A python-based pcb design project full-cycle automatic management method and system

Abstract

The application relates to the field of PCB design, and discloses a Python-based PCB design project full-cycle automatic management method and system, which comprises the following steps: S1, project scanning and indexing: traversing the folder under a working path, analyzing a project metadata file, and establishing an in-memory index list according to a pinned state and a time attribute; in the application, specific suffix files under a GERBER directory and timestamp information under a PCB directory are automatically scanned in the background, a project stage is reversely deduced in real time by using an automatic state machine logic, the management efficiency during multi-project parallel development is significantly improved, and the risk of a serious accident of misdelivering an unfinished design file to production is effectively eliminated; meanwhile, an intelligent incremental archiving mechanism based on a time dimension is constructed, a version date feature in a source file name is intelligently parsed by using a regular expression, and archiving is automatically replaced, so that each major modification can be traced, and the risk of file loss caused by misoperation is reduced.

Description

Technical Field

[0001] This invention relates to the field of PCB design, and in particular to a Python-based method and system for automating the entire lifecycle of PCB design projects. Background Technology

[0002] In the field of electronic hardware R&D, PCB design is a complex and frequently iterated engineering activity. The conventional design process relies on EDA software for schematic drawing and layout routing, while also requiring the review and verification of DXF structure files and Gerber project files. However, in the file management and project collaboration aspects outside of EDA software, the current approach mainly relies on manual management based on the operating system. Designers directly use Windows Explorer to create, copy, and rename folders, manually create standard subdirectories such as DSN, PCB, and Gerber, copy and rename PCB design files daily, continue designing, and manually edit and save changes. They also need to open Gerber or DXF viewers to check manufacturing and structural data. Although some companies use general version control systems such as SVN, Git, or PLM, managing the large number of binary files and intermediate process files generated in PCB design is too cumbersome and lacks intuitive display of the characteristics of PCB design. The above-mentioned existing technologies have the following drawbacks: File archiving relies on manual processes, which carries a high risk of version overwrite. Engineers may easily forget to back up their files and directly modify the source files, or enter the wrong date suffix when manually renaming them, making it impossible to trace back to previous versions. Design status perception is lagging, multi-project management is chaotic, folders cannot intuitively show the stage of the project, engineers need to check the modification time of each file one by one, which can easily confuse the production status or even mistakenly send incomplete project files to production. Design logs are disconnected from process assets. Traditional Txt or Excel recording methods with screenshots are cumbersome, causing engineers to give up recording details and making it impossible to review design ideas later. The project directory structure is not standardized, with different engineers naming things arbitrarily, making team collaboration and retrieval difficult and not conducive to automation. Manufacturing documents and structural documents need to be viewed separately using external tools. Frequent software switching can easily lead to missed anomalies, reduce verification efficiency, and increase the risk of production errors.

[0003] In summary, existing technologies lack a lightweight desktop auxiliary system that is optimized for PCB design characteristics and integrates automated version control, multimedia log management, and Gerber / DXF preview. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a Python-based method and system for automating the entire lifecycle of PCB design projects, thus solving the aforementioned problems.

