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生信云平台 Python SDK,提供图表上传和文件存储功能

Project description

Lims2 SDK

Version Python

生信云平台 Python SDK,提供图表上传和文件存储功能。

当前版本: v0.6.1

功能特性

  • 图表服务:支持 Plotly、Cytoscape、图片、PDF 格式上传
  • 缩略图生成:自动为 Plotly 图表生成静态缩略图(800×600 WebP格式)
  • 文件存储:通过 STS 凭证上传文件到阿里云 OSS,支持断点续传
  • 命令行工具:提供便捷的 CLI 命令
  • 精度控制:使用 decimal 库精确四舍五入,默认保留3位小数,减少 JSON 文件大小(可减少 15-60%)
  • 连接优化:自动重试机制处理网络不稳定问题,适合批量上传场景

安装配置

从 PyPI 安装

pip install -U lims2-sdk

设置环境变量:

export LIMS2_API_URL="your-api"
export LIMS2_API_TOKEN="your-api-token"

命令行使用

📖 获取帮助信息

# 查看所有可用命令
lims2 --help

# 查看图表上传帮助
lims2 chart --help
lims2 chart upload --help

# 查看存储服务帮助
lims2 storage --help
lims2 storage upload --help
lims2 storage upload-dir --help

# 查看文件操作帮助
lims2 storage exists --help
lims2 storage info --help

图表上传

# 上传图表文件(完整参数示例)
lims2 chart upload plot.json -p proj_001 -n "基因表达分析" -s sample_001 -t heatmap -d "差异表达热图" -c A_vs_B -a Expression_statistics --precision 3

文件存储

# 上传单个文件(简化)
lims2 storage upload results.csv -p proj_001

# 上传到指定路径
lims2 storage upload results.csv -p proj_001 --base-path analysis

# 上传目录(简化)
lims2 storage upload-dir output/ -p proj_001

# 上传目录到指定路径
lims2 storage upload-dir output/ -p proj_001 --base-path analysis

Python SDK 使用

** 多个图表上传,推荐使用该方法,可复用链接池 **

推荐使用方式(v0.4.1+)

from lims2 import Lims2Client

# 初始化客户端(推荐复用,避免重复创建连接)
client = Lims2Client()

# 批量上传时复用同一个客户端实例
charts = ["plot1.json", "plot2.json", "plot3.json"]
for chart_file in charts:
    client.chart.upload(
        data_source=chart_file,
        project_id="proj_001",
        chart_name=f"图表_{chart_file}",
        analysis_node="Expression_statistics",
        precision=3
    )

完整参数示例

# 上传图表(完整参数示例)
client.chart.upload(
    data_source="plot.json",        # 图表数据源:字典、文件路径或 Path 对象
    project_id="proj_001",          # 项目 ID(必需)
    chart_name="基因表达分析",        # 图表名称(必需)
    sample_id="sample_001",         # 样本 ID(可选)
    chart_type="heatmap",           # 图表类型(可选)
    description="差异表达基因热图",   # 图表描述(可选)
    contrast="A_vs_B",              # 对比策略(可选)
    analysis_node="Expression_statistics",  # 分析节点名称(可选)
    precision=3,                    # 浮点数精度:0-10位小数(默认3)
    generate_thumbnail=True         # 是否生成缩略图(默认True)
)

# 上传文件(最简)
client.storage.upload_file("results.csv", "proj_001")

# 上传文件到指定路径
client.storage.upload_file("results.csv", "proj_001", base_path="analysis")

# 上传目录(最简)
client.storage.upload_directory("output/", "proj_001")

# 上传目录到指定路径
client.storage.upload_directory("output/", "proj_001", base_path="analysis")

便捷函数(已弃用)

⚠️ 弃用警告: 以下函数在 v0.4.1 中已弃用,将在 v0.5.0 中移除。推荐使用上述 Lims2Client 实例方法复用连接池,避免批量上传时的连接问题。

# 不推荐:每次调用都创建新连接
from lims2 import upload_chart_from_file
upload_chart_from_file("图表名", "proj_001", "chart.json")

缩略图功能

自动生成缩略图

v0.6.0 版本新增了 Plotly 图表的缩略图自动生成功能:

# 默认启用缩略图生成
client.chart.upload(
    data_source="plot.json",
    project_id="proj_001",
    chart_name="基因表达分析"
    # generate_thumbnail=True  # 默认为 True
)

# 禁用缩略图生成
client.chart.upload(
    data_source="plot.json",
    project_id="proj_001",
    chart_name="基因表达分析",
    generate_thumbnail=False
)

缩略图配置

可通过环境变量配置缩略图参数:

# 是否自动生成缩略图(默认 true)
export LIMS2_AUTO_GENERATE_THUMBNAIL=true

# 缩略图尺寸(默认 800x600)
export LIMS2_THUMBNAIL_WIDTH=800
export LIMS2_THUMBNAIL_HEIGHT=600

# 缩略图格式(默认 webp,支持 png、jpeg)
export LIMS2_THUMBNAIL_FORMAT=webp

特性说明

  • 自动容错:使用 skip_invalid=True 跳过无效属性,确保兼容性
  • 格式优化:默认使用 WebP 格式,体积小质量高
  • 异步处理:缩略图生成失败不影响主文件上传
  • URL 返回:生成成功后返回缩略图 URL

支持的数据格式

图表格式

  • Plotly: 包含 datalayout 字段的字典(支持缩略图)
  • Cytoscape: 包含 elementsnodes+edges 字段的字典
  • 图片: PNG, JPG, JPEG, SVG
  • 其他: PDF

文件格式

  • 支持任意格式的文件上传
  • 自动处理大文件(>10MB)的断点续传
  • 提供进度回调支持

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