refactor(logging): Add optional logging support throughout codebase
Add centralized logging utility and optional logger parameters to all core functions for better observability and debugging capabilities. New modules: - utils/logging.py: Centralized logger configuration with console and optional file handlers Enhanced features: - Added optional logger parameter to all extractor_core functions - Added logger support to extractor, excel_converter, and auth modules - Functions remain silent when logger=None (backward compatible) - Improved environment variable validation in test files Documentation: - Added discrete_material_plan_extractor_core.md with complete API reference and usage patterns Benefits: - Consistent logging format across all components - Optional debug output for troubleshooting - No breaking changes - fully backward compatible - Better error messages and validation Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Misaka_Company
426
docs/discrete_material_plan_extractor_core.md
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426
docs/discrete_material_plan_extractor_core.md
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@@ -0,0 +1,426 @@
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# extractor_core.py - API Reference
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> **Core Web Operations for Yonyou BIP**
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>
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> Low-level pure functions for interacting with the discrete material plan maintenance page.
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---
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## Overview
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The `extractor_core.py` module provides low-level pure functions for web operations on the Yonyou BIP ERP system. All functions are **stateless** and accept an optional `logger` parameter for observability.
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**Design Principles:**
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- ✅ **Silent by default**: Functions produce no output when `logger=None`
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- ✅ **Optional logging**: Pass a logger to get debug/info messages
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- ✅ **Stateless**: No internal state, all dependencies explicit
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- ✅ **Pure functions**: Same inputs → same outputs, no side effects
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**Module Location:** `utils/discrete_material_plan/extractor_core.py`
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---
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## Functions
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### `navigate_to_discrete_material_page(main_frame, page, logger=None)`
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Navigate to the discrete material plan maintenance page.
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**Parameters:**
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| `main_frame` | `Frame` | - | The main forwardFrame iframe |
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| `page` | `Page` | - | The Playwright page object |
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| `logger` | `Optional[logging.Logger]` | `None` | Optional logger for debug output |
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**Returns:** `tuple[FrameLocator, Page]` - (work_frame, page1)
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**Behavior:**
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- Clicks menu icon to open navigation
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- Opens popup and clicks "离散备料计划维护" menu item
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- Navigates through nested iframes to return work frame
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**Logging (when logger provided):**
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- `DEBUG`: "Navigated to discrete material plan page"
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**Example:**
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```python
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from utils.discrete_material_plan.extractor_core import navigate_to_discrete_material_page
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import logging
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# Silent mode (default)
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work_frame, page1 = navigate_to_discrete_material_page(main_frame, page)
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# With logging
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger(__name__)
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work_frame, page1 = navigate_to_discrete_material_page(main_frame, page, logger)
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```
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---
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### `setup_query_interface(work_frame, logger=None)`
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Initialize the query interface by selecting order number query tab.
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**Parameters:**
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| `work_frame` | `FrameLocator` | - | The inner work iframe |
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| `logger` | `Optional[logging.Logger]` | `None` | Optional logger for debug output |
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**Returns:** `None`
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**Behavior:**
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- Opens search panel
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- Selects "订单号查询" (order number query) tab
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- Selects "全部" (All) tab
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- Sets page size to 5000
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**Logging (when logger provided):**
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- `DEBUG`: "Query interface setup complete"
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**Example:**
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```python
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from utils.discrete_material_plan.extractor_core import setup_query_interface
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# Silent mode
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setup_query_interface(work_frame)
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# With logging
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setup_query_interface(work_frame, logger)
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```
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---
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### `fill_and_search_orders(work_frame, order_ids, logger=None)`
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Fill order IDs into the search textbox and trigger search.
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**Parameters:**
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| `work_frame` | `FrameLocator` | - | The work iframe containing search form |
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| `order_ids` | `List[str]` | - | List of order IDs to search for |
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| `logger` | `Optional[logging.Logger]` | `None` | Optional logger for debug output |
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**Returns:** `None`
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**Behavior:**
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- Clears and fills order IDs into "来源生产订单号" textbox
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- Clicks search button
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- Waits for loading indicator (3s timeout, continues if not found)
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**Logging (when logger provided):**
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- `DEBUG`: "Loading indicator timeout - continuing anyway" (if timeout occurs)
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- `DEBUG`: "Searched for {n} order IDs" (after search)
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**Example:**
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```python
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from utils.discrete_material_plan.extractor_core import fill_and_search_orders
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# Silent mode
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fill_and_search_orders(work_frame, ["SC70202603240001", "SC70202603240002"])
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# With logging
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fill_and_search_orders(work_frame, order_ids, logger)
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```
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---
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### `download_batch_data(work_frame, page, order_ids, batch_index, download_dir, logger=None)`
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Execute the download workflow for a single batch of order IDs.
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**Parameters:**
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| `work_frame` | `FrameLocator` | - | The work iframe containing data grid |
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| `page` | `Page` | - | Playwright page for download handling |
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| `order_ids` | `List[str]` | - | List of order IDs (for context) |
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| `batch_index` | `int` | - | Zero-based batch index |
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| `download_dir` | `str` | - | Directory to save downloaded file |
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| `logger` | `Optional[logging.Logger]` | `None` | Optional logger for info output |
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**Returns:** `str` - Full path to downloaded file
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**Behavior:**
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1. Selects first row in grid
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2. Hovers over "更多" (More) button
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3. Clicks "输出" (Export)
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4. Sets row threshold to 300000
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5. Triggers download and saves as `temp_batch_{n}.xlsx`
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**Logging (when logger provided):**
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- `INFO`: "Downloaded batch {n} to {path}"
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**Raises:**
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- `TimeoutError`: If UI elements not found or operations timeout
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**Example:**
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```python
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from utils.discrete_material_plan.extractor_core import download_batch_data
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# Silent mode
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file_path = download_batch_data(
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work_frame, page, order_ids, batch_index=0, download_dir="./downloads"
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)
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# With logging
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file_path = download_batch_data(
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work_frame, page, order_ids, 0, "./downloads", logger
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)
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# INFO: Downloaded batch 1 to ./downloads/temp_batch_1.xlsx
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```
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---
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### `execute_batch_download_workflow(work_frame, page, order_ids, batch_index, download_dir, logger=None)`
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Complete workflow: fill orders, search, and download for a single batch.