[0005] To achieve the above objectives, this invention provides the following technical solution: a Python-based method for fully automated management of the entire lifecycle of PCB design projects, comprising the following steps: S1. Project Scanning and Indexing: Traverse the folders under the working path, parse the project metadata files, and build a project memory index list based on the pinned status and time attributes. S2. Automatic Status Detection: In response to the user's selection of the target project, the background automatically scans the production file directory and design source file directory under the project. Based on the regular expression characteristics of the file name and the modification timestamp, it determines whether the project is in the state of "drawings completed" or "design in progress" and updates the visual status indicator. S3, Standardized Library Creation: In response to the creation command, based on the preset list of folder templates, it generates a project directory with a standard hierarchical structure on the physical disk and initializes the project metadata; S4 Smart Archiving: Responding to archiving commands, it traces back to the historical date directory to lock the latest PCB source file, uses regular expressions to parse the version date characteristics in the file name, replaces it with the current date, and then copies it to the newly created backup directory; S5, Multimedia Log Management: Receives text and clipboard image stream input from users, generates image and text logs, and calculates and physically deletes unreferenced orphaned image files based on the differences in the image reference list before and after the log update. S6, Panel Analysis and Vector Rendering: Responding to drawing preview commands, extracting and detecting file features in preset product subdirectories to achieve automatic classification of layer functions, using an MD5 verification fingerprint system based on single-layer and merged features to manage buffer resources generated by the dual-engine vector graphics pipeline, and in parallel restoring the multi-polar rendering overlay view containing corrected inverted code defects in the interactive scene outside the separate main program. S7. Structural Measurement and Analysis: Start the decoding thread of the inline structure to deeply scan the graphics set, call the state machine that avoids closed references to perform coordinate translation and dimensionality reduction expansion of mechanical parts and their sub-references, and perform cross-layer ranging in the scene with adsorption factors.

[0006] Preferably, the S2 state automatic sensing step specifically includes: S21. First scan the production file directory and use regular expressions to match whether there is a final file with a specific suffix, -LAST.brd. If it exists, it is determined that the image has been generated. S22. If no match is found, scan the design source file directory, traverse the date subfolders in reverse chronological order, extract the modification time of the latest .brd format source file, determine that it is under design, and display the progress details.

[0007] Preferably, the S4 intelligent archiving step specifically includes: S41. Obtain the current system date string; S42. Traverse the historical date folders excluding today's date and locate the most recent working directory as the source directory; S43. Locate the .brd file with the latest modification time in the source directory and use regular expressions to match its filename; if a date format suffix is ​​matched, replace the original date suffix with the current date string to generate a new filename; if no match is found, add the current date prefix to generate a new filename; S44. Call the system file operation interface to copy the source file and rename it to today's backup directory.

[0008] Preferably, in the S5 multimedia log management step, the physical deletion of unreferenced isolated image files includes: obtaining the original image file name set A before editing; obtaining the existing image file name set B after editing submission; calculating the difference (AB) between set A and set B to obtain the list of images to be deleted; traversing the list of images to be deleted, constructing absolute paths, and performing file system deletion operations.

[0009] Preferably, the S6 PCB fabrication and vector rendering steps specifically include: S61. Automatically classify the physical types of the bottom layer, top layer, and borehole layer based on the file name extension and text characteristics; S62. Construct a unified maximum margin alignment box, schedule multi-core processes to translate and deliver the light plotting trajectory to the alignment box, and combine it with SVG vector layer or parallel bit layer. S63. Establish a security screener to find coordinate mirroring issues caused by differences in the original software, and introduce negative scaling and offset matrices at the SVG level to forcibly correct them; for special files with multi-level negative polarity regions, inject color channel mixing masks in the final process of image merging to remove conflicting black spots. S64: The main control unit uses Python to create multi-level temporary storage areas across platforms and uses MD5 fingerprints to determine the validity of the current file's generation. It schedules an external Qt independent process through the operating system console to complete parameter pass-through, preventing complex graphical matrices from damaging the performance and security of the original monitoring project.

[0010] Preferably, the S7 structure measurement and analysis step specifically includes: S71. When reading a DXF dataset containing binary and various non-standard character encodings, a downgrade decoding retry anti-blackening protection mechanism is applied; and a plain text extraction algorithm is started to establish a top-down multi-line combination logic to sequentially identify HEADER, TABLES, BLOCKS to ENTITIES. S72. When processing the mosaic layers contained in the tile, apply depth isolation, extract the scale and orientation angle, and then restore the actual X / Y of the vector node to the physical coordinates; at the same time, repair the convexity omission and coordinate missing problems caused by polyline extraction. S73. The main thread crashes due to continuous high-speed dragging of the user mouse in the generation of visualization drawing application layer proxy anti-aliasing architecture buffer. S74 captures the coordinate system difference between the mouse and grid nodes and provides it to the size conversion algorithm attached to the cursor. It supports the straight-line distance arbitrarily selected from two base points and calculation based on the X-axis and Y-axis. It also converts the extracted graphic element metric and imperial attributes back to a unified standard for intuitive calculation of the redundancy of the plate size.

