#!/usr/bin/env python3
"""
参数验证模块 - 简化但有效的参数验证
只验证真正重要的参数，防止滥用和性能问题
"""
class ValidationError(Exception):
"""参数验证错误"""
pass
def validate_common_params(
max_results: int = 20, species: str = "human", query_type: str = "auto"
) -> tuple[int, str]:
"""
验证通用参数
Args:
max_results: 最大结果数
species: 物种
query_type: 查询类型
Returns:
验证后的参数元组
Raises:
ValidationError: 参数验证失败
"""
# 验证max_results
if not isinstance(max_results, int):
raise ValidationError("max_results must be an integer")
if max_results < 1:
max_results = 1
elif max_results > 100:
max_results = 100
# 验证species
valid_species = {
"human": "9606",
"mouse": "10090",
"rat": "10116",
"zebrafish": "7955",
"fruitfly": "7227",
"worm": "6239",
# 直接支持NCBI taxid
"9606": "9606",
"10090": "10090",
"10116": "10116",
"7955": "7955",
"7227": "7227",
"6239": "6239",
}
if species not in valid_species:
# 记录警告但不抛出错误，使用默认值
species = "human"
# 验证query_type
valid_query_types = {
"auto",
"info",
"search",
"region",
"protein",
"gene_protein",
"ortholog",
"evolution",
"batch",
}
if query_type not in valid_query_types:
query_type = "auto"
return max_results, species, query_type
def validate_gene_params(
gene_symbol: str,
target_species: list | None = None,
analysis_level: str = "Eukaryota",
) -> tuple[str, list | None, str]:
"""
验证基因分析参数
Args:
gene_symbol: 基因符号
target_species: 目标物种列表
analysis_level: 分析层级
Returns:
验证后的参数元组
Raises:
ValidationError: 基因符号验证失败
"""
if not gene_symbol or not gene_symbol.strip():
raise ValidationError("Gene symbol cannot be empty")
gene_symbol = gene_symbol.strip()
# 验证target_species
if target_species is not None:
if not isinstance(target_species, list):
target_species = [target_species]
# 过滤有效物种
valid_species = {"human", "mouse", "rat", "zebrafish", "fruitfly", "worm"}
target_species = [s for s in target_species if s in valid_species]
if not target_species:
target_species = ["human"]
# 验证analysis_level
valid_levels = {"Eukaryota", "Metazoa", "Vertebrata", "Mammalia"}
if analysis_level not in valid_levels:
analysis_level = "Eukaryota"
return gene_symbol, target_species, analysis_level
def validate_kegg_params(
gene_list: list,
organism: str = "hsa",
pvalue_threshold: float = 0.05,
min_gene_count: int = 2,
) -> tuple[list, str, float, int]:
"""
验证KEGG通路分析参数
Args:
gene_list: 基因列表
organism: 生物体代码
pvalue_threshold: p值阈值
min_gene_count: 最小基因数量
Returns:
验证后的参数元组
Raises:
ValidationError: 基因列表验证失败
"""
if not gene_list or not isinstance(gene_list, list):
raise ValidationError("Gene list must be a non-empty list")
# 过滤有效的基因符号
valid_genes = []
for gene in gene_list:
if isinstance(gene, str) and gene.strip():
valid_genes.append(gene.strip())
if not valid_genes:
raise ValidationError("No valid gene symbols found in the list")
# 验证organism
valid_organisms = {"hsa", "mmu", "rno", "dre", "cel", "scf"}
if organism not in valid_organisms:
organism = "hsa"
# 验证pvalue_threshold
try:
pvalue_threshold = float(pvalue_threshold)
if pvalue_threshold <= 0 or pvalue_threshold >= 1:
pvalue_threshold = 0.05
except (ValueError, TypeError):
pvalue_threshold = 0.05
# 验证min_gene_count
try:
min_gene_count = int(min_gene_count)
if min_gene_count < 1:
min_gene_count = 1
elif min_gene_count > 10:
min_gene_count = 10
except (ValueError, TypeError):
min_gene_count = 2
return valid_genes, organism, pvalue_threshold, min_gene_count
def validate_search_params(
description: str, context: str = "genomics", max_results: int = 20
) -> tuple[str, str, int]:
"""
验证搜索参数
Args:
description: 搜索描述
context: 搜索上下文
max_results: 最大结果数
Returns:
验证后的参数元组
Raises:
ValidationError: 搜索描述验证失败
"""
if not description or not description.strip():
raise ValidationError("Search description cannot be empty")
description = description.strip()
# 验证context
valid_contexts = {"genomics", "proteomics", "pathway"}
if context not in valid_contexts:
context = "genomics"
# 验证max_results
if not isinstance(max_results, int) or max_results < 1:
max_results = 20
elif max_results > 50:
max_results = 50
return description, context, max_results