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* feat: add ssh proxy * feat: add ssh proxy * feat: add ssh proxy * feat: add ssh proxy * feat: add prompt * feat: add agent wrapper * feat: add agent wrapper * feat: add agent wrapper * feat: add tushare skill * feat: add tushare skill * feat: add tushare skill * feat: add none stream * chore(deps): update dependency versions in pyproject.toml - Bump claude-agent-sdk from 0.2.123 to 0.2.126 - Upgrade pre-commit to version 4.6.1 or higher - Upgrade pytest to version 9.1.1 or higher * feat(agent_wrapper): add session compaction support and unify session commands - Introduce compact_session method to BaseAgentWrapper and implement it in AsAgentWrapper, CcAgentWrapper, and CodexAgentWrapper - Add session_command module with SessionCommandResult dataclass and handle_session_command function for /clear and /compact commands - Update __init__.py exports to include session_command handlers - Modify DingTalkWaitStep to handle session commands via handle_session_command function - Remove streaming mode from DingTalkWaitStep and simplify reply handling to final Markdown replies only - Add unit tests for session compaction methods and session command handling across wrappers and DingTalk integration - Clean up and remove obsolete streaming and card rendering code from DingTalk wait step - Adjust daily_cookbook.yaml to remove stream and card_update_interval config entries for DingTalk wait step * feat(auto_fin): add Auto Fin simulated portfolio cookbook workflow - Add comprehensive Auto Fin schema exports for multiple models and enums - Implement base class and helpers for Auto Fin analysis steps - Create file, state, and formatting utilities for Auto Fin with atomic file writes and locking - Define Auto Fin pipeline with four analysis agents: backtest, event, portfolio, and US correlation - Register Auto Fin package in cookbook workflows and schema initialization - Add detailed documentation in markdown describing the system design, workflow, and data contracts * feat(outbound_proxy): add application-scoped outbound HTTP proxy components - Introduce BaseOutboundProxy and OutboundProxyEndpoint as core contracts - Implement FixedHttpOutboundProxy for external HTTP proxy integration - Add SshHttpOutboundProxy providing SSH-backed local HTTP proxy tunnels - Register outbound proxy components in component registry and enumeration - Update components package to include outbound_proxy module - Add dependency on pproxy for SSH HTTP proxy bridging - Include comprehensive unit tests covering proxy lifecycle, validation, environment merging, error handling, readiness, and monitoring mechanisms * refactor(network): replace SSH proxy with explicit HTTP outbound proxy - Remove SSH proxy helper implementation and references in codebase - Add support for explicit HTTP proxy URL in arXiv and HuggingFace clients - Modify clients to use async context manager for consistent resource handling - Update daily paper steps to forward outbound proxy configuration explicitly - Change tests to cover new proxy usage model and remove SSH proxy mocks - Add outbound proxy component configuration in daily_cookbook.yaml - Ensure proxy URL usage disables environment trust in HTTP clients - Fix app context component enum access to be defensive against missing keys * feat(agent_wrapper): add managed proxy support for command environments - Introduce BaseOutboundProxy binding in BaseAgentWrapper for outbound proxy management - Add bash_environment and command_proxy_environment properties to apply proxy settings - Update WorkspaceBackend instantiation in AsAgentWrapper to use bash_environment - Inject managed proxy export commands into Claude Code Bash commands via hooks - Enhance CodexAgentWrapper to include managed proxy in shell environment policy - Modify daily_cookbook.yaml steps to specify outbound_proxy as default where needed - Add comprehensive unit tests verifying managed proxy injection and environment isolation - Ensure subprocess_environment remains unchanged while proxy is applied selectively to commands * refactor(memory): replace search job_tools with memory in daily cookbook config - Change workspace_dir default from .reme to reme_workspace - Replace search job_tools with memory across multiple components and jobs - Update descriptions to reflect long-term memory retrieval instead of search - Modify system prompts to instruct using memory for retrieving notes - Adjust unit tests to verify memory job_tools and job presence instead of search - Ensure consistency in configuration and tests for memory backend usage * refactor(config): rename memory to memory_search in daily cookbook config - Change all occurrences of "memory" to "memory_search" in job_tools and job definitions - Update related system prompts to reflect the new memory_search terminology - Modify unit tests to assert the presence of memory_search instead of memory - Ensure consistency across skills, job tools, and backend configurations in multiple components * feat(auto_fin): add deterministic quantitative research and ranking fusion - Introduce new schema models: EtfScore, RankingMetrics, ExtremeAnalysis, DimensionRanking, and FusionRanking to represent deterministic research outputs - Add ranking data to event, backtest, us_correlation, and portfolio analysis outputs - Implement ranking_section renderer to format Top20 scores and diagnostics in Markdown - Develop AutoFinQuantStep for deterministic ETF ranking using TuShare data, Polars, and a custom extremely randomized tree ensemble - Integrate quantitative rankings into backtest and portfolio analysis steps and reports - Extend auto_fin pipeline with new quant_enabled and quant_required config options - Enforce ranking constraints like unique codes, contiguous ranks, and normalized fusion weights - Update analysis YAMLs with rules limiting data freshness, universe, and ranking usage - Incorporate ranking outputs into all major markdown report bodies in Auto Fin pipeline - Add concurrency-limited asynchronous TuShare client to fetch required market data - Introduce cross-sectional rank correlation and NDCG metrics for ranking quality evaluation * feat(auto_fin): implement stage-wise notification and reporting for analysis pipeline - Refactor notification config in daily_cookbook.yaml to support dispatch steps - Update AutoFinNotificationStep to deduplicate notifications per run stage - Add _notify_stage method in pipeline to send notifications for each analysis stage - Implement persistence and notification for event, backtest, US correlation, and portfolio stages - Modify pipeline flow to persist reports and notify after each stage completion - Adjust metadata to track notifications and errors per stage - Update tests to verify stage-wise notification sending and deduplication - Remove older combined report persistence in favor of modular stage handling * feat(auto_fin): add outbound proxy support for Tushare API usage - Introduce BaseOutboundProxy reference in AutoFinPipelineStep and AutoFinQuantStep - Update TushareResearchClient and trade calendar fetch to accept and use proxy URL - Create _ProxiedTushareApi adapter to route Tushare requests via explicit HTTP proxy - Modify create_tushare_api utility to optionally return proxied API client - Add unit tests covering proxy forwarding and client behavior with managed proxies - Ensure proxy usage respects explicit proxy URL over environment fallback - Integrate outbound proxy into data fetching and quantitative research steps * feat(auto_fin): enforce checkpoint time validation and add state models - Introduce AnalysisState base class and specific states for event, backtest, and US correlation analyses - Replace analysis output types with corresponding state classes in run schemas - Add require_checkpoint_reached method to validate decision_at/data_cutoff against current time - Enforce checkpoint time checks before analysis steps in event, backtest, portfolio, and quant analyses - Refactor quant data loading to include adjustment factors and apply price adjustments without fallback - Update analysis YAML docs to require real-time checkpoint validation and forbid using future data - Improve portfolio run serialization by excluding redundant legacy fields and nested proposed actions - Add helper to extract readable sections from persisted checkpoint documents - Fix event analysis output validation to reject events and sources with future timestamps * feat(auto_fin): auto-select latest reached checkpoint if none specified - Extend checkpoint config to accept empty string for auto selection - Add static method to compute latest checkpoint reached by current time - Modify pipeline step to auto-select checkpoint based on trade calendar and time - Adjust force flag default depending on whether checkpoint is explicit or auto - Log details when checkpoint is auto-selected to improve observability - Add comprehensive tests for auto checkpoint selection logic and edge cases - Remove deprecated default and required constraints from force parameter in config * refactor(auto_fin): unify datetime comparison with compare_datetimes utility - Replace direct datetime comparisons with compare_datetimes function calls - Use cmp_to_key with compare_datetimes for sorting datetime tuples and lists - Update validation logic in backtest, event, analysis, and ledger modules for consistent datetime handling - Add