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refactor(worker): 合并渲染和TS封装任务为单一处理流程

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- 将 RENDER_SEGMENT_VIDEO 和 PACKAGE_SEGMENT_TS 任务类型合并为 RENDER_SEGMENT_TS
- 移除独立的 PackageSegmentTsHandler，将其功能集成到 RenderSegmentTsHandler 中
- 更新任务执行器中的 GPU 资源分配配置
- 修改单元测试以适配新的任务类型名称
- 在 TaskType 枚举中保留历史任务类型的兼容性标记
- 更新常量定义和默认功能配置中的任务类型引用
- 添加视频精确裁剪和 TS 封装功能到渲染处理器中
This commit is contained in:
Jerry Yan
2026-02-11 14:30:24 +08:00
parent c2ece02ecf
commit 9dd5b6237d
11 changed files with 230 additions and 365 deletions
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3
constant/__init__.py
View File

@@ -10,10 +10,9 @@ SOFTWARE_VERSION = '2.0.0'
# 支持的任务类型
TASK_TYPES = (
'RENDER_SEGMENT_VIDEO',
'RENDER_SEGMENT_TS',
'COMPOSE_TRANSITION',
'PREPARE_JOB_AUDIO',
'PACKAGE_SEGMENT_TS',
'FINALIZE_MP4',
)

3
domain/config.py
View File

@@ -17,9 +17,8 @@ logger = logging.getLogger(__name__)
# 默认支持的任务类型
DEFAULT_CAPABILITIES = [
"RENDER_SEGMENT_VIDEO",
"RENDER_SEGMENT_TS",
"PREPARE_JOB_AUDIO",
"PACKAGE_SEGMENT_TS",
"FINALIZE_MP4"
]

7
domain/task.py
View File

@@ -20,12 +20,15 @@ IMAGE_EXTENSIONS = {'.jpg', '.jpeg', '.png', '.webp', '.bmp', '.gif'}
class TaskType(Enum):
"""任务类型枚举"""
RENDER_SEGMENT_VIDEO = "RENDER_SEGMENT_VIDEO" # 渲染视频片段
RENDER_SEGMENT_TS = "RENDER_SEGMENT_TS" # 渲染+封装 TS（合并原 RENDER_SEGMENT_VIDEO + PACKAGE_SEGMENT_TS）
COMPOSE_TRANSITION = "COMPOSE_TRANSITION" # 合成转场效果
PREPARE_JOB_AUDIO = "PREPARE_JOB_AUDIO" # 生成全局音频
PACKAGE_SEGMENT_TS = "PACKAGE_SEGMENT_TS" # 封装 TS 分片
FINALIZE_MP4 = "FINALIZE_MP4" # 产出最终 MP4
# Deprecated: 历史任务类型，保留枚举值供兼容
RENDER_SEGMENT_VIDEO = "RENDER_SEGMENT_VIDEO"
PACKAGE_SEGMENT_TS = "PACKAGE_SEGMENT_TS"
# 支持的转场类型（对应 FFmpeg xfade 参数）
TRANSITION_TYPES = {

6
handlers/__init__.py
View File

@@ -6,17 +6,15 @@
"""
from handlers.base import BaseHandler
from handlers.render_video import RenderSegmentVideoHandler
from handlers.render_video import RenderSegmentTsHandler
from handlers.compose_transition import ComposeTransitionHandler
from handlers.prepare_audio import PrepareJobAudioHandler
from handlers.package_ts import PackageSegmentTsHandler
from handlers.finalize_mp4 import FinalizeMp4Handler
__all__ = [
'BaseHandler',
'RenderSegmentVideoHandler',
'RenderSegmentTsHandler',
'ComposeTransitionHandler',
'PrepareJobAudioHandler',
'PackageSegmentTsHandler',
'FinalizeMp4Handler',
]