[0011] A Python-based automated management system for the entire lifecycle of PCB design projects, comprising: Configuration management module: used to load local JSON configuration files and initialize global color schemes; UI rendering module: Builds interactive interfaces based on the GUI framework, dynamically rendering the project card list and details panel; The core logic processing module is used to perform project scanning, status awareness, intelligent archiving, multimedia log management, PCB layout parsing and vector rendering, and structural measurement and analysis logic. Data persistence module: Used to serialize and store project status changes, log records, and system configurations to a local JSON database.

[0012] Preferably, the UI rendering module is built on the Flet framework and includes: a ListView component for displaying projects, a Dropdown component for path selection, a right-side details panel container, a status card component, and a log list component; the system listens for user clicks on project cards, triggers a project selection function, updates the selected project path in the global status dictionary, highlights the current card, and sequentially calls the update title, update status, and update log functions to refresh the right-side details panel.

[0013] Preferably, the intelligent archiving module in the core logic processing module further includes: The regular expression parsing unit is used to match date version features in the source file name and extract the file name header, old date, and version suffix. The date replacement unit is used to replace the matched old date with the current date string, generating a new filename that conforms to the standard format. The fallback naming unit is used to generate a new filename by adding the current date prefix when a regular expression match fails.

[0014] Preferably, the PCB layout analysis and vector rendering module in the core logic processing module further includes: The engine detection and degradation unit is used to detect the high-performance vector rendering engine Gerbonara by default. If the detection fails, it will smoothly downgrade to the PyGerber raster engine. The MIA mirror repair unit is used to scan the original file for mirror declarations before rendering using regular expression analysis, and to perform underlying coordinate system mirror repair using matrix transformations at the SVG level after rendering. Multi-level caching units are used to establish MD5 hash fingerprints based on modification timestamps as cache verification keys, and to establish single-layer pre-rendering cache, multi-layer merging result cache and SVG renderer memory cache respectively; The process isolation unit is used to create an independent Qt high-performance preview process through subprocess, which is physically isolated from the main GUI application in memory and provides independent layer visibility control, transparency overlay, dynamic color mapping and light and dark view switching functions.

[0015] This invention provides a Python-based method and system for automating the entire lifecycle management of PCB design projects. Compared with existing technologies, it has the following advantages: In this invention, by automatically scanning files with specific extensions in the GERBER directory and timestamp information in the PCB directory in the background, the system uses automated state machine logic to back-calculate the project's current stage in real time. This not only significantly improves management efficiency during parallel development of multiple projects but also effectively eliminates the serious risk of accidentally sending unfinished design files to production. Simultaneously, this invention constructs an intelligent incremental archiving mechanism based on the time dimension. It uses regular expressions to intelligently parse the version date features in the source filenames and automatically replaces the archives, ensuring that every major modification is traceable and reducing the risk of file loss due to misoperation. Furthermore, the system automatically identifies and physically deletes no longer-used image files through set difference operations, ensuring both the richness and traceability of the design log and avoiding the accumulation of junk files caused by long-term operation, achieving lightweight and efficient management. 2. In this invention, regarding Gerber preview, by automatically detecting drawing categories with one click, applying a seamless downgraded dual-channel rendering engine with a built-in MIA multi-polarity inverted code correction algorithm, combined with a multi-level offline cache pool based on MD5 file fingerprints and an independent external Qt rendering pipeline, not only is the main system lag caused by the analysis of large-scale boards completely avoided, but also the second-level custom smooth scaling and multi-layer overlay rendering under dark filters are achieved, greatly reshaping the seamlessness between the output graphics and the original wiring. In addition, regarding DXF preview, anti-self-referencing matrix scaling and rotation translation coordinate reconstruction transformation is performed on high-rise buildings with embedded loop structures, supplemented by a high-speed bitmap proxy buffer system during dragging, giving the 2D measurement module an excellent capture experience and the ability to directly convert the drawing into physical structure values. Attached Figure Description