unit tests to verify handling of naive and aware datetime comparisons in event and backtest validations - Ensure marked_at and interval_end timestamps are set and compared consistently using compare_datetimes - Improve correctness of ordering and conditional checks related to timestamps throughout auto_fin steps and ledger code * feat(auto_fin): add datetime comparison helper for mixed timezone data - Implement compare_datetimes function to handle naive and aware datetimes - Ensure naive datetime is interpreted in the known timezone of the counterpart - Facilitate comparisons between legacy and timezone-aware Auto Fin data - Add module docstring explaining purpose of the helpers * docs(auto_fin): enforce unique ETF representative per sub-theme in analysis rules - Update backtest.yaml to recommend or highlight only one ETF per sub-theme for ETF analyses - Modify event.yaml to map only one representative ETF per sub-theme, avoiding duplicate recommendations - Revise portfolio.yaml to restrict holdings/buys to a single ETF per sub-theme, preventing repeated buys of highly overlapping ETFs - Adjust us_correlation.yaml to retain only one representative A-share ETF per sub-theme for mapping or recommendation - Add test to verify presence of new sub-theme uniqueness guidance in step prompts * feat(auto_fin): separate draft model and include deterministic fusion ranking - Introduce _PortfolioProposalDraft pydantic model for agent-authored fields before ranking - Discard any "fusion_ranking" data from draft to prevent conflicts with canonical ranking - Modify AutoFinPortfolioStep to receive draft, enrich with fusion_ranking, and produce final output - Update tests to use _PortfolioProposalDraft and validate deterministic fusion ranking propagation - Add async test verifying fusion ranking is correctly set in portfolio output with no errors * refactor(auto_fin): rewrite and simplify Auto Fin schema and steps - Remove legacy Auto Fin analysis step modules and helpers - Replace complex ranking and portfolio models with simplified current-news models - Update schema to focus on news-case workflow with new domain models - Remove A-share decision checkpoints and backtest details from schema - Simplify recommendation and decision output structures - Clean up deprecated state and utility functions - Update Auto Fin steps initialization to new pipeline steps only - Improve uniqueness validation for themes and ETFs in research plan * feat(auto_fin): implement full local cache and analysis workflow for Auto Fin - Add AutoFinDataStep to prepare and cache daily TuShare data with lookback - Add AutoFinAnalysisStep to analyze cached data and generate Markdown report - Implement detailed time window, ETF filtering, and historical case validation - Introduce YAML prompts for planning and decision-making steps - Update .gitignore to include reme_workspace/ - Clean up config and import structure for auto_fin steps - Remove old pipeline.py and consolidate functionality into new modules - Use polars for efficient CSV reading and data processing - Ensure atomic writes and strict JSON serialization for cache files - Enforce rules on news timing, ETF universe, and historical case usage * fix(auto_fin): restrict news data source to '财联社' in analysis and cache - Update analysis templates to specify current news as from '财联社' only - Modify news fetching functions to filter by source '财联社' - Add validation method to check cached news source correctness - Update news caching logic to exclude non-'财联社' news - Enhance unit tests with multiple sources to ensure filtering works - Confirm news API calls include source filter parameter as '财联社' * refactor(auto_fin): convert I/O methods to asynchronous implementations - Change _news, _dataset, and _theme_data methods to async for improved concurrency - Move JSONL and CSV reading operations to asynchronous wrappers using asyncio.to_thread - Remove synchronous _read_jsonl and _read_csv functions, integrate them as static async class methods - Update cache validation methods to async, awaiting I/O operations accordingly - Adjust usage of dataset and news retrieval in analysis step to await asynchronous methods - Add async unit test to validate JSONL reading with unicode line separators - Preserve existing functionality while enabling non-blocking file and data access * fix(nx_file_graph): defer networkx import and improve dependency handling - Move networkx import inside NxFileGraph constructor for lazy loading - Raise ImportError with original exception context if networkx is missing - Remove module-level fallback assignment of nx to None - Expand test to block loading of multiple optional core dependencies eagerly - Change exception