318
handlers/package_ts.py
View File

@@ -1,318 +0,0 @@
# -*- coding: utf-8 -*-
"""
TS 分片封装处理器
处理 PACKAGE_SEGMENT_TS 任务，将视频片段和对应时间区间的音频封装为 TS 分片。
支持转场相关的 overlap 裁剪和转场分片封装。
"""
import os
import logging
from typing import List, Optional
from handlers.base import BaseHandler, VIDEO_ENCODE_ARGS
from domain.task import Task, TaskType
from domain.result import TaskResult, ErrorCode
logger = logging.getLogger(__name__)
class PackageSegmentTsHandler(BaseHandler):
"""
TS 分片封装处理器
职责：
- 下载视频片段
- 下载全局音频
- 截取对应时间区间的音频
- 封装为 TS 分片
- 上传 TS 产物
关键约束：
- TS 必须包含音视频同轨
- 使用 output_ts_offset 保证时间戳连续
- 输出 extinfDurationSec 供 m3u8 使用
转场相关：
- 普通片段 TS：需要裁剪掉 overlap 区域（已被转场分片使用）
- 转场分片 TS：直接封装转场视频产物，无需裁剪
- 无转场时：走原有逻辑，不做裁剪
精确裁剪：
- 当需要裁剪 overlap 区域时，必须使用重编码方式（-vf trim）才能精确切割
- 使用 -c copy 只能从关键帧切割，会导致不精确
"""
def get_supported_type(self) -> TaskType:
return TaskType.PACKAGE_SEGMENT_TS
def handle(self, task: Task) -> TaskResult:
"""处理 TS 封装任务"""
work_dir = self.create_work_dir(task.task_id)
try:
# 解析参数
video_url = task.get_video_url()
audio_url = task.get_audio_url()
start_time_ms = task.get_start_time_ms()
duration_ms = task.get_duration_ms()
output_spec = task.get_output_spec()
# 转场相关参数
is_transition_segment = task.is_transition_segment()
trim_head = task.should_trim_head()
trim_tail = task.should_trim_tail()
trim_head_ms = task.get_trim_head_ms()
trim_tail_ms = task.get_trim_tail_ms()
if not video_url:
return TaskResult.fail(
ErrorCode.E_SPEC_INVALID,
"Missing videoUrl"
)
if not audio_url:
return TaskResult.fail(
ErrorCode.E_SPEC_INVALID,
"Missing audioUrl"
)
# 计算时间参数
start_sec = start_time_ms / 1000.0
duration_sec = duration_ms / 1000.0
# 1. 并行下载视频片段与全局音频
video_file = os.path.join(work_dir, 'video.mp4')
audio_file = os.path.join(work_dir, 'audio.aac')
download_results = self.download_files_parallel([
{
'key': 'video',
'url': video_url,
'dest': video_file,
'required': True
},
{
'key': 'audio',
'url': audio_url,
'dest': audio_file,
'required': True
}
])
video_result = download_results.get('video')
if not video_result or not video_result['success']:
return TaskResult.fail(
ErrorCode.E_INPUT_UNAVAILABLE,
f"Failed to download video: {video_url}"
)
audio_result = download_results.get('audio')
if not audio_result or not audio_result['success']:
return TaskResult.fail(
ErrorCode.E_INPUT_UNAVAILABLE,
f"Failed to download audio: {audio_url}"
)
# 2. 判断是否需要精确裁剪视频
needs_video_trim = not is_transition_segment and (
(trim_head and trim_head_ms > 0) or
(trim_tail and trim_tail_ms > 0)
)
# 3. 如果需要裁剪，先重编码裁剪视频
processed_video_file = video_file
if needs_video_trim:
processed_video_file = os.path.join(work_dir, 'trimmed_video.mp4')
trim_cmd = self._build_trim_command(
video_file=video_file,
output_file=processed_video_file,
trim_head_ms=trim_head_ms if trim_head else 0,
trim_tail_ms=trim_tail_ms if trim_tail else 0,
output_spec=output_spec
)
logger.info(f"[task:{task.task_id}] Trimming video: head={trim_head_ms}ms, tail={trim_tail_ms}ms")
if not self.run_ffmpeg(trim_cmd, task.task_id):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Video trim failed"
)
if not self.ensure_file_exists(processed_video_file, min_size=1024):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Trimmed video file is missing or too small"
)