[0016] Figure 1 This is the overall logic flowchart of the present invention; Figure 2 This is a flowchart of the PCB design status automatic sensing logic of the present invention; Figure 3 This is a flowchart of the intelligent incremental archiving logic of the present invention; Figure 4 This is a flowchart illustrating the logic for maintaining multimedia log and resource consistency in this invention. Figure 5 This is a flowchart of the Gerber file preview and multi-layer overlay rendering module of the present invention; Figure 6 This is a flowchart of the DXF structure preview and interactive measurement module of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figures 1-6 The present invention provides two technical solutions, specifically including the following embodiments:

[0019] Example 1: A Python-based method for automating the entire lifecycle of PCB design projects, comprising the following steps: S1. Project Scanning and Indexing: Traverse the folders under the working path, parse the project metadata files, and build a project memory index list based on the pinned status and time attributes. S2. Automatic Status Detection: In response to the user's selection of a target project, the background automatically scans the production file directory and design source file directory under that project. Based on the regular expression characteristics of the filenames and the modification timestamp, it determines whether the project is in the "drawing completed" or "design in progress" state and updates the visual status indicator. The S2 automatic status detection steps specifically include: S21. First scan the production file directory and use regular expressions to match whether there is a final file with a specific suffix, -LAST.brd. If it exists, it is determined that the image has been generated. S22. If no match is found, scan the design source file directory, traverse the date subfolder in reverse chronological order, extract the modification time of the latest .brd format source file, determine that it is under design, and display the progress details; S3, Standardized Library Creation: In response to the creation command, based on the preset list of folder templates, it generates a project directory with a standard hierarchical structure on the physical disk and initializes the project metadata; S4 Smart Archiving: Responding to archiving commands, it traces back through historical date directories to locate the latest PCB source file, uses regular expressions to parse the version date characteristics in the filename, replaces them with the current date, and then copies them to a newly created backup directory. The specific steps of S4 Smart Archiving include: S41. Obtain the current system date string; S42. Traverse the historical date folders excluding today's date and locate the most recent working directory as the source directory; S43. Locate the .brd file with the latest modification time in the source directory and use regular expressions to match its filename; if a date format suffix is ​​matched, replace the original date suffix with the current date string to generate a new filename; if no match is found, add the current date prefix to generate a new filename; S44. Call the system file operation interface to copy the source file and rename it to today's backup directory; S5 Multimedia Log Management: Receives text and clipboard image stream input from the user, generates a text and image log, and calculates and physically deletes unreferenced orphaned image files based on the difference in the image reference list before and after the log update. The physical deletion of unreferenced orphaned image files in the S5 multimedia log management steps includes: obtaining the original image filename set A before editing; obtaining the existing image filename set B after editing submission; calculating the difference (AB) between set A and set B to obtain the list of images to be deleted; traversing the list of images to be deleted, constructing absolute paths, and performing file system deletion operations. S6, Plate Making Analysis and Vector Rendering: Responding to drawing preview commands, it extracts and detects file characteristics in preset product subdirectories to achieve automatic layer classification. It uses an MD5 verification fingerprint system based on single-layer and merged features to manage buffer resources generated by the dual-engine vector graphics pipeline. Furthermore, it parallelly restores a multi-polar rendering overlay view containing corrected inverted code defects in an interactive scene outside the separate main program. The specific steps of S6 Plate Making Analysis and Vector Rendering include: S61. Automatically classify the physical types of the bottom layer, top layer, and borehole layer based on the file name extension and text characteristics; S62. Construct a unified maximum margin alignment box, schedule multi-core processes to translate and deliver the light plotting trajectory to the alignment box, and combine it with SVG vector layer or parallel bit layer. S63. Establish a security screener to find coordinate mirroring issues caused by differences in the original software, and introduce negative scaling and offset matrices at the SVG level to forcibly correct them; for special files with multi-level negative polarity regions, inject color channel mixing masks in the final process of image merging to remove conflicting black spots. S64: The main control terminal uses Python to create multi-level temporary storage areas across platforms and uses MD5 fingerprints to determine the validity of the current file's generation. It schedules an external Qt independent process through the operating system console to complete parameter pass-through, preventing complex graphical matrices from damaging the performance and security of the original monitoring project. S7. Structural Measurement and Analysis: The decoding thread for the inline structure is initiated to perform a deep scan of the graphics set. A state machine that avoids enclosing references is invoked to perform coordinate translation and dimensionality reduction expansion on the mechanical parts and their sub-references. In scenes with adsorption factors, cross-layer ranging is implemented. The specific steps of S7 structural measurement and analysis include: S71. When reading a DXF dataset containing binary and various non-standard character encodings, a downgrade decoding retry anti-blackening protection mechanism is applied; and a plain text extraction algorithm is started to establish a top-down multi-line combination logic to sequentially identify HEADER, TABLES, BLOCKS to ENTITIES. S72. When processing the mosaic layers contained in the tile, apply depth isolation, extract the scale and orientation angle, and then restore the actual X / Y of the vector node to the physical coordinates; at the same time, repair the convexity omission and coordinate missing problems caused by polyline extraction. S73. The main thread crashes due to continuous high-speed dragging of the user mouse in the generation of visualization drawing application layer proxy anti-aliasing architecture buffer. S74 captures the coordinate system difference between the mouse and grid nodes and provides it to the size conversion algorithm attached to the cursor. It supports the straight-line distance arbitrarily selected from two base points and calculation based on the X-axis and Y-axis. It also converts the extracted graphic element metric and imperial attributes back to a unified standard for intuitive calculation of the redundancy of the plate size.