type in test from ModuleNotFoundError to AssertionError - Update test comments to reflect broader optional dependency checks * feat(embedding_store): add quota retry delay mechanism for embedding requests - Introduce quota_retry_delay parameter to configure wait time before retry on quota exhaustion - Implement detection of insufficient quota errors in LocalEmbeddingStore without external SDK - Add retry logic with custom delay when quota is insufficient during embedding requests - Update configuration to set max_retries and quota_retry_delay defaults for embedding store - Add unit tests covering quota exhaustion retry behavior with delay and opt-in control - Ensure existing retry behavior remains unchanged if quota_retry_delay is not set * feat(auto_fin): add detailed logging to analysis and data fetching steps - Add _preview static method for bounded diagnostic output in analysis.py - Log prompt start, completion, errors, and validation details in _reply method - Add info logs for major processing steps in execute method of analysis.py - Add debug and info logs for cache validation, data fetching, and pagination in data.py - Log conditions for skipping reports and cache plans in data.py execute method - Log download summaries and cache writes for news and ETF data - Improve error logging with exception details in cache validation functions - Ensure all logs include context such as record counts, paths, and parameters * refactor(auto_fin): overhaul Auto Fin workflow and schema contracts - Replace old Auto Fin schema models with comprehensive new data classes - Remove legacy Auto Fin analysis step in favor of modular agent-based steps - Introduce AutoFinAgentStep for validating structured agent replies - Simplify data cleaning and JSONL writing utilities for news cache - Remove synchronous and asynchronous dataset methods from analysis step - Redefine Auto Fin analysis configuration for 360-day news retention and multi-step pipeline - Remove embedded analysis prompt templates and replace with agent-driven logic - Update __init__.py exports to match new step implementations and remove deprecated classes - Improve error handling and validation in agent step reply processing - Clean up redundant imports and unused code in analysis and data preparation modules * feat(auto_fin): add detailed logging for analysis and data processing steps - Add timing logs to measure agent prompt processing duration in analysis.py - Log news cache hits and news write paths with record counts in data.py - Include detailed info logs for news download start and completion in data.py - Add start, progress, and completion logs with topic and event counts in history.py - Log start and completion of merge step including path and ETF count in merge.py - Add start and done logs with window and news counts in topic.py * feat(auto_fin): enhance schema and steps with detailed ETF and event modeling - Replace and add multiple AutoFin schema classes to support detailed ETF selection, historical research, market analysis, forecast models, and report output with validation - Implement Shanghai timezone normalization and strict validation in schema models - Remove deprecated AutoFin analysis agent step and consolidate reply handling in base step - Introduce AutoFinStep base class with shared helpers for prompt handling, data fetching, logging, and JSONL file operations - Add AutoFinDataStep to manage daily news data complete with schedule validation, caching, and source validation logic - Update cookbook configuration to customize auto_fin step parameters and simplify outbound proxy settings - Refactor imports and clean unused code for better maintainability * feat(auto_fin): introduce detailed historical event resolution and market similarity analysis - Add AutoFinHistoricalEventReference and AutoFinHistoricalSimilarity models for refined event referencing and similarity judgment - Implement validation to ensure non-empty critical fields and uniqueness of historical news IDs - Develop method to resolve Agent-selected historical event references from workspace files with strict path and existence checks - Enrich historical events with market entry and future returns data after resolution - Redesign market step to calculate similarity-weighted ETF forecasts based on matched historical event similarities - Enforce validation on matched historical events for uniqueness and proper weight summation - Simplify merge step output to final Markdown report without YAML frontmatter and redundant fields - Update user instructions for history search, market, and merge steps to reflect new data structures and responsibilities - Adjust test suite to cover new schema and step behavior