
def decode_results(response, file_format, compressed):
if compressed:
decompressed = zlib.decompress(response.content, 16 + zlib.MAX_WBITS)
if file_format == "json":
j = json.loads(decompressed.decode("utf-8"))
return j
elif file_format == "tsv":
return [line for line in decompressed.decode("utf-8").split("\n") if line]
elif file_format == "xlsx":
return [decompressed]
elif file_format == "xml":
return [decompressed.decode("utf-8")]
else:
return decompressed.decode("utf-8")
elif file_format == "json":
return response.json()
elif file_format == "tsv":
return [line for line in response.text.split("\n") if line]
elif file_format == "xlsx":
return [response.content]
elif file_format == "xml":
return [response.text]
return response.text
def get_xml_namespace(element):
m = re.match(r"\{(.*)\}", element.tag)
return m.groups()[0] if m else ""
def merge_xml_results(xml_results):
merged_root = ElementTree.fromstring(xml_results[0])
for result in xml_results[1:]:
root = ElementTree.fromstring(result)
for child in root.findall("{http://uniprot.org/uniprot}entry"):
merged_root.insert(-1, child)
ElementTree.register_namespace("", get_xml_namespace(merged_root[0]))
return ElementTree.tostring(merged_root, encoding="utf-8", xml_declaration=True)
def get_id_mapping_results_search(url):
parsed = urlparse(url)
query = parse_qs(parsed.query)
file_format = query["format"][0] if "format" in query else "json"
if "size" in query:
size = int(query["size"][0])
else:
size = 500
query["size"] = size
compressed = (
query["compressed"][0].lower() == "true" if "compressed" in query else False
)
parsed = parsed._replace(query=urlencode(query, doseq=True))
url = parsed.geturl()
request = session.get(url)
check_response(request)
results = decode_results(request, file_format, compressed)
total = int(request.headers["x-total-results"])
for i, batch in enumerate(get_batch(request, file_format, compressed), 1):
results = combine_batches(results, batch, file_format)
if file_format == "xml":
return merge_xml_results(results)
return results
job_id = submit_id_mapping(
from_db="UniProtKB_AC-ID", to_db="PDB", ids=protein_id
)
if check_id_mapping_results_ready(job_id):
link = get_id_mapping_results_link(job_id)
results = get_id_mapping_results_search(link)
# Equivalently using the stream endpoint which is more demanding
# on the API and so is less stable:
# results = get_id_mapping_results_stream(link)
return [i['to'] for i in results['results']]
def get_pdb_ids(protein_id):
try:
request = IdMappingClient.submit(
source="UniProtKB_AC-ID", dest="PDB", ids={protein_id})
time.sleep(2.0)
pdb_list = list(request.each_result())
return [i['to'] for i in pdb_list]
except requests.exceptions.HTTPError:
get_pdb_ids_2(protein_id)
except KeyError:
get_pdb_ids_2(protein_id)
|