[0020] A Python-based automated management system for the entire lifecycle of PCB design projects, comprising: Configuration management module: used to load local JSON configuration files and initialize global color schemes; The UI rendering module is built on a GUI framework to create an interactive interface that dynamically renders the project card list and details panel. It includes a ListView component for displaying projects, a Dropdown component for path selection, a right-side details panel container, a status card component, and a log list component. The system listens for user clicks on project cards, triggers a project selection function, updates the selected project path in the global status dictionary, highlights the current card, and sequentially calls the update title, update status, and update log functions to refresh the right-side details panel. The core logic processing module is used to perform project scanning, status awareness, intelligent archiving, multimedia log management, PCB layout parsing and vector rendering, and structural measurement and analysis logic. The intelligent archiving module within the core logic processing module also includes: The regular expression parsing unit matches date version features in the source filename, extracting the filename header, old date, and version suffix. The date replacement unit replaces the matched old date with the current date string, generating a new, standardized filename. The fallback naming unit uses a backup naming strategy, adding the current date prefix, to generate a new filename when regular expression matching fails. The data persistence module serializes and stores project status changes, log records, and system configurations to a local JSON database. The slab parsing and vector rendering modules in the core logic processing module also include an engine detection and degradation unit, which detects the high-performance vector rendering engine Gerbonara by default and smoothly downgrades it if identification fails. Upgraded to the PyGerber raster engine; the MIA mirror repair unit is used to scan the original file for mirror declarations using regular expression analysis before rendering, and to perform underlying coordinate system mirror repair using matrix transformations at the SVG level after rendering; the multi-level caching unit is used to establish an MD5 hash fingerprint based on the modification timestamp as a cache verification key, and to establish a single-layer pre-rendering cache, a multi-layer merging result cache, and an SVG renderer memory cache respectively; the process isolation unit is used to create an independent Qt high-performance preview process through subprocess, achieving physical memory isolation from the main GUI application, and providing independent layer visibility control, transparency overlay, dynamic color mapping, and light and dark view switching functions.