changes, including enhanced validation and JSON output formats * feat(auto_fin): add new cron jobs and output analysis jsonl - Add new cron jobs auto_fin_1145_cron and auto_fin_1800_cron with auto_fin_steps - Change auto_fin_0930_cron schedule to run Monday to Sunday - Extend merge step to write analysis data to auto_fin_analysis.jsonl - Update unit tests to verify new cron jobs and their steps configuration * fix(auto_fin): improve atomic file write and refresh daily index - Change temporary file naming to include UUID for uniqueness and hidden prefix - Replace atomic write method from using Path.replace to os.replace with safe unlink - Add import and use os.replace for safer file replace operation - Refresh daily index after writing auto finance markdown and JSONL files - Import and call refresh_day_index in merge step to update file index asynchronously * docs(cookbook): add optional SSH proxy configuration in README files - Introduce optional SSH proxy setup in auto-fin and daily_paper cookbooks - Provide instructions to enable outbound proxy via `daily_cookbook.yaml` and environment variables - Add `REME_PROXY_IP` and `REME_PROXY_ACCOUNT` environment variables descriptions in multiple README files - Update English and Chinese README and README_ZH documents with proxy details - Maintain consistent formatting of environment variable tables across documents * fix(file_io): include schema_version in hidden metadata keys - Added "schema_version" to _INDEX_HIDDEN_METADATA_KEYS in _daily_index.py - Updated _render_notes_block to always include additional keys regardless of schema_version fix(deps): move pproxy dependency to later in pyproject.toml - Removed pproxy from early dependencies list - Added pproxy back near the end of dependency list for better ordering fix(outbound_proxy): require pproxy package for ssh_http proxy - Added importlib.util check for pproxy package presence - Raise RuntimeError if pproxy is not installed when using SSH HTTP outbound proxy - Improved error message suggests installing reme-ai with 'core' extra * docs(readme): update News section with new Cookbook workflows - Clarify introduction of optional Cookbooks with Daily Paper and Auto Fin workflows - Update English README to reflect both paper discovery and file-native ETF event research - Revise Chinese README to include financial news and historical market data research capability - Maintain announcement of paper acceptance at Findings of ACL 2026 * feat(auto_fin): add calculation results to final Markdown output - Implement _calculation_results to summarize forecast for each ETF analyzed - Include program-calculated results in the JSON input for the Markdown report - Update YAML template to incorporate calculation results and adjust recommendation rules - Refine recommendation logic to rely on event impact judgments combined with calculation outputs - Modify tests to verify presence of calculation results and updated report content and format * up prompt * fix(keyword_index): ignore non-indexable chunks during keyword sync - Add is_indexable method to base and BM25 keyword index classes to check text tokenizability - Update local file store to exclude non-indexable chunks from expected document IDs to prevent rebuild - Fix JSONL chunker to correctly handle Unicode line separator U+2028 inside JSON strings without splitting - Add test to ensure non-empty but non-indexable chunk does not trigger keyword index rebuild - Add test to verify U+2028 character does not cause incorrect JSONL record splitting
341 lines
12 KiB
Python
341 lines
12 KiB
Python
"""Tests for application-scoped outbound proxy components."""
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# pylint: disable=missing-function-docstring,protected-access
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import asyncio
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import os
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import sys
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from collections.abc import Callable
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import pytest
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from reme.application import Application
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from reme.components import R
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from reme.components.outbound_proxy import FixedHttpOutboundProxy, SshHttpOutboundProxy
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from reme.enumeration import ComponentEnum
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class FakeProcess:
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"""Minimal asyncio subprocess stand-in with observable shutdown."""