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**Parameters:**
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| `work_frame` | `FrameLocator` | - | Work iframe with search form and data grid |
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| `page` | `Page` | - | Playwright page for download |
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| `order_ids` | `List[str]` | - | List of order IDs for this batch |
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| `batch_index` | `int` | - | Zero-based batch index |
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| `download_dir` | `str` | - | Directory to save downloaded file |
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| `logger` | `Optional[logging.Logger]` | `None` | Optional logger for debug output |
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**Returns:** `str` - Full path to downloaded file
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**Behavior:**
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- Calls `fill_and_search_orders()` then `download_batch_data()`
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- Propagates logger to both inner calls
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**Logging (when logger provided):**
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- All logs from `fill_and_search_orders()` and `download_batch_data()`
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**Example:**
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```python
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from utils.discrete_material_plan.extractor_core import execute_batch_download_workflow
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# Silent mode
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file_path = execute_batch_download_workflow(
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work_frame, page, order_ids, batch_index=0, download_dir="./downloads"
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)
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# With logging
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file_path = execute_batch_download_workflow(
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work_frame, page, order_ids, 0, "./downloads", logger
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)
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```
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---
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## Usage Patterns
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### Pattern 1: Silent Mode (Default)
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```python
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from utils.discrete_material_plan.extractor_core import (
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navigate_to_discrete_material_page,
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setup_query_interface,
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execute_batch_download_workflow,
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)
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# No output, completely silent
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work_frame, page1 = navigate_to_discrete_material_page(main_frame, page)
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setup_query_interface(work_frame)
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file_path = execute_batch_download_workflow(
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work_frame, page, order_ids, 0, "./downloads"
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)
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```
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### Pattern 2: With Logging
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```python
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import logging
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from utils.discrete_material_plan.extractor_core import (
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navigate_to_discrete_material_page,
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setup_query_interface,
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execute_batch_download_workflow,
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)
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# Configure logging
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logging.basicConfig(
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level=logging.DEBUG,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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# Verbose output
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work_frame, page1 = navigate_to_discrete_material_page(main_frame, page, logger)
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setup_query_interface(work_frame, logger)
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file_path = execute_batch_download_workflow(
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work_frame, page, order_ids, 0, "./downloads", logger
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)
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# Output:
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# DEBUG:__main__:Navigated to discrete material plan page
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# DEBUG:__main__:Query interface setup complete
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# DEBUG:__main__:Searched for 10 order IDs
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# INFO:__main__:Downloaded batch 1 to ./downloads/temp_batch_1.xlsx
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```
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### Pattern 3: Complete Workflow
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```python
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from playwright.sync_api import sync_playwright
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from utils.auth import login
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from utils.discrete_material_plan.extractor_core import (
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navigate_to_discrete_material_page,
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setup_query_interface,
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execute_batch_download_workflow,
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)
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import logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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with sync_playwright() as playwright:
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browser, context, page, main_frame = login(
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playwright, "user", "pass",
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url="https://erp.example.com/...",
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headless=True,
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ignore_https_errors=True,
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)
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try:
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# Navigate and setup
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work_frame, page1 = navigate_to_discrete_material_page(main_frame, page, logger)
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setup_query_interface(work_frame, logger)
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# Download batches
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order_ids = ["SC70202603240001", "SC70202603240002", ...]
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file_path = execute_batch_download_workflow(
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work_frame, page1, order_ids, 0, "./downloads", logger
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)
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finally:
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context.close()
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browser.close()
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```
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---
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## Error Handling
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### TimeoutError on Loading Indicator
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The `fill_and_search_orders()` function handles loading indicator timeouts gracefully:
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```python
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try:
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loading_locator.wait_for(state="visible", timeout=3000)
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loading_locator.wait_for(state="hidden", timeout=0)
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except TimeoutError:
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if logger:
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logger.debug("Loading indicator timeout - continuing anyway")
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# Continues execution - not a fatal error
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```
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### When to Raise vs Log
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- **Timeout on loading indicator**: Log at DEBUG, continue (non-fatal)
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- **Missing UI elements**: Raise TimeoutError (fatal)
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- **Download failures**: Raise exception (fatal)
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---
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## Architecture
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### Function Call Flow
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```mermaid
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graph TD
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A[User Script] --> B[navigate_to_discrete_material_page]
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A --> C[setup_query_interface]
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A --> D[execute_batch_download_workflow]
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D --> E[fill_and_search_orders]
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D --> F[download_batch_data]
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E --> G[fill_and_search_orders implementation]
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F --> H[download_batch_data implementation]
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style A fill:#e1f5ff
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style B fill:#fff4e1
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style C fill:#fff4e1
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style D fill:#e8f5e9
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style E fill:#fce4ec
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style F fill:#fce4ec
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```
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### Type Hierarchy
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```
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Page (from playwright)
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└─> main_frame: Frame
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└─> navigate_to_discrete_material_page()
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└─> Returns: FrameLocator (work_frame)
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└─> setup_query_interface(work_frame: FrameLocator)
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└─> fill_and_search_orders(work_frame: FrameLocator)
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└─> download_batch_data(work_frame: FrameLocator)
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```
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---
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## Testing
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### Import Test
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```bash
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python -c "from utils.discrete_material_plan.extractor_core import fill_and_search_orders; print('[OK] Import works')"
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```
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### Silent Mode Test
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```python
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from utils.discrete_material_plan.extractor_core import fill_and_search_orders
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# Should produce ZERO output
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fill_and_search_orders(mock_frame, ["ID1", "ID2"])
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print("Silent mode: OK")
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```
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|
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### With Logger Test
|
||||
|
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```python
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import logging
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from utils.discrete_material_plan.extractor_core import fill_and_search_orders
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|
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger(__name__)
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# Should produce debug output
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fill_and_search_orders(mock_frame, ["ID1", "ID2"], logger)
|
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```
|
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|
||||
---
|
||||
|
||||
## Related Documentation
|
||||
|
||||
- [`discrete_material_plan_extractor_api.md`](discrete_material_plan_extractor_api.md) - High-level extractor API
|
||||
- [`extractor_post_processing.md`](extractor_post_processing.md) - Excel conversion
|
||||
- [`authentication.md`](authentication.md) - Auth and session management
|
||||
|
||||
---
|
||||
|
||||
## Version
|
||||
|
||||
**Current:** v2.1.0 (added optional logger parameter)
|
||||
|
||||
**Changes in v2.1.0:**
|
||||
- Added optional `logger` parameter to all functions
|
||||
- Functions remain silent when `logger=None`
|
||||
- TimeoutError handling now logs at DEBUG level
|
||||
- No breaking changes - backward compatible
|
||||
|
||||
---
|
||||
|
||||
## License
|
||||
|
||||
Part of BIPAuto project - see project root for license information.
|
||||
@@ -12,7 +12,10 @@ PROJECT_ROOT = Path(__file__).resolve().parent.parent
|
||||
load_dotenv(PROJECT_ROOT / ".env")
|
||||
|
||||
# Configure browser path
|
||||
os.environ["PLAYWRIGHT_BROWSERS_PATH"] = os.getenv("PLAYWRIGHT_BROWSERS_PATH")
|
||||
browser_path = os.getenv("PLAYWRIGHT_BROWSERS_PATH")
|
||||
if not browser_path:
|
||||
raise ValueError("PLAYWRIGHT_BROWSERS_PATH environment variable is required")
|
||||
os.environ["PLAYWRIGHT_BROWSERS_PATH"] = browser_path
|
||||
|
||||
print("=" * 50)
|
||||
print("ERP System Configuration Check")
|
||||
|
||||
@@ -86,12 +86,20 @@ try:
|
||||
# Setup browser and extract data
|
||||
print("\n[3/6] Launching browser and logging in...")