[0021] Example 2: Based on Example 1, this example uses specific verification data, test scenarios, and actual operating results to verify the feasibility of the technical solution described in Example 1 and provide a detailed explanation. In a test path containing 500 project folders, the system completed a full scan and correctly built the memory index within 1.2 seconds. Valid metadata items were parsed accurately, and corrupted metadata was abnormally captured without interrupting the process. In the automatic status awareness test, projects in the GERBER directory containing files with the -LAST.brd suffix were correctly identified as having been drawn (green), and projects in the PCB directory containing date subfolders and the latest .brd source file were correctly identified as being under design (orange). Empty directory items were displayed as having no files, and the status switching response latency was less than 0.1 seconds. During standardized library construction, the system correctly generated a standard hierarchical structure containing CANKAO, DSN, DXF, GERBER, LIB, NET, PCB, and data based on a preset template list. In the PCB directory, a subfolder for the current date is automatically generated, and the metadata file is fully initialized. In the intelligent archiving test, when MainBoard-0309A.brd is archived, the regular expression successfully parses the header, old date, and version suffix, generating MainBoard-0703A.brd. The date is replaced while the version suffix is ​​retained, and the file content and timestamp are completely copied. For Legacy.brd that does not match the regular expression, BACKUP_0703_Legacy.brd is generated as a fallback. When editing multimedia logs, the system performs a difference operation on the image reference sets before and after editing, accurately identifies and physically deletes isolated images, and new screenshots are correctly persisted from the temporary directory to the resource directory. The metadata is updated without errors, and there is no redundant residue on the disk. This embodiment further verifies the rendering parsing and system stability: For the Gerber file set of a 6-layer PCB, the system automatically categorizes copper foil, solder mask, silkscreen, and drill layers according to file extensions and keyword features, with accurate classification; for files containing the %MIA*% mirror command, a scale(-1, 1) matrix transformation is injected after rendering, and the deviation between the graphic and the original trace is less than 0.01mm; multi-level caching based on MD5 fingerprints reduces the time for repeated loading from 8 seconds to 0.3 seconds, and the cache is automatically invalidated after file modification; the Qt independent process created by subprocess is isolated from the main program memory, and the layer showing / hiding and transparency operations are smooth without crashes. For DXF files containing 3-layer nested INSERT statements, Chinese comments, and missing convexity attributes, the system prioritizes UTF-8 decoding and then reverts to GBK if decoding fails, ensuring correct display of Chinese characters. For LWPOLYLINE vertices missing 42 sets of codes, zero-filling is automatically performed, and closed curves show no abnormal polygonal lines. Blocks with a 30° rotation angle and a 1.2 scale undergo affine transformation to achieve coordinates consistent with AutoCAD, with a deviation of less than 0.001mm. The measurement function automatically converts inches to millimeters, providing accurate results. The system ran continuously for 72 hours, performing over 500 operations, with memory usage remaining stable between 150MB and 200MB without leakage. After forced termination and restart, the data was complete with no residual dirty data.

[0022] Conclusion: This system can achieve efficient and stable operation in complex multi-project parallel development environments: the project scanning and indexing module can complete the traversal and memory indexing of 500 project folders within 1.2 seconds; the automatic status perception module achieves 100% accuracy in determining the two statuses of output drawings and design in progress, with a response latency of less than 0.1 seconds; the intelligent archiving module achieves intelligent replacement of filename date versions through regular expression parsing, taking into account both standardized naming and fallback strategies, and there is no risk of file loss or overwriting during archiving operations; the isolated resource cleanup mechanism of the multimedia log management module ensures no redundant disk space residue, and clipboard image stream processing is smooth and stable; the automatic layer classification, MIA image repair, and multi-level caching mechanism of the Gerber preview module improve the efficiency of repeated loading by approximately 96.7%; the self-developed state machine of the DXF parsing module achieves accurate rendering and measurement of complex files containing nested references, encoding anomalies, and missing attributes, with coordinate deviation controlled within 0.001mm. The system ran continuously for 72 hours without memory leaks, and after abnormal termination, the data was complete with no dirty data residue. The overall performance meets the engineering requirements for automated management of the entire PCB design process.