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def __init__(self, label: str, events: list[str]) -> None:
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self.label = label
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self.events = events
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self.returncode: int | None = None
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self.stdout = asyncio.StreamReader()
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self.stderr = asyncio.StreamReader()
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self._finished = asyncio.Event()
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async def wait(self) -> int:
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await self._finished.wait()
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assert self.returncode is not None
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return self.returncode
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def terminate(self) -> None:
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self.events.append(f"terminate:{self.label}")
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self.exit(-15)
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def kill(self) -> None:
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self.events.append(f"kill:{self.label}")
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self.exit(-9)
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def exit(self, returncode: int, output: str = "") -> None:
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if self.returncode is not None:
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return
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self.returncode = returncode
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encoded = output.encode()
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self.stdout.feed_data(encoded)
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self.stdout.feed_eof()
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self.stderr.feed_data(encoded)
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self.stderr.feed_eof()
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self._finished.set()
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async def _ready_listener(*_args) -> None:
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return None
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async def _wait_until(predicate: Callable[[], bool], timeout: float = 1.0) -> None:
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loop = asyncio.get_running_loop()
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deadline = loop.time() + timeout
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while not predicate():
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if loop.time() >= deadline:
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raise AssertionError("condition did not become true")
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await asyncio.sleep(0.005)
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def test_outbound_proxy_backends_are_registered() -> None:
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assert R.get(ComponentEnum.OUTBOUND_PROXY, "fixed_http") is FixedHttpOutboundProxy
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assert R.get(ComponentEnum.OUTBOUND_PROXY, "ssh_http") is SshHttpOutboundProxy
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@pytest.mark.asyncio
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async def test_application_builds_and_manages_fixed_http_proxy(tmp_path) -> None:
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app = Application(
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workspace_dir=str(tmp_path),
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enable_logo=False,
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log_to_console=False,
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log_to_file=False,
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service={"backend": "cli"},
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components={
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"outbound_proxy": {
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"default": {
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"backend": "fixed_http",
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"url": "http://127.0.0.1:18080",
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},
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},
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},
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)
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component = app.context.components[ComponentEnum.OUTBOUND_PROXY]["default"]
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assert isinstance(component, FixedHttpOutboundProxy)
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await app.start()
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assert component.http_url == "http://127.0.0.1:18080"
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await app.close()
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with pytest.raises(RuntimeError, match="start the component"):
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_ = component.endpoint
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@pytest.mark.asyncio
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async def test_fixed_http_publishes_endpoint_and_merges_environment(monkeypatch) -> None:
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monkeypatch.setenv("HTTP_PROXY", "http://ambient.example:8080")
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component = FixedHttpOutboundProxy(url="http://127.0.0.1:18080")
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base = {"CUSTOM": "value", "NO_PROXY": "example.com"}
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with pytest.raises(RuntimeError, match="start the component"):
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_ = component.http_url
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await component.start()