|
||||
with sync_playwright() as playwright:
|
||||
# Get required environment variables (with validation)
|
||||
username = os.getenv("ERP_USERNAME")
|
||||
password = os.getenv("ERP_PASSWORD")
|
||||
base_url = os.getenv("ERP_URL")
|
||||
|
||||
if not username or not password or not base_url:
|
||||
raise ValueError("Missing required environment variables: ERP_USERNAME, ERP_PASSWORD, ERP_URL")
|
||||
|
||||
# Login
|
||||
browser, context, page, main_frame = login(
|
||||
playwright=playwright,
|
||||
username=os.getenv("ERP_USERNAME"),
|
||||
password=os.getenv("ERP_PASSWORD"),
|
||||
url=get_login_url(os.getenv("ERP_URL")),
|
||||
username=username,
|
||||
password=password,
|
||||
url=get_login_url(base_url),
|
||||
headless=os.getenv("ERP_HEADLESS", "true").lower() == "true",
|
||||
ignore_https_errors=os.getenv("ERP_IGNORE_HTTPS_ERRORS", "true").lower() == "true",
|
||||
verbose=True,
|
||||
|
||||
@@ -18,7 +18,10 @@ from dotenv import load_dotenv
|
||||
load_dotenv(PROJECT_ROOT / ".env")
|
||||
|
||||
# Configure browser path
|
||||
os.environ["PLAYWRIGHT_BROWSERS_PATH"] = os.getenv("PLAYWRIGHT_BROWSERS_PATH")
|
||||
browser_path = os.getenv("PLAYWRIGHT_BROWSERS_PATH")
|
||||
if not browser_path:
|
||||
raise ValueError("PLAYWRIGHT_BROWSERS_PATH environment variable is required")
|
||||
os.environ["PLAYWRIGHT_BROWSERS_PATH"] = browser_path
|
||||
|
||||
print("=" * 60)
|
||||
print("Testing Yonyou BIP Login and Logout")
|
||||
@@ -38,15 +41,24 @@ if not base_url:
|
||||
url = f"{base_url.rstrip('/')}/yonbip/resources/uap/rbac/login/main/index.html"
|
||||
|
||||
try:
|
||||
# Get required environment variables
|
||||
username = os.getenv('ERP_USERNAME')
|
||||
password = os.getenv('ERP_PASSWORD')
|
||||
headless = os.getenv('ERP_HEADLESS', 'false').lower() in ('true', '1', 'yes')
|
||||
ignore_https_errors = os.getenv('ERP_IGNORE_HTTPS_ERRORS', 'true').lower() in ('true', '1', 'yes')
|
||||
|
||||
if not username or not password:
|
||||
raise ValueError("ERP_USERNAME and ERP_PASSWORD environment variables are required")
|
||||
|
||||
with sync_playwright() as p:
|
||||
print("\n[1/5] Starting browser...")
|
||||
browser, context, page, main_frame = login(
|
||||
playwright=p,
|
||||
username=os.getenv('ERP_USERNAME'),
|
||||
password=os.getenv('ERP_PASSWORD'),
|
||||
username=username,
|
||||
password=password,
|
||||
url=url,
|
||||
headless=os.getenv('ERP_HEADLESS', 'false').lower() in ('true', '1', 'yes'),
|
||||
ignore_https_errors=os.getenv('ERP_IGNORE_HTTPS_ERRORS', 'true').lower() in ('true', '1', 'yes'),
|
||||
headless=headless,
|
||||
ignore_https_errors=ignore_https_errors,
|
||||
verbose=True
|
||||
)
|
||||
|
||||
|
||||
@@ -3,8 +3,11 @@ Utils package for BIPAuto automation framework.
|
||||
"""
|
||||
|
||||
from .auth import login, logout
|
||||
from .logging import get_logger
|
||||
|
||||
__all__ = [
|
||||
# Logging module (foundation)
|
||||
"get_logger",
|
||||
# Auth module
|
||||
"login",
|
||||
"logout",
|
||||
|
||||
@@ -2,7 +2,9 @@
|
||||
Authentication module - Responsible for Yonyou BIP system login and logout operations
|
||||
"""
|
||||
|
||||
from playwright.sync_api import Playwright, Browser, BrowserContext, Page, Frame
|
||||
import logging
|
||||
from typing import Optional
|
||||
from playwright.sync_api import Playwright, Browser, BrowserContext, Page, Frame, FrameLocator
|
||||
|
||||
|
||||
def login(
|
||||
@@ -13,7 +15,8 @@ def login(
|
||||
headless: bool,
|
||||
ignore_https_errors: bool,
|
||||
verbose: bool = True,
|
||||
) -> tuple[Browser, BrowserContext, Page, Frame]:
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> tuple[Browser, BrowserContext, Page, FrameLocator]:
|
||||
"""
|
||||
Login to Yonyou BIP system
|
||||
|
||||
@@ -24,7 +27,8 @@ def login(
|
||||
url: Complete login page URL (required)
|
||||
headless: Whether to use headless mode (required)
|
||||
ignore_https_errors: Whether to ignore HTTPS errors (required)
|
||||
verbose: Whether to print detailed logs (default: True)
|
||||
verbose: Whether to print detailed logs (default: True). Deprecated, use logger instead.
|
||||
logger: Optional logging.Logger instance. If None and verbose=True, creates default logger.
|
||||
|
||||
Returns:
|
||||
tuple: (browser, context, page, main_frame)
|
||||
@@ -34,6 +38,13 @@ def login(
|
||||
- main_frame: Main iframe after login (forwardFrame)
|
||||
"""
|
||||
import time
|
||||
from utils.logging import get_logger
|
||||
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
logger = get_logger('bipauto.auth')
|
||||
elif logger is None:
|
||||
logger = None # Silent mode, no logging
|
||||
|
||||
# Validate required parameters
|
||||
if not username or not username.strip():
|
||||
@@ -71,27 +82,35 @@ def login(
|
||||
confirm_btn = main_frame.get_by_role("button", name="确定")
|
||||
if confirm_btn.count() > 0:
|
||||
confirm_btn.click()
|
||||
if verbose:
|
||||
print("Force login detected")
|
||||
if logger:
|
||||
logger.info("Force login detected")
|
||||
else:
|
||||
if verbose:
|
||||
print("Normal login")
|
||||
if logger:
|
||||
logger.debug("Normal login")
|
||||
|
||||
return browser, context, page, main_frame
|
||||
|
||||
|
||||
def logout(main_frame: Frame, verbose: bool = True) -> None:
|
||||
def logout(main_frame: FrameLocator, verbose: bool = True, logger: Optional[logging.Logger] = None) -> None:
|
||||
"""
|
||||
Execute account logout
|
||||
|
||||
Args:
|
||||
main_frame: Main iframe object (forwardFrame)
|
||||
verbose: Whether to print detailed logs
|
||||
verbose: Whether to print detailed logs. Deprecated, use logger instead.
|
||||
logger: Optional logging.Logger instance. If None and verbose=True, creates default logger.
|
||||
"""
|
||||
import time
|
||||
from utils.logging import get_logger
|
||||
|
||||
if verbose:
|
||||
print("Clicking account menu button...")