[0023] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A Python-based method for automating the entire lifecycle of PCB design projects, characterized by: Includes the following steps: S1. Project Scanning and Indexing: Traverse the folders under the working path, parse the project metadata files, and build a project memory index list based on the pinned status and time attributes. S2. Automatic Status Detection: In response to the user's selection of a target project, the background automatically scans the production file directory and design source file directory under the project. Based on the regular expression characteristics of the file name and the modification timestamp, it determines whether the project is in the state of "drawings completed" or "design in progress" and updates the visual status indicator. S3, Standardized Library Creation: In response to the creation command, based on the preset list of folder templates, it generates a project directory with a standard hierarchical structure on the physical disk and initializes the project metadata; S4 Smart Archiving: Responding to archiving commands, it traces back to the historical date directory to lock the latest PCB source file, uses regular expressions to parse the version date characteristics in the file name, replaces it with the current date, and then copies it to the newly created backup directory; S5, Multimedia Log Management: Receives text and clipboard image stream input from users, generates image and text logs, and calculates and physically deletes unreferenced orphaned image files based on the differences in the image reference list before and after the log update. S6. Plate Making Analysis and Vector Rendering: Responding to drawing preview commands, extracting and detecting file features in preset product subdirectories to achieve automatic layer classification, using an MD5 verification fingerprint system based on single-layer and merged features to manage buffer resources generated by the dual-engine vector graphics pipeline, and in parallel restoring a multi-polar rendering overlay view containing corrected inverted code defects in an interactive scene outside the separate main program. The S6 plate making analysis and vector rendering steps specifically include: S61. Automatically classify the physical types of the bottom layer, top layer, and borehole layer based on the file name extension and text characteristics; S62. Construct a unified maximum margin alignment box, schedule multi-core processes to translate and deliver the light plotting trajectory to the alignment box, and combine it with SVG vector layer or parallel bit layer. S63. Establish a security screener to find coordinate mirroring issues caused by differences in the original software, and introduce negative scaling and offset matrices at the SVG level to forcibly correct them; for special files with multi-level negative polarity regions, inject color channel mixing masks in the final process of image merging to remove conflicting black spots. S64: The main control unit uses Python to create multi-level temporary storage areas across platforms and uses MD5 fingerprints to determine the validity of the current file's generation. It also uses the operating system console to schedule an external Qt independent process to complete parameter pass-through, preventing complex graphical matrices from damaging the performance and security of the original monitoring project. S7. Structural Measurement and Analysis: Start the decoding thread of the inline structure to deeply scan the graphics set, call the state machine that avoids closed references to perform coordinate translation and dimensionality reduction expansion of mechanical parts and their sub-references, and perform cross-layer ranging in the scene with adsorption factors.

2. The method for automated management of the entire lifecycle of PCB design projects based on Python, as described in claim 1, is characterized in that: The S2 state automatic sensing step specifically includes: S21. First scan the production file directory and use regular expressions to match whether there is a final file with a specific suffix, -LAST.brd. If it exists, it is determined that the image has been generated. S22. If no match is found, scan the design source file directory, traverse the date subfolders in reverse chronological order, extract the modification time of the latest .brd format source file, determine that it is under design, and display the progress details.

3. The method for automated management of the entire lifecycle of PCB design projects based on Python, as described in claim 1, is characterized in that: The S4 intelligent archiving steps specifically include: S41. Obtain the current system date string; S42. Traverse the historical date folders excluding today's date and locate the most recent working directory as the source directory; S43. Locate the .brd file with the latest modification time in the source directory and use regular expressions to match its filename; if a date format suffix is ​​matched, replace the original date suffix with the current date string to generate a new filename; if no match is found, add the current date prefix to generate a new filename; S44. Call the system file operation interface to copy the source file and rename it to today's backup directory.