# 4. 构建 TS 封装命令
output_file = os.path.join(work_dir, 'segment.ts')
cmd = self._build_package_command(
video_file=processed_video_file,
audio_file=audio_file,
output_file=output_file,
start_sec=start_sec,
duration_sec=duration_sec
)
# 5. 执行 FFmpeg
if not self.run_ffmpeg(cmd, task.task_id):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"TS packaging failed"
)
# 6. 验证输出文件
if not self.ensure_file_exists(output_file, min_size=1024):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"TS output file is missing or too small"
)
# 8. 获取实际时长（用于 EXTINF）
actual_duration = self.probe_duration(output_file)
extinf_duration = actual_duration if actual_duration else duration_sec
# 9. 上传产物
ts_url = self.upload_file(task.task_id, 'ts', output_file)
if not ts_url:
return TaskResult.fail(
ErrorCode.E_UPLOAD_FAILED,
"Failed to upload TS"
)
return TaskResult.ok({
'tsUrl': ts_url,
'extinfDurationSec': extinf_duration
})
except Exception as e:
logger.error(f"[task:{task.task_id}] Unexpected error: {e}", exc_info=True)
return TaskResult.fail(ErrorCode.E_UNKNOWN, str(e))
finally:
self.cleanup_work_dir(work_dir)
def _build_trim_command(
self,
video_file: str,
output_file: str,
trim_head_ms: int,
trim_tail_ms: int,
output_spec
) -> List[str]:
"""
构建视频精确裁剪命令（重编码方式）
使用 trim 滤镜进行精确帧级裁剪，而非 -ss/-t 参数的关键帧裁剪。
Args:
video_file: 输入视频路径
output_file: 输出视频路径
trim_head_ms: 头部裁剪时长（毫秒）
trim_tail_ms: 尾部裁剪时长（毫秒）
output_spec: 输出规格
Returns:
FFmpeg 命令参数列表
"""
# 获取原视频时长
original_duration = self.probe_duration(video_file)
if not original_duration:
original_duration = 10.0 # 默认值，避免除零
trim_head_sec = trim_head_ms / 1000.0
trim_tail_sec = trim_tail_ms / 1000.0
# 计算裁剪后的起止时间
start_time = trim_head_sec
end_time = original_duration - trim_tail_sec
# 构建 trim 滤镜
vf_filter = f"trim=start={start_time}:end={end_time},setpts=PTS-STARTPTS"
cmd = [
'ffmpeg', '-y', '-hide_banner',
'-i', video_file,
'-vf', vf_filter,
]
# 编码参数
cmd.extend(VIDEO_ENCODE_ARGS)
# 帧率
fps = output_spec.fps
cmd.extend(['-r', str(fps)])
# 计算输出视频帧数，动态调整 GOP
output_duration_sec = end_time - start_time
total_frames = int(output_duration_sec * fps)
# 动态 GOP：短视频使用较小的 GOP
if total_frames <= 1:
gop_size = 1
elif total_frames < fps:
gop_size = total_frames
else:
gop_size = fps # 每秒一个关键帧
cmd.extend(['-g', str(gop_size)])
cmd.extend(['-keyint_min', str(min(gop_size, fps // 2 or 1))])
# 强制第一帧为关键帧
cmd.extend(['-force_key_frames', 'expr:eq(n,0)'])
# 无音频（音频单独处理）
cmd.append('-an')
cmd.append(output_file)
return cmd
def _build_package_command(
self,
video_file: str,
audio_file: str,
output_file: str,
start_sec: float,
duration_sec: float
) -> List[str]:
"""
构建 TS 封装命令
将视频和对应时间区间的音频封装为 TS 分片。
视频使用 copy 模式（已经过精确裁剪或无需裁剪）。
Args:
video_file: 视频文件路径（已处理）
audio_file: 音频文件路径
output_file: 输出文件路径
start_sec: 音频开始时间（秒）
duration_sec: 音频时长（秒）
Returns:
FFmpeg 命令参数列表
"""
cmd = [
'ffmpeg', '-y', '-hide_banner',
# 视频输入
'-i', video_file,
# 音频输入（从 start_sec 开始截取 duration_sec）
'-ss', str(start_sec),
'-t', str(duration_sec),
'-i', audio_file,
# 映射流
'-map', '0:v:0', # 使用第一个输入的视频流
'-map', '1:a:0', # 使用第二个输入的音频流
# 复制编码（视频已处理，无需重编码）
'-c:v', 'copy',
'-c:a', 'copy',
# 关键：时间戳偏移，保证整体连续
'-output_ts_offset', str(start_sec),
# 复用参数
'-muxdelay', '0',
'-muxpreload', '0',
# 输出格式
'-f', 'mpegts',
output_file
]
return cmd