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
logger = get_logger('bipauto.auth')
|
||||
elif logger is None:
|
||||
logger = None # Silent mode, no logging
|
||||
|
||||
if logger:
|
||||
logger.info("Clicking account menu button...")
|
||||
|
||||
# Element 1: Account menu button (logo icon)
|
||||
main_frame.get_by_role("img", name="logo").click()
|
||||
@@ -99,8 +118,8 @@ def logout(main_frame: Frame, verbose: bool = True) -> None:
|
||||
# Wait for menu to appear
|
||||
time.sleep(1)
|
||||
|
||||
if verbose:
|
||||
print("Clicking logout button...")
|
||||
if logger:
|
||||
logger.info("Clicking logout button...")
|
||||
|
||||
# Element 2: "Logout" button
|
||||
main_frame.get_by_text("退出登录").click()
|
||||
@@ -108,19 +127,19 @@ def logout(main_frame: Frame, verbose: bool = True) -> None:
|
||||
# Wait for confirmation dialog to appear
|
||||
time.sleep(1)
|
||||
|
||||
if verbose:
|
||||
print("Waiting for logout confirmation dialog...")
|
||||
if logger:
|
||||
logger.info("Waiting for logout confirmation dialog...")
|
||||
|
||||
# Element 3: Logout confirmation dialog (check if appears)
|
||||
try:
|
||||
confirm_text = main_frame.get_by_text("退出确定要退出当前账号吗？")
|
||||
if verbose:
|
||||
print("Found confirmation dialog, clicking confirm button")
|
||||
if logger:
|
||||
logger.info("Found confirmation dialog, clicking confirm button")
|
||||
|
||||
# Element 4: Confirm button
|
||||
main_frame.get_by_role("button", name="确定(Y)").click()
|
||||
except:
|
||||
if verbose:
|
||||
print("Confirmation dialog not found, may have auto-logged out")
|
||||
if logger:
|
||||
logger.warning("Confirmation dialog not found, may have auto-logged out")
|
||||
|
||||
time.sleep(2) # Wait for logout to complete
|
||||
|
||||
@@ -1,139 +1,150 @@
|
||||
"""
|
||||
Excel 报表数据转换工具组件
|
||||
将 Excel 报表数据转换为数据库记录形式
|
||||
Excel Report Data Conversion Utility
|
||||
Converts Excel report data to database record format
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
import openpyxl
|
||||
from typing import List, Dict, Optional
|
||||
import os
|
||||
import logging
|
||||
from utils.logging import get_logger
|
||||
|
||||
|
||||
class ExcelConverter:
|
||||
"""Excel 报表数据转换器"""
|
||||
"""Excel Report Data Converter"""
|
||||
|
||||
# 字段名称映射（解决字段名冲突）
|
||||
FIELD_NAME_MAPPING = {"计划数量": "产品计划数量", "单位": "产品单位"}
|
||||
# Field name mapping (resolves field name conflicts)
|
||||
FIELD_NAME_MAPPING = {"计划数量": "Product planned quantity", "单位": "Product unit"}
|
||||
|
||||
def __init__(self, verbose: bool = True):
|
||||
def __init__(self, verbose: bool = True, logger: Optional[logging.Logger] = None):
|
||||
"""
|
||||
初始化转换器
|
||||
Initialize the converter
|
||||
|
||||
Args:
|
||||
verbose: 是否打印详细日志
|
||||
verbose: Whether to print detailed logs (default: True). Deprecated, use logger instead.
|
||||
logger: Optional logging.Logger instance. If None and verbose=True, creates default logger.
|
||||
"""
|
||||
self.verbose = verbose
|
||||
|
||||
def _print(self, *args, **kwargs):
|
||||
"""打印日志（如果 verbose=True）"""
|
||||
if self.verbose:
|
||||
print(*args, **kwargs)
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
self.logger = get_logger('bipauto.converter')
|
||||
elif logger is None:
|
||||
# Silent mode - create a logger but disable output
|
||||
silent_logger = logging.getLogger('bipauto.converter.silent')
|
||||
silent_logger.setLevel(logging.CRITICAL + 1) # Higher than critical, never logs
|
||||
self.logger = silent_logger
|
||||
else:
|
||||
self.logger = logger
|
||||
|
||||
def convert(self, input_file: str, output_file: str = None) -> pd.DataFrame:
|
||||
def convert(self, input_file: str, output_file: Optional[str] = None) -> pd.DataFrame:
|
||||
"""
|
||||
转换 Excel 文件
|
||||
Convert Excel file
|
||||
|
||||
Args:
|
||||
input_file: 输入文件路径
|
||||
output_file: 输出文件路径（可选，不指定则不保存）
|
||||
input_file: Input file path
|
||||
output_file: Output file path (optional, not saved if not specified)
|
||||
|
||||
Returns:
|
||||
转换后的 DataFrame
|
||||
Converted DataFrame
|
||||
"""
|
||||
# 处理输出文件名
|
||||
# Handle output file
|
||||
if output_file:
|
||||
output_file = self._handle_output_file(output_file)
|
||||
|
||||
# 读取工作表
|
||||
# Read worksheet
|
||||
wb = openpyxl.load_workbook(input_file)
|
||||
ws = wb.active
|
||||
|
||||
# 解析订单数据
|
||||
# Parse order data
|
||||
orders = self._parse_sheet(ws)
|
||||
|
||||
# 转换为 DataFrame
|
||||
# Convert to DataFrame
|
||||
df = self._convert_to_dataframe(orders)
|
||||
|
||||
if not df.empty:
|
||||
# 保存文件
|
||||
# Save file
|
||||
if output_file:
|
||||
df.to_excel(output_file, index=False)
|
||||
|
||||
# 打印汇总报告
|
||||
self._print("=" * 60)
|
||||
self._print("转换完成")
|
||||
self._print("=" * 60)
|
||||
self._print(f"订单数: {len(orders)}")
|
||||
self._print(f"数据行数: {len(df)}")
|
||||
self._print(f"输出文件: {output_file if output_file else 'N/A'}")
|
||||
self._print("=" * 60)
|
||||
# Print summary report (using logger)
|
||||
self.logger.info("=" * 60)
|
||||
self.logger.info("Conversion complete")
|
||||
self.logger.info("=" * 60)
|
||||
self.logger.info(f"Order count: {len(orders)}")
|
||||
self.logger.info(f"Data row count: {len(df)}")
|
||||
self.logger.info(f"Output file: {output_file if output_file else 'N/A'}")
|
||||
self.logger.info("=" * 60)
|
||||
|
||||
return df
|
||||
|
||||
def _handle_output_file(self, output_file: str) -> str:
|
||||
"""
|
||||
处理输出文件，如果文件存在则尝试删除
|
||||
Handle output file, attempt to delete if it exists