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merged = component.merge_environment(base)
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assert component.http_url == "http://127.0.0.1:18080"
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assert base == {"CUSTOM": "value", "NO_PROXY": "example.com"}
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assert os.environ["HTTP_PROXY"] == "http://ambient.example:8080"
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assert merged["CUSTOM"] == "value"
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for key in ("HTTP_PROXY", "HTTPS_PROXY", "ALL_PROXY", "http_proxy", "https_proxy", "all_proxy"):
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assert merged[key] == component.http_url
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assert merged["NO_PROXY"] == "127.0.0.1,localhost,::1"
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assert merged["no_proxy"] == "127.0.0.1,localhost,::1"
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await component.close()
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with pytest.raises(RuntimeError, match="start the component"):
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_ = component.endpoint
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@pytest.mark.parametrize(
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("url", "message"),
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[
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("", "must use http"),
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("https://proxy.example:8080", "must use http"),
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("http://proxy.example", "include host and port"),
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("http://user@proxy.example:8080", "must not contain userinfo"),
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("http://proxy.example:8080?mode=x", "must not contain query or fragment"),
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("http://proxy.example:8080#fragment", "must not contain query or fragment"),
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("http://proxy.example:not-a-port", "malformed"),
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],
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)
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@pytest.mark.asyncio
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async def test_fixed_http_rejects_invalid_urls(url: str, message: str) -> None:
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component = FixedHttpOutboundProxy(url=url)
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with pytest.raises(ValueError, match=message):
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await component.start()
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assert component.is_started is False
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with pytest.raises(RuntimeError, match="start the component"):
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_ = component.endpoint
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@pytest.mark.parametrize(
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("kwargs", "message"),
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[
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({"host": "", "account": "agent"}, "host is required"),
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({"host": "proxy.example", "account": ""}, "account is required"),
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({"host": "proxy.example", "account": "agent", "connect_timeout": 0}, "connect_timeout"),
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({"host": "proxy.example", "account": "agent", "monitor_interval": -1}, "monitor_interval"),
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({"host": "proxy.example", "account": "agent", "restart_initial_delay": "bad"}, "restart_initial_delay"),
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({"host": "proxy.example", "account": "agent", "restart_max_delay": float("inf")}, "restart_max_delay"),
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],
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)
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@pytest.mark.asyncio
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async def test_ssh_http_validates_configuration(kwargs: dict, message: str) -> None:
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component = SshHttpOutboundProxy(**kwargs)
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with pytest.raises(ValueError, match=message):
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await component.start()
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@pytest.mark.asyncio
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async def test_ssh_http_requires_ssh_executable(monkeypatch) -> None:
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monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.shutil.which", lambda _name: None)
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component = SshHttpOutboundProxy(host="proxy.example", account="agent")
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with pytest.raises(RuntimeError, match="ssh executable was not found"):
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await component.start()
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@pytest.mark.asyncio
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async def test_ssh_http_starts_expected_commands_and_closes_bridge_first(monkeypatch) -> None:
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events: list[str] = []
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commands: list[tuple[str, ...]] = []
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processes: list[FakeProcess] = []
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async def fake_spawn(*command, **kwargs):
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assert kwargs
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commands.append(command)
