api_examples

# UniProt API 示例 与 UniProt REST API 交互的多语言实用代码示例。 ## Python 示例 ### 示例 1：基础搜索 python import requests # 搜索人类胰岛素蛋白质 url = "https://rest.uniprot.org/uniprotkb/search" params = { "query": "insulin AND organism_id:9606 AND reviewed:true", "format": "json", "size": 10 } response = requests.get(url, params=params) data = response.json() for result in data['results']: print(f"{result['primaryAccession']}: {result['proteinDescription']['recommendedName']['fullName']['value']}") ### 示例 2：检索蛋白质序列 python import requests # 以 FASTA 格式获取人类胰岛素序列 accession = "P01308" url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta" response = requests.get(url) print(response.text) ### 示例 3：自定义字段 python import requests # 仅获取特定字段 url = "https://rest.uniprot.org/uniprotkb/search" params = { "query": "gene:BRCA1 AND reviewed:true", "format": "tsv", "fields": "accession,gene_names,organism_name,length,cc_function" } response = requests.get(url, params=params) print(response.text) ### 示例 4：ID 映射 python import requests import time def map_uniprot_ids(ids, from_db, to_db): # 提交任务 submit_url = "https://rest.uniprot.org/idmapping/run" data = { "from": from_db, "to": to_db, "ids": ",".join(ids) } response = requests.post(submit_url, data=data) job_id = response.json()["jobId"] # 轮询完成状态 status_url = f"https://rest.uniprot.org/idmapping/status/{job_id}" while True: response = requests.get(status_url) status = response.json() if "results" in status or "failedIds" in status: break time.sleep(3) # 获取结果 results_url = f"https://rest.uniprot.org/idmapping/results/{job_id}" response = requests.get(results_url) return response.json() # 将 UniProt ID 映射到 PDB ids = ["P01308", "P04637"] mapping = map_uniprot_ids(ids, "UniProtKB_AC-ID", "PDB") print(mapping) ### 示例 5：流式传输大数据集 python import requests # 流式传输所有已审阅的人类蛋白质 url = "https://rest.uniprot.org/uniprotkb/stream" params = { "query": "organism_id:9606 AND reviewed:true", "format": "fasta" } response = requests.get(url, params=params, stream=True) # 分块处理 with open("human_proteins.fasta", "wb") as f: for chunk in response.iter_content(chunk_size=8192): f.write(chunk)