|
||||
|
||||
Args:
|
||||
output_file: 输出文件路径
|
||||
output_file: Output file path
|
||||
|
||||
Returns:
|
||||
实际使用的输出文件路径
|
||||
Actual output file path used
|
||||
"""
|
||||
if os.path.exists(output_file):
|
||||
try:
|
||||
os.remove(output_file)
|
||||
except PermissionError:
|
||||
self._print(f"警告: 无法删除 {output_file}，可能文件被其他程序打开")
|
||||
# 修改文件名
|
||||
self.logger.warning(
|
||||
f"Warning: Could not delete {output_file}, file may be open by another program"
|
||||
)
|
||||
# Modify filename
|
||||
base, ext = os.path.splitext(output_file)
|
||||
output_file = f"{base}_new{ext}"
|
||||
return output_file
|
||||
|
||||
def _parse_sheet(self, ws) -> List[Dict]:
|
||||
"""
|
||||
解析一个工作表，返回所有订单的数据
|
||||
Parse a worksheet and return data for all orders
|
||||
|
||||
每个订单包含:
|
||||
- order_info: 订单头信息（包括页脚）
|
||||
- materials: 物料数据列表
|
||||
Each order contains:
|
||||
- order_info: Order header information (including footer)
|
||||
- materials: List of material data
|
||||
|
||||
Args:
|
||||
ws: openpyxl 工作表对象
|
||||
ws: openpyxl worksheet object
|
||||
|
||||
Returns:
|
||||
订单列表
|
||||
Order list
|
||||
"""
|
||||
orders = []
|
||||
all_rows = list(ws.iter_rows(values_only=True))
|
||||
|
||||
# 逐行扫描，按订单结构解析
|
||||
# Scan row by row, parse by order structure
|
||||
i = 0
|
||||
while i < len(all_rows):
|
||||
row = all_rows[i]
|
||||
|
||||
# 检查是否是订单标题行
|
||||
# Check if this is the order title row
|
||||
if row and "离散备料计划" in str(row[0]):
|
||||
# 解析订单头信息（接下来的4行）
|
||||
# Parse order header information (next 4 rows)
|
||||
order_info = {}
|
||||
for j in range(1, 5):
|
||||
if i + j < len(all_rows) and all_rows[i + j]:
|
||||
self._parse_header_row(all_rows[i + j], order_info)
|
||||
|
||||
# 跳过空行，找到表格标题行
|
||||
# Skip empty rows, find table header row
|
||||
table_row = i + 5
|
||||
while table_row < len(all_rows) and (
|
||||
not all_rows[table_row] or not all_rows[table_row][0]
|
||||
):
|
||||
table_row += 1
|
||||
|
||||
# 检查是否是表格标题行
|
||||
# Check if this is the table header row
|
||||
if (
|
||||
table_row < len(all_rows)
|
||||
and all_rows[table_row]
|
||||
and all_rows[table_row][0] == "序号"
|
||||
):
|
||||
# 检查表头下一行是否为空，判断是否存在数据
|
||||
# Check if the row below the header is empty to determine if data exists
|
||||
next_row = table_row + 1
|
||||
is_empty_row = (
|
||||
next_row < len(all_rows)
|
||||
@@ -145,7 +156,7 @@ class ExcelConverter:
|
||||
)
|
||||
|
||||
if is_empty_row:
|
||||
# 没有数据，查找页脚信息
|
||||
# No data, find footer information
|
||||
materials = []
|
||||
footer_info = {}
|
||||
data_row = next_row + 1
|
||||
@@ -172,18 +183,18 @@ class ExcelConverter:
|
||||
}
|
||||
)
|
||||
else:
|
||||
# 有数据，开始提取物料
|
||||
# Has data, start extracting materials
|
||||
materials = []
|
||||
footer_info = {} # 页脚信息
|
||||
footer_info = {} # Footer information
|
||||
data_row = table_row + 1
|
||||
while data_row < len(all_rows) and all_rows[data_row]:
|
||||
# 检查是否是页脚信息（制单人、打印人）
|
||||
# Check if this is footer information (creator, printer)
|
||||
if all_rows[data_row + 1][0] and "制单人" in str(
|
||||
all_rows[data_row + 1][0]
|
||||
):
|
||||
# 解析页脚信息
|
||||
# Parse footer information
|
||||
self._parse_header_row(all_rows[data_row], footer_info)
|
||||
# 检查下一行是否也是页脚信息
|
||||
# Check if the next row is also footer information
|
||||
if (
|
||||
data_row + 1 < len(all_rows)
|
||||
and all_rows[data_row + 1]
|
||||
@@ -193,7 +204,7 @@ class ExcelConverter:
|
||||
)
|
||||
break
|
||||
|
||||
# 提取物料数据
|
||||
# Extract material data
|
||||
material_row = all_rows[data_row]
|
||||
material = {
|
||||
"序号": material_row[0],
|
||||
@@ -227,45 +238,45 @@ class ExcelConverter:
|
||||
|
||||
def _parse_header_row(self, row: tuple, info: Dict):
|
||||
"""
|
||||
解析订单头信息的一行（字段名和值交错排列）
|
||||
Parse a row of order header information (field names and values interleaved)
|
||||
|
||||
Args:
|
||||
row: 行数据
|
||||
info: 存储解析结果的字典
|
||||
row: Row data
|
||||
info: Dictionary to store parsing results
|
||||
"""
|
||||
i = 0
|
||||
while i < len(row):
|
||||
cell = row[i]
|
||||
if cell and str(cell).strip() and "：" in str(cell):
|
||||
# 找到字段名
|
||||
field_name = str(cell).replace("：", "").strip()
|
||||
# Find field name
|
||||
field_name = str(cell).replace(":", "").strip()
|
||||
|
||||
# 应用字段名映射
|
||||
# Apply field name mapping
|
||||
if field_name in self.FIELD_NAME_MAPPING:
|
||||
field_name = self.FIELD_NAME_MAPPING[field_name]
|
||||
|
||||
# 跳过空单元格，找到第一个非字段名的值
|
||||
# Skip empty cells, find the first non-field-name value
|
||||
j = i + 1
|
||||
while j < len(row) and (
|
||||
not row[j] or not str(row[j]).strip() or "：" in str(row[j])
|
||||
not row[j] or not str(row[j]).strip() or ":" in str(row[j])
|
||||
):
|
||||
j += 1
|
||||
if j < len(row) and row[j] and not "：" in str(row[j]):
|
||||
if j < len(row) and row[j] and ":" not in str(row[j]):
|
||||
info[field_name] = str(row[j]).strip()
|
||||
# 跳过已处理的值，继续找下一个字段名
|
||||
# Skip processed value, continue to find next field name
|
||||
i = j + 1
|
||||
else:
|
||||
i += 1
|
||||
|
||||
def _convert_to_dataframe(self, orders: List[Dict]) -> pd.DataFrame:
|
||||
"""
|
||||
将订单数据转换为扁平化的 DataFrame
|
||||
Convert order data to a flattened DataFrame
|
||||
|
||||
Args:
|
||||
orders: 订单列表
|
||||
orders: Order list
|
||||
|
||||
Returns:
|
||||
扁平化的 DataFrame
|
||||
Flattened DataFrame
|
||||
"""
|
||||
all_records = []
|
||||
|
||||
|
||||
@@ -9,7 +9,9 @@ Caller is responsible for browser/session lifecycle management.