237
handlers/render_video.py
View File

@@ -1,9 +1,9 @@
# -*- coding: utf-8 -*-
"""
视频片段渲染处理器
渲染+TS封装处理器
处理 RENDER_SEGMENT_VIDEO 任务，将原素材渲染为符合输出规格的视频片段。
支持转场 overlap 区域的帧冻结生成。
处理 RENDER_SEGMENT_TS 任务，将原素材渲染为视频并封装为 TS 分片。
支持转场 overlap 区域的帧冻结生成和精确裁剪。
"""
import os
@@ -11,7 +11,7 @@ import logging
from typing import List, Optional, Tuple
from urllib.parse import urlparse, unquote
from handlers.base import BaseHandler
from handlers.base import BaseHandler, VIDEO_ENCODE_ARGS
from domain.task import Task, TaskType, RenderSpec, OutputSpec, Effect, IMAGE_EXTENSIONS
from domain.result import TaskResult, ErrorCode
@@ -26,21 +26,24 @@ def _get_extension_from_url(url: str) -> str:
return ext.lower() if ext else ''
class RenderSegmentVideoHandler(BaseHandler):
class RenderSegmentTsHandler(BaseHandler):
"""
视频片段渲染处理器
渲染+TS封装处理器
职责：
- 下载素材文件
- 下载 LUT 文件（如有）
- 下载叠加层（如有）
- 下载音频（如有）
- 构建 FFmpeg 渲染命令
- 执行渲染（支持帧冻结生成 overlap 区域）
- 裁剪 overlap 区域（如需要）
- 封装为 TS 分片
- 上传产物
"""
def get_supported_type(self) -> TaskType:
return TaskType.RENDER_SEGMENT_VIDEO
return TaskType.RENDER_SEGMENT_TS
def handle(self, task: Task) -> TaskResult:
"""处理视频渲染任务"""
@@ -85,7 +88,10 @@ class RenderSegmentVideoHandler(BaseHandler):
else:
input_file = os.path.join(work_dir, 'input.mp4')
# 2. 构建并行下载任务（主素材 + 可选 LUT + 可选叠加层）
# 2. 构建并行下载任务（主素材 + 可选 LUT + 可选叠加层 + 可选音频）
audio_url = task.get_audio_url()
audio_file = None
lut_file = os.path.join(work_dir, 'lut.cube') if render_spec.lut_url else None
overlay_file = None
if render_spec.overlay_url:
@@ -121,6 +127,14 @@ class RenderSegmentVideoHandler(BaseHandler):
'dest': overlay_file,
'required': False
})
if audio_url:
audio_file = os.path.join(work_dir, 'audio.aac')
download_jobs.append({
'key': 'audio',
'url': audio_url,
'dest': audio_file,
'required': True
})
download_results = self.download_files_parallel(download_jobs)
material_result = download_results.get('material')
@@ -142,6 +156,14 @@ class RenderSegmentVideoHandler(BaseHandler):
logger.warning(f"[task:{task.task_id}] Failed to download overlay, continuing without it")
overlay_file = None
if audio_url:
audio_dl = download_results.get('audio')
if not audio_dl or not audio_dl['success']:
return TaskResult.fail(
ErrorCode.E_INPUT_UNAVAILABLE,
f"Failed to download audio: {audio_url}"
)
# 3. 图片素材转换为视频
if is_image:
video_input_file = os.path.join(work_dir, 'input_video.mp4')
@@ -219,27 +241,82 @@ class RenderSegmentVideoHandler(BaseHandler):
"Output file is missing or too small"
)
# 9. 获取实际时长
actual_duration = self.probe_duration(output_file)
actual_duration_ms = int(actual_duration * 1000) if actual_duration else duration_ms
# 9. Overlap 裁剪（仅非转场分片、且有需要裁剪的 overlap 时）
is_transition_seg = task.is_transition_segment()
trim_head = task.should_trim_head()
trim_tail = task.should_trim_tail()
trim_head_ms = task.get_trim_head_ms()
trim_tail_ms = task.get_trim_tail_ms()
needs_video_trim = not is_transition_seg and (
(trim_head and trim_head_ms > 0) or
(trim_tail and trim_tail_ms > 0)
)
# 10. 上传产物
video_url = self.upload_file(task.task_id, 'video', output_file)
if not video_url:
return TaskResult.fail(
ErrorCode.E_UPLOAD_FAILED,
"Failed to upload video"
processed_video = output_file
if needs_video_trim:
processed_video = os.path.join(work_dir, 'trimmed_video.mp4')
trim_cmd = self._build_trim_command(
video_file=output_file,
output_file=processed_video,
trim_head_ms=trim_head_ms if trim_head else 0,
trim_tail_ms=trim_tail_ms if trim_tail else 0,
output_spec=output_spec
)
# 11. 构建结果（包含 overlap 信息）
result_data = {
'videoUrl': video_url,
'actualDurationMs': actual_duration_ms,
'overlapHeadMs': overlap_head_ms,
'overlapTailMs': overlap_tail_ms
}
logger.info(f"[task:{task.task_id}] Trimming video: head={trim_head_ms}ms, tail={trim_tail_ms}ms")