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label = "ssh" if command[0] == "/usr/bin/ssh" else "bridge"
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process = FakeProcess(label, events)
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processes.append(process)
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return process
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monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.shutil.which", lambda _name: "/usr/bin/ssh")
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monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.asyncio.create_subprocess_exec", fake_spawn)
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component = SshHttpOutboundProxy(host="proxy.example", account="agent")
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monkeypatch.setattr(component, "_pick_distinct_ports", lambda: (43123, 43124))
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monkeypatch.setattr(component, "_wait_for_listener", _ready_listener)
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await component.start()
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assert component.http_url == "http://127.0.0.1:43124"
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assert commands[0] == (
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"/usr/bin/ssh",
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"-N",
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"-D",
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"127.0.0.1:43123",
|
|
"-o",
|
|
"BatchMode=yes",
|
|
"-o",
|
|
"ExitOnForwardFailure=yes",
|
|
"-o",
|
|
"StrictHostKeyChecking=accept-new",
|
|
"-o",
|
|
"ConnectTimeout=10",
|
|
"-o",
|
|
"LogLevel=ERROR",
|
|
"--",
|
|
"agent@proxy.example",
|
|
)
|
|
assert commands[1] == (
|
|
sys.executable,
|
|
"-m",
|
|
"pproxy",
|
|
"-l",
|
|
"http://127.0.0.1:43124",
|
|
"-r",
|
|
"socks5://127.0.0.1:43123",
|
|
)
|
|
|
|
await component.close()
|
|
|
|
assert events == ["terminate:bridge", "terminate:ssh"]
|
|
assert all(process.returncode == -15 for process in processes)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_ssh_http_cleans_up_when_initial_readiness_fails(monkeypatch) -> None:
|
|
events: list[str] = []
|
|
process = FakeProcess("ssh", events)
|
|
|
|
async def fake_spawn(*_command, **_kwargs):
|
|
return process
|
|
|
|
async def fail_readiness(*_args):
|
|
raise TimeoutError("not ready")
|
|
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.shutil.which", lambda _name: "/usr/bin/ssh")
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.asyncio.create_subprocess_exec", fake_spawn)
|
|
component = SshHttpOutboundProxy(host="proxy.example", account="agent")
|
|
monkeypatch.setattr(component, "_pick_distinct_ports", lambda: (43123, 43124))
|
|
monkeypatch.setattr(component, "_wait_for_listener", fail_readiness)
|
|
|
|
with pytest.raises(RuntimeError, match="SSH proxy exited before readiness"):
|
|
await component.start()
|
|
|
|
assert events == ["terminate:ssh"]
|
|
assert component.is_started is False
|
|
with pytest.raises(RuntimeError, match="start the component"):
|
|
_ = component.endpoint
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_ssh_http_reselects_ports_only_before_endpoint_is_published(monkeypatch) -> None:
|
|
events: list[str] = []
|
|
commands: list[tuple[str, ...]] = []
|
|
selected_ports = iter(((43123, 43124), (43125, 43126)))
|
|
|
|
async def fake_spawn(*command, **_kwargs):
|
|
commands.append(command)
|
|
label = "ssh" if command[0] == "/usr/bin/ssh" else "bridge"
|
|
process = FakeProcess(label, events)
|
|
if label == "ssh" and len(commands) == 1:
|
|
process.exit(255, "bind [127.0.0.1]:43123: Address already in use")
|
|
return process
|
|
|
|
async def fake_readiness(process, *_args):
|
|
if process.returncode is not None:
|
|
raise RuntimeError("process exited")
|
|
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.shutil.which", lambda _name: "/usr/bin/ssh")
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.asyncio.create_subprocess_exec", fake_spawn)
|
|
component = SshHttpOutboundProxy(host="proxy.example", account="agent")
|
|
monkeypatch.setattr(component, "_pick_distinct_ports", lambda: next(selected_ports))
|
|
monkeypatch.setattr(component, "_wait_for_listener", fake_readiness)
|
|
|
|
await component.start()
|
|
|
|
assert component.http_url == "http://127.0.0.1:43126"
|
|
assert [command[0] for command in commands] == ["/usr/bin/ssh", "/usr/bin/ssh", sys.executable]
|
|
await component.close()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_ssh_http_monitor_restarts_on_original_ports(monkeypatch) -> None:
|
|
events: list[str] = []
|
|
commands: list[tuple[str, ...]] = []
|
|
processes: list[FakeProcess] = []
|
|
|
|
async def fake_spawn(*command, **_kwargs):
|
|
commands.append(command)
|
|
label = "ssh" if command[0] == "/usr/bin/ssh" else "bridge"
|
|
process = FakeProcess(label, events)
|
|
processes.append(process)
|
|
return process
|
|
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.shutil.which", lambda _name: "/usr/bin/ssh")
|
|
monkeypatch.setattr("reme.components.outbound_proxy.ssh_http.asyncio.create_subprocess_exec", fake_spawn)
|
|
component = SshHttpOutboundProxy(
|
|
host="proxy.example",
|
|
account="agent",
|
|
monitor_interval=0.005,
|
|
restart_initial_delay=0.005,
|
|
)
|
|
monkeypatch.setattr(component, "_pick_distinct_ports", lambda: (43123, 43124))
|
|
monkeypatch.setattr(component, "_wait_for_listener", _ready_listener)
|
|
await component.start()
|
|
endpoint = component.endpoint
|
|
|
|
processes[0].exit(7)
|
|
await _wait_until(lambda: len(processes) == 3)
|
|
|
|
assert component.endpoint is endpoint
|
|
assert commands[2][0] == "/usr/bin/ssh"
|
|
assert "127.0.0.1:43123" in commands[2]
|
|
assert sum(command[0] == sys.executable for command in commands) == 1
|
|
|
|
processes[1].exit(8)
|
|
await _wait_until(lambda: len(processes) == 4)
|
|
|
|
assert component.endpoint is endpoint
|
|
assert commands[3] == (
|
|
sys.executable,
|
|
"-m",
|
|
"pproxy",
|
|
"-l",
|
|
"http://127.0.0.1:43124",
|
|
"-r",
|
|
"socks5://127.0.0.1:43123",
|
|
)
|
|
|
|
await component.close()
|