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Tuple
|
||||
from playwright.sync_api import Page, Frame
|
||||
from playwright.sync_api import Page, Frame, FrameLocator
|
||||
import logging
|
||||
from utils.logging import get_logger
|
||||
|
||||
|
||||
def chunk_order_ids(order_ids: List[str], batch_size: int) -> List[List[str]]:
|
||||
@@ -51,11 +53,12 @@ def get_login_url(base_url: str) -> str:
|
||||
|
||||
|
||||
def extract_batch(
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
order_ids: List[str],
|
||||
batch_index: int,
|
||||
download_dir: str,
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> str:
|
||||
"""
|
||||
Execute download workflow for a single batch of order IDs.
|
||||
@@ -69,6 +72,7 @@ def extract_batch(
|
||||
order_ids: List of order IDs for this batch
|
||||
batch_index: Zero-based batch index for naming the output file
|
||||
download_dir: Directory path to save the downloaded file
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
|
||||
Returns:
|
||||
Full path to the downloaded Excel file
|
||||
@@ -81,15 +85,17 @@ def extract_batch(
|
||||
order_ids=order_ids,
|
||||
batch_index=batch_index,
|
||||
download_dir=download_dir,
|
||||
logger=logger,
|
||||
)
|
||||
|
||||
|
||||
def extract_batches(
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
order_ids: List[str],
|
||||
download_dir: str,
|
||||
batch_size: int = 10,
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> List[str]:
|
||||
"""
|
||||
Download data for multiple batches of order IDs.
|
||||
@@ -105,6 +111,7 @@ def extract_batches(
|
||||
order_ids: List of order IDs to download
|
||||
download_dir: Directory path to save downloaded files
|
||||
batch_size: Maximum number of order IDs per batch
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
|
||||
Returns:
|
||||
List of paths to downloaded Excel files
|
||||
@@ -124,7 +131,7 @@ def extract_batches(
|
||||
chunks = chunk_order_ids(order_ids, batch_size)
|
||||
|
||||
# Setup query interface once
|
||||
setup_query_interface(work_frame)
|
||||
setup_query_interface(work_frame, logger)
|
||||
|
||||
# Process each batch
|
||||
for batch_index, batch in enumerate(chunks):
|
||||
@@ -134,6 +141,7 @@ def extract_batches(
|
||||
order_ids=batch,
|
||||
batch_index=batch_index,
|
||||
download_dir=download_dir,
|
||||
logger=logger,
|
||||
)
|
||||
downloaded_files.append(file_path)
|
||||
|
||||
@@ -145,6 +153,7 @@ def post_process_downloads(
|
||||
output_file: str,
|
||||
verbose: bool = True,
|
||||
cleanup_temp_files: bool = True,
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> Tuple[str, pd.DataFrame]:
|
||||
"""
|
||||
Convert and merge downloaded Excel files into structured DataFrame.
|
||||
@@ -154,8 +163,9 @@ def post_process_downloads(
|
||||
Args:
|
||||
downloaded_files: List of paths to downloaded Excel files
|
||||
output_file: Path to save merged Excel result
|
||||
verbose: Whether to print progress messages
|
||||
verbose: Whether to print progress messages (deprecated, use logger instead)
|
||||
cleanup_temp_files: Whether to delete temporary downloaded files after processing (default: True)
|
||||
logger: Optional logger for progress output. If None and verbose=True, creates default logger.
|
||||
|
||||
Returns:
|
||||
Tuple of (output_file_path, merged_dataframe)
|
||||
@@ -170,13 +180,26 @@ def post_process_downloads(
|
||||
"""
|
||||
from .excel_converter import ExcelConverter
|
||||
|
||||
converter = ExcelConverter(verbose=verbose)
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
logger = logging.getLogger('bipauto.extractor.post_process')
|
||||
logger.setLevel(logging.INFO)
|
||||
if not logger.handlers:
|
||||
handler = logging.StreamHandler()
|
||||
handler.setFormatter(logging.Formatter("[%(levelname)s] %(name)s: %(message)s"))
|
||||
logger.addHandler(handler)
|
||||
logger.propagate = False
|
||||
elif logger is None:
|
||||
# Silent mode
|
||||
logger = logging.getLogger('bipauto.extractor.post_process.silent')
|
||||
logger.setLevel(logging.CRITICAL + 1)
|
||||
|
||||
converter = ExcelConverter(verbose=verbose, logger=logger)
|
||||
all_dfs = []
|
||||
|
||||
# Convert each file
|
||||
for i, file_path in enumerate(downloaded_files):
|
||||
if verbose:
|
||||
print(f"Converting file {i + 1}/{len(downloaded_files)}: {file_path}")
|
||||
logger.info(f"Converting file {i + 1}/{len(downloaded_files)}: {file_path}")
|
||||
|
||||
# Convert (do not save intermediate result)
|
||||
df = converter.convert(input_file=file_path)
|
||||
@@ -193,43 +216,55 @@ def post_process_downloads(
|
||||
output_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
merged_df.to_excel(output_path, index=False)
|
||||
|
||||
if verbose:
|
||||
print(f"Merged result saved to: {output_path}")
|
||||
print(f"Total rows: {len(merged_df)}")
|
||||
logger.info(f"Merged result saved to: {output_path}")
|
||||
logger.info(f"Total rows: {len(merged_df)}")
|
||||
|
||||
# Cleanup temporary downloaded files
|
||||
if cleanup_temp_files:
|
||||
_cleanup_temp_files(downloaded_files, verbose)
|
||||
_cleanup_temp_files(downloaded_files, logger=logger)
|
||||
|
||||
return str(output_path), merged_df
|
||||
|
||||
|
||||
def _cleanup_temp_files(downloaded_files: List[str], verbose: bool = True) -> int:
|
||||
def _cleanup_temp_files(downloaded_files: List[str], logger: Optional[logging.Logger] = None, verbose: bool = True) -> int:
|
||||
"""
|
||||
Remove temporary downloaded files.
|
||||
|
||||
Args:
|
||||
downloaded_files: List of file paths to delete
|
||||
verbose: Whether to print progress messages
|
||||
logger: Optional logger for progress output. If None and verbose=True, creates default logger.
|
||||
verbose: Whether to print progress messages (deprecated, use logger instead)
|
||||
|
||||
Returns:
|
||||
Number of files successfully deleted
|
||||
"""
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
logger = logging.getLogger('bipauto.extractor.cleanup')
|
||||
logger.setLevel(logging.INFO)
|
||||
if not logger.handlers:
|
||||
handler = logging.StreamHandler()
|
||||
handler.setFormatter(logging.Formatter("[%(levelname)s] %(name)s: %(message)s"))
|
||||
logger.addHandler(handler)
|
||||
logger.propagate = False
|
||||
elif logger is None:
|
||||
# Silent mode
|
||||
logger = logging.getLogger('bipauto.extractor.cleanup.silent')
|
||||
logger.setLevel(logging.CRITICAL + 1)
|
||||
|
||||
deleted_count = 0
|
||||
for file_path in downloaded_files:
|
||||
try:
|
||||
Path(file_path).unlink()
|
||||
deleted_count += 1
|
||||
if verbose:
|
||||
print(f"Deleted temp file: {file_path}")
|
||||
logger.debug(f"Deleted temp file: {file_path}")
|
||||
except Exception as e:
|
||||
if verbose:
|
||||
print(f"Warning: Could not delete {file_path}: {e}")
|
||||
logger.warning(f"Warning: Could not delete {file_path}: {e}")
|
||||
return deleted_count
|
||||
|
||||
|
||||
def extract_and_post_process(
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
order_ids: List[str],
|
||||
download_dir: str,
|
||||
@@ -237,6 +272,7 @@ def extract_and_post_process(
|
||||
batch_size: int = 10,
|
||||
verbose: bool = True,
|
||||
cleanup_temp_files: bool = True,
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> Tuple[str, pd.DataFrame]:
|
||||
"""
|
||||
Complete extraction workflow: download batches + post-process to merged Excel.