return TaskResult.ok(result_data)
if not self.run_ffmpeg(trim_cmd, task.task_id):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Video trim failed"
)
if not self.ensure_file_exists(processed_video, min_size=1024):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Trimmed video file is missing or too small"
)
# 10. 封装 TS
start_time_ms = task.get_start_time_ms()
start_sec = start_time_ms / 1000.0
duration_sec = duration_ms / 1000.0
ts_output = os.path.join(work_dir, 'segment.ts')
ts_cmd = self._build_ts_package_command(
video_file=processed_video,
audio_file=audio_file,
output_file=ts_output,
start_sec=start_sec,
duration_sec=duration_sec
)
if not self.run_ffmpeg(ts_cmd, task.task_id):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"TS packaging failed"
)
if not self.ensure_file_exists(ts_output, min_size=1024):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"TS output file is missing or too small"
)
# 11. 获取 EXTINF 时长 + 上传 TS
actual_duration = self.probe_duration(ts_output)
extinf_duration = actual_duration if actual_duration else duration_sec
ts_url = self.upload_file(task.task_id, 'ts', ts_output)
if not ts_url:
return TaskResult.fail(
ErrorCode.E_UPLOAD_FAILED,
"Failed to upload TS"
)
return TaskResult.ok({
'tsUrl': ts_url,
'extinfDurationSec': extinf_duration
})
except Exception as e:
logger.error(f"[task:{task.task_id}] Unexpected error: {e}", exc_info=True)
@@ -350,6 +427,116 @@ class RenderSegmentVideoHandler(BaseHandler):
logger.info(f"[task:{task_id}] Converting image to video: {actual_duration_sec:.2f}s at {fps}fps")
return self.run_ffmpeg(cmd, task_id)
def _build_trim_command(
self,
video_file: str,
output_file: str,
trim_head_ms: int,
trim_tail_ms: int,
output_spec
) -> List[str]:
"""
构建视频精确裁剪命令（重编码方式）
使用 trim 滤镜进行精确帧级裁剪，而非 -ss/-t 参数的关键帧裁剪。
Args:
video_file: 输入视频路径
output_file: 输出视频路径
trim_head_ms: 头部裁剪时长（毫秒）
trim_tail_ms: 尾部裁剪时长（毫秒）
output_spec: 输出规格
Returns:
FFmpeg 命令参数列表
"""
original_duration = self.probe_duration(video_file)
if not original_duration:
original_duration = 10.0
trim_head_sec = trim_head_ms / 1000.0
trim_tail_sec = trim_tail_ms / 1000.0
start_time = trim_head_sec
end_time = original_duration - trim_tail_sec
vf_filter = f"trim=start={start_time}:end={end_time},setpts=PTS-STARTPTS"
cmd = [
'ffmpeg', '-y', '-hide_banner',
'-i', video_file,
'-vf', vf_filter,
]
cmd.extend(VIDEO_ENCODE_ARGS)
fps = output_spec.fps
cmd.extend(['-r', str(fps)])
output_duration_sec = end_time - start_time
total_frames = int(output_duration_sec * fps)
if total_frames <= 1:
gop_size = 1
elif total_frames < fps:
gop_size = total_frames
else:
gop_size = fps
cmd.extend(['-g', str(gop_size)])
cmd.extend(['-keyint_min', str(min(gop_size, fps // 2 or 1))])
cmd.extend(['-force_key_frames', 'expr:eq(n,0)'])
cmd.append('-an')
cmd.append(output_file)
return cmd
def _build_ts_package_command(
self,
video_file: str,
audio_file: Optional[str],
output_file: str,
start_sec: float,
duration_sec: float
) -> List[str]:
"""
构建 TS 封装命令
将视频和对应时间区间的音频封装为 TS 分片。
视频使用 copy 模式（已经过渲染/裁剪）。
支持无音频模式（video-only TS）。
Args:
video_file: 视频文件路径（已处理）
audio_file: 音频文件路径（可选，None 时生成 video-only TS）
output_file: 输出文件路径
start_sec: 音频开始时间（秒）
duration_sec: 音频时长（秒）
Returns:
FFmpeg 命令参数列表
"""
cmd = [
'ffmpeg', '-y', '-hide_banner',
'-i', video_file,
]
if audio_file:
cmd.extend(['-ss', str(start_sec), '-t', str(duration_sec), '-i', audio_file])
cmd.extend(['-map', '0:v:0', '-map', '1:a:0', '-c:v', 'copy', '-c:a', 'copy'])
else:
cmd.extend(['-c:v', 'copy'])
cmd.extend([
'-output_ts_offset', str(start_sec),
'-muxdelay', '0',
'-muxpreload', '0',
'-f', 'mpegts',
output_file
])
return cmd
def _build_command(
self,
input_file: str,