4. The method for automated management of the entire lifecycle of PCB design projects based on Python, as described in claim 1, is characterized in that: In the S5 multimedia log management steps, the physical deletion of unreferenced orphaned image files includes: obtaining the original image file name set A before editing; obtaining the existing image file name set B after editing submission; calculating the difference (AB) between set A and set B to obtain the list of images to be deleted; traversing the list of images to be deleted, constructing absolute paths, and performing file system deletion operations.

5. The method for automated management of the entire lifecycle of PCB design projects based on Python according to claim 1, characterized in that: The S7 structure measurement and analysis steps specifically include: S71. When reading a DXF dataset containing binary and various non-standard character encodings, a downgrade decoding retry anti-blackening protection mechanism is applied; and a plain text extraction algorithm is started to establish a top-down multi-line combination logic to sequentially identify HEADER, TABLES, BLOCKS to ENTITIES. S72. When processing the mosaic layers contained in the tile, apply depth isolation, extract the scale and orientation angle, and then restore the actual X / Y of the vector node to the physical coordinates; at the same time, repair the convexity omission and coordinate missing problems caused by polyline extraction. S73. The main thread crashes due to continuous high-speed dragging of the user mouse in the generation of visualization drawing application layer proxy anti-aliasing architecture buffer. S74 captures the coordinate system difference between the mouse and grid nodes and provides it to the size conversion algorithm attached to the cursor. It supports the straight-line distance arbitrarily selected from two base points and calculation based on the X-axis and Y-axis. It also converts the extracted graphic element metric and imperial attributes back to a unified standard for intuitive calculation of the redundancy of the plate size.

6. A Python-based automated management system for the entire lifecycle of PCB design projects, based on the Python-based automated management method for the entire lifecycle of PCB design projects as described in any one of claims 1-5, characterized in that: include: Configuration management module: used to load local JSON configuration files and initialize global color schemes; UI rendering module: Builds interactive interfaces based on the GUI framework, dynamically rendering the project card list and details panel; The core logic processing module is used to perform project scanning, status awareness, intelligent archiving, multimedia log management, PCB layout parsing and vector rendering, and structural measurement and analysis logic. Data persistence module: Used to serialize and store project status changes, log records, and system configurations to a local JSON database.

7. The Python-based PCB design project lifecycle automated management system according to claim 6, characterized in that: The UI rendering module is built on the Flet framework and includes: a ListView component for displaying projects, a Dropdown component for path selection, a right-side details panel container, a status card component, and a log list component. The system listens for user clicks on project cards, triggers a project selection function, updates the selected project path in the global status dictionary, highlights the current card, and sequentially calls the update title, update status, and update log functions to refresh the right-side details panel.

8. The PCB design project lifecycle automation management system based on Python according to claim 6, characterized in that: The intelligent archiving module in the core logic processing module also includes: The regular expression parsing unit is used to match date version features in the source file name and extract the file name header, old date, and version suffix. The date replacement unit is used to replace the matched old date with the current date string, generating a new filename that conforms to the standard format. The fallback naming unit is used to generate a new filename by adding the current date prefix when a regular expression match fails.

9. The PCB design project lifecycle automation management system based on Python according to claim 6, characterized in that: The PCB analysis and vector rendering module in the core logic processing module also includes: The engine detection and degradation unit is used to detect the high-performance vector rendering engine Gerbonara by default. If the detection fails, it will smoothly downgrade to the PyGerber raster engine. The MIA mirror repair unit is used to scan the original file for mirror declarations before rendering using regular expression analysis, and to perform underlying coordinate system mirror repair using matrix transformations at the SVG level after rendering. Multi-level caching units are used to establish MD5 hash fingerprints based on modification timestamps as cache verification keys, and to establish single-layer pre-rendering cache, multi-layer merging result cache and SVG renderer memory cache respectively; The process isolation unit is used to create an independent Qt high-performance preview process through subprocess, which is physically isolated from the main GUI application in memory and provides independent layer visibility control, transparency overlay, dynamic color mapping and light and dark view switching functions.

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