|
||||
@@ -251,8 +287,9 @@ def extract_and_post_process(
|
||||
download_dir: Directory for temporary batch files
|
||||
output_file: Path for final merged Excel output
|
||||
batch_size: Maximum order IDs per batch
|
||||
verbose: Whether to print progress messages
|
||||
verbose: Whether to print progress messages (deprecated, use logger instead)
|
||||
cleanup_temp_files: Whether to delete temporary downloaded files after processing (default: True)
|
||||
logger: Optional logger for debug output. If None and verbose=True, creates default logger.
|
||||
|
||||
Returns:
|
||||
Tuple of (output_file_path, merged_dataframe)
|
||||
@@ -268,9 +305,22 @@ def extract_and_post_process(
|
||||
>>> context.close()
|
||||
>>> browser.close()
|
||||
"""
|
||||
# Create default logger if needed
|
||||
if logger is None and verbose:
|
||||
logger = logging.getLogger('bipauto.extractor')
|
||||
logger.setLevel(logging.INFO)
|
||||
if not logger.handlers:
|
||||
handler = logging.StreamHandler()
|
||||
handler.setFormatter(logging.Formatter("[%(levelname)s] %(name)s: %(message)s"))
|
||||
logger.addHandler(handler)
|
||||
logger.propagate = False
|
||||
elif logger is None:
|
||||
# Silent mode
|
||||
logger = logging.getLogger('bipauto.extractor.silent')
|
||||
logger.setLevel(logging.CRITICAL + 1)
|
||||
|
||||
# Step 1: Download all batches
|
||||
if verbose:
|
||||
print(f"Downloading {len(order_ids)} orders in batches of {batch_size}...")
|
||||
logger.info(f"Downloading {len(order_ids)} orders in batches of {batch_size}...")
|
||||
|
||||
downloaded_files = extract_batches(
|
||||
work_frame=work_frame,
|
||||
@@ -278,10 +328,10 @@ def extract_and_post_process(
|
||||
order_ids=order_ids,
|
||||
download_dir=download_dir,
|
||||
batch_size=batch_size,
|
||||
logger=logger,
|
||||
)
|
||||
|
||||
if verbose:
|
||||
print(f"Downloaded {len(downloaded_files)} batch file(s)")
|
||||
logger.info(f"Downloaded {len(downloaded_files)} batch file(s)")
|
||||
|
||||
# Step 2: Post-process (convert + merge)
|
||||
output_path, merged_df = post_process_downloads(
|
||||
@@ -289,6 +339,7 @@ def extract_and_post_process(
|
||||
output_file=output_file,
|
||||
verbose=verbose,
|
||||
cleanup_temp_files=cleanup_temp_files,
|
||||
logger=logger,
|
||||
)
|
||||
|
||||
return output_path, merged_df
|
||||
@@ -321,13 +372,14 @@ def read_order_ids_from_file(id_file: str, encoding: str = "utf-8") -> List[str]
|
||||
|
||||
def extract_from_file(
|
||||
id_file: str,
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
download_dir: str,
|
||||
output_file: str,
|
||||
batch_size: int = 10,
|
||||
verbose: bool = True,
|
||||
cleanup_temp_files: bool = True,
|
||||
logger: Optional[logging.Logger] = None,
|
||||
) -> Tuple[str, pd.DataFrame]:
|
||||
"""
|
||||
Extract data from order IDs in a file and post-process to merged Excel.
|
||||
@@ -341,8 +393,9 @@ def extract_from_file(
|
||||
download_dir: Directory for temporary batch files
|
||||
output_file: Path for final merged Excel output
|
||||
batch_size: Maximum order IDs per batch
|
||||
verbose: Whether to print progress messages
|
||||
verbose: Whether to print progress messages (deprecated, use logger instead)
|
||||
cleanup_temp_files: Whether to delete temporary downloaded files after processing (default: True)
|
||||
logger: Optional logger for debug output. If None and verbose=True, creates default logger.
|
||||
|
||||
Returns:
|
||||
Tuple of (output_file_path, merged_dataframe)
|
||||
@@ -358,8 +411,22 @@ def extract_from_file(
|
||||
"""
|
||||
order_ids = read_order_ids_from_file(id_file)
|
||||
|
||||
if verbose:
|
||||
print(f"Loaded {len(order_ids)} order IDs from {id_file}")
|
||||
# Create default logger if needed (for this function's own logging)
|
||||
func_logger = logger
|
||||
if func_logger is None and verbose:
|
||||
func_logger = logging.getLogger('bipauto.extractor.file')
|
||||
func_logger.setLevel(logging.INFO)
|
||||
if not func_logger.handlers:
|
||||
handler = logging.StreamHandler()
|
||||
handler.setFormatter(logging.Formatter("[%(levelname)s] %(name)s: %(message)s"))
|
||||
func_logger.addHandler(handler)
|
||||
func_logger.propagate = False
|
||||
elif func_logger is None:
|
||||
# Silent mode
|
||||
func_logger = logging.getLogger('bipauto.extractor.file.silent')
|
||||
func_logger.setLevel(logging.CRITICAL + 1)
|
||||
|
||||
func_logger.info(f"Loaded {len(order_ids)} order IDs from {id_file}")
|
||||
|
||||
return extract_and_post_process(
|
||||
work_frame=work_frame,
|
||||
@@ -370,4 +437,5 @@ def extract_from_file(
|
||||
batch_size=batch_size,
|
||||
verbose=verbose,
|
||||
cleanup_temp_files=cleanup_temp_files,
|
||||
logger=logger,
|
||||
)
|
||||
|
||||
@@ -6,17 +6,19 @@ All functions are stateless and accept required parameters explicitly.
|
||||
|
||||
import re
|
||||
import os
|
||||
from typing import List
|
||||
from playwright.sync_api import Page, Frame, TimeoutError
|
||||
import logging
|
||||
from typing import List, Optional
|
||||
from playwright.sync_api import Page, Frame, FrameLocator, TimeoutError
|
||||
|
||||
|
||||
def navigate_to_discrete_material_page(main_frame: Frame, page: Page) -> tuple[Frame, Page]:
|
||||
def navigate_to_discrete_material_page(main_frame: FrameLocator, page: Page, logger: Optional[logging.Logger] = None) -> tuple[FrameLocator, Page]:
|
||||
"""
|
||||
Navigate to the discrete material plan maintenance page.
|
||||
|
||||
Args:
|
||||
main_frame: The main forwardFrame iframe
|
||||
main_frame: The main forwardFrame iframe (FrameLocator)
|
||||
page: The Playwright page object
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
|
||||
Returns:
|
||||
tuple: (work_frame, page1) - The work iframe and the new popup page
|
||||
@@ -36,15 +38,19 @@ def navigate_to_discrete_material_page(main_frame: Frame, page: Page) -> tuple[F
|
||||
inner_frame_locator.wait_for(state="visible", timeout=15000)
|
||||
work_frame = inner_frame_locator.content_frame
|
||||
|
||||
if logger:
|
||||
logger.debug("Navigated to discrete material plan page")
|
||||
|
||||
return work_frame, page1
|
||||
|
||||
|
||||
def setup_query_interface(work_frame: Frame) -> None:
|
||||
def setup_query_interface(work_frame: FrameLocator, logger: Optional[logging.Logger] = None) -> None:
|
||||
"""
|
||||
Initialize the query interface by selecting order number query tab.