3
index.py
View File

@@ -4,9 +4,8 @@
RenderWorker v2 入口
支持 v2 API 协议的渲染 Worker，处理以下任务类型：
- RENDER_SEGMENT_VIDEO: 渲染视频片段
- RENDER_SEGMENT_TS: 渲染视频片段并封装为 TS
- PREPARE_JOB_AUDIO: 生成全局音频
- PACKAGE_SEGMENT_TS: 封装 TS 分片
- FINALIZE_MP4: 产出最终 MP4
使用方法:

8
services/task_executor.py
View File

@@ -14,7 +14,7 @@ from domain.task import Task, TaskType
# 需要 GPU 加速的任务类型
GPU_REQUIRED_TASK_TYPES = {
TaskType.RENDER_SEGMENT_VIDEO,
TaskType.RENDER_SEGMENT_TS,
TaskType.COMPOSE_TRANSITION,
}
from domain.config import WorkerConfig
@@ -85,17 +85,15 @@ class TaskExecutor:
def _register_handlers(self):
"""注册所有任务处理器"""
# 延迟导入以避免循环依赖
from handlers.render_video import RenderSegmentVideoHandler
from handlers.render_video import RenderSegmentTsHandler
from handlers.compose_transition import ComposeTransitionHandler
from handlers.prepare_audio import PrepareJobAudioHandler
from handlers.package_ts import PackageSegmentTsHandler
from handlers.finalize_mp4 import FinalizeMp4Handler
handlers = [
RenderSegmentVideoHandler(self.config, self.api_client),
RenderSegmentTsHandler(self.config, self.api_client),
ComposeTransitionHandler(self.config, self.api_client),
PrepareJobAudioHandler(self.config, self.api_client),
PackageSegmentTsHandler(self.config, self.api_client),
FinalizeMp4Handler(self.config, self.api_client),
]

2
tests/unit/test_base_handler_parallel_transfer.py
View File

@@ -21,7 +21,7 @@ class _DummyHandler(BaseHandler):
return TaskResult.ok({})
def get_supported_type(self):
return TaskType.RENDER_SEGMENT_VIDEO
return TaskType.RENDER_SEGMENT_TS
def _create_handler(tmp_path):

4
tests/unit/test_render_video_effects.py
View File

@@ -4,7 +4,7 @@ import pytest
from domain.config import WorkerConfig
from domain.task import Effect, OutputSpec, RenderSpec
from handlers.render_video import RenderSegmentVideoHandler
from handlers.render_video import RenderSegmentTsHandler
class _DummyApiClient:
@@ -20,7 +20,7 @@ def _create_handler(tmp_path):
cache_enabled=False,
cache_dir=str(tmp_path / 'cache')
)
return RenderSegmentVideoHandler(config, _DummyApiClient())
return RenderSegmentTsHandler(config, _DummyApiClient())
def test_get_zoom_params_with_valid_values():

4
tests/unit/test_tracing.py
View File

@@ -7,7 +7,7 @@ import util.tracing as tracing_module
def _create_task_stub():
task_type = SimpleNamespace(value="RENDER_SEGMENT_VIDEO")
task_type = SimpleNamespace(value="RENDER_SEGMENT_TS")
return SimpleNamespace(
task_id="task-1001",
task_type=task_type,
@@ -28,7 +28,7 @@ def test_task_trace_scope_sets_and_resets_context(monkeypatch):
context = tracing.get_current_task_context()
assert context is not None
assert context.task_id == "task-1001"
assert context.task_type == "RENDER_SEGMENT_VIDEO"
assert context.task_type == "RENDER_SEGMENT_TS"
assert context.job_id == "job-2002"
assert context.segment_id == "seg-3003"