|
||||
|
||||
Args:
|
||||
work_frame: The inner work iframe containing the query interface
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
"""
|
||||
# Open search panel
|
||||
work_frame.locator(".search-name-wrapper > .iconfont").click()
|
||||
@@ -60,14 +66,18 @@ def setup_query_interface(work_frame: Frame) -> None:
|
||||
input_box.fill("5000")
|
||||
input_box.press("Enter")
|
||||
|
||||
if logger:
|
||||
logger.debug("Query interface setup complete")
|
||||
|
||||
def fill_and_search_orders(work_frame: Frame, order_ids: List[str]) -> None:
|
||||
|
||||
def fill_and_search_orders(work_frame: FrameLocator, order_ids: List[str], logger: Optional[logging.Logger] = None) -> None:
|
||||
"""
|
||||
Fill order IDs into the search textbox and trigger search.
|
||||
|
||||
Args:
|
||||
work_frame: The work iframe containing the search form
|
||||
order_ids: List of order IDs to search for
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
"""
|
||||
textbox = work_frame.get_by_role("textbox", name="来源生产订单号")
|
||||
|
||||
@@ -84,15 +94,20 @@ def fill_and_search_orders(work_frame: Frame, order_ids: List[str]) -> None:
|
||||
loading_locator.wait_for(state="visible", timeout=3000)
|
||||
loading_locator.wait_for(state="hidden", timeout=0)
|
||||
except TimeoutError:
|
||||
pass
|
||||
if logger:
|
||||
logger.debug("Loading indicator timeout - continuing anyway")
|
||||
|
||||
if logger:
|
||||
logger.debug(f"Searched for {len(order_ids)} order IDs")
|
||||
|
||||
|
||||
def download_batch_data(
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
order_ids: List[str],
|
||||
batch_index: int,
|
||||
download_dir: str
|
||||
download_dir: str,
|
||||
logger: Optional[logging.Logger] = None
|
||||
) -> str:
|
||||
"""
|
||||
Execute the download workflow for a single batch of order IDs.
|
||||
@@ -103,6 +118,7 @@ def download_batch_data(
|
||||
order_ids: List of order IDs to download
|
||||
batch_index: Zero-based batch index for naming the output file
|
||||
download_dir: Directory path to save the downloaded file
|
||||
logger: Optional logger for info output (silent if None)
|
||||
|
||||
Returns:
|
||||
str: Full path to the downloaded file
|
||||
@@ -137,15 +153,19 @@ def download_batch_data(
|
||||
download = download_info.value
|
||||
download.save_as(download_path)
|
||||
|
||||
if logger:
|
||||
logger.info(f"Downloaded batch {batch_index + 1} to {download_path}")
|
||||
|
||||
return download_path
|
||||
|
||||
|
||||
def execute_batch_download_workflow(
|
||||
work_frame: Frame,
|
||||
work_frame: FrameLocator,
|
||||
page: Page,
|
||||
order_ids: List[str],
|
||||
batch_index: int,
|
||||
download_dir: str
|
||||
download_dir: str,
|
||||
logger: Optional[logging.Logger] = None
|
||||
) -> str:
|
||||
"""
|
||||
Complete workflow: fill orders, search, and download for a single batch.
|
||||
@@ -156,9 +176,10 @@ def execute_batch_download_workflow(
|
||||
order_ids: List of order IDs for this batch
|
||||
batch_index: Zero-based batch index for naming the output file
|
||||
download_dir: Directory path to save the downloaded file
|
||||
logger: Optional logger for debug output (silent if None)
|
||||
|
||||
Returns:
|
||||
str: Full path to the downloaded file
|
||||
"""
|
||||
fill_and_search_orders(work_frame, order_ids)
|
||||
return download_batch_data(work_frame, page, order_ids, batch_index, download_dir)
|
||||
fill_and_search_orders(work_frame, order_ids, logger)
|
||||
return download_batch_data(work_frame, page, order_ids, batch_index, download_dir, logger)
|
||||
|
||||
81
utils/logging.py
Normal file
81
utils/logging.py
Normal file
@@ -0,0 +1,81 @@
|
||||
"""
|
||||
Centralized logging utility module for BIPAuto project.
|
||||
|
||||
Provides a standardized logger configuration for consistent logging across
|
||||
all BIPAuto components. Supports console output with optional file logging.
|
||||
|
||||
Basic usage examples:
|
||||
|
||||
# Basic usage - console logging at INFO level
|
||||
from utils.logging import get_logger
|
||||
logger = get_logger('bipauto.auth')
|
||||
logger.info('Login successful')
|
||||
|
||||
# With debug level for detailed output
|
||||
logger = get_logger('bipauto.extractor', level=logging.DEBUG)
|
||||
logger.debug('Processing batch 1 of 5...')
|
||||
|
||||
# With file output for persistent logs
|
||||
logger = get_logger('bipauto.app', level=logging.INFO, log_file='app.log')
|
||||
logger.info('Application started')
|
||||
|
||||
Logger naming convention:
|
||||
Use hierarchical names with 'bipauto.' prefix:
|
||||
- 'bipauto.auth' - Authentication module
|
||||
- 'bipauto.extractor' - Material plan extractor
|
||||
- 'bipauto.converter' - Excel converter
|
||||
- 'bipauto.utils' - Utility functions
|
||||
"""
|
||||
|
||||
import logging
|
||||
from typing import Optional
|
||||
|
||||
|
||||
def get_logger(
|
||||
name: str,
|
||||
level: int = logging.INFO,
|
||||
log_file: Optional[str] = None
|
||||
) -> logging.Logger:
|
||||
"""
|
||||
Create and configure a logger with console and optional file handlers.
|
||||
|
||||
Args:
|
||||
name: Logger name (use hierarchical naming, e.g., 'bipauto.auth')
|
||||
level: Logging level (default: logging.INFO)
|
||||
log_file: Optional path to log file. If None, only console output.
|
||||
|
||||
Returns:
|
||||
Configured logging.Logger instance
|
||||
|
||||
Example:
|
||||
>>> logger = get_logger('bipauto.auth')
|
||||
>>> logger.info('User logged in')
|
||||
[INFO] bipauto.auth: User logged in
|
||||
"""
|
||||
logger = logging.getLogger(name)
|
||||
logger.setLevel(level)
|
||||
|
||||
# Avoid adding duplicate handlers if logger already configured
|
||||
if logger.handlers:
|
||||
return logger
|
||||
|
||||
# Create formatter
|
||||
formatter = logging.Formatter("[%(levelname)s] %(name)s: %(message)s")
|
||||
|
||||
# Console handler (always added)
|
||||
console_handler = logging.StreamHandler()
|
||||
console_handler.setLevel(level)
|
||||
console_handler.setFormatter(formatter)
|
||||
logger.addHandler(console_handler)
|
||||
|
||||
# File handler (optional)
|
||||
if log_file:
|
||||
file_handler = logging.FileHandler(log_file)
|
||||
file_handler.setLevel(level)
|
||||
file_handler.setFormatter(formatter)
|
||||
logger.addHandler(file_handler)
|
||||
|
||||
# Prevent log propagation to root logger (avoids duplicate output)
|
||||
logger.propagate = False
|
||||
|
||||
return logger
|
||||
Reference in New Issue
Block a user