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Automation Utilities

PDF Invoice Conversion & eBay Reconciliation Toolkit

Document ETL toolkit that extracts structured invoice data from PDF files, converts it into clean workbook and CSV outputs, and supports reconciliation against eBay transaction records.

PythonpdfplumberRegexExcelPandasReconciliationDocument ETL

Document ETL command view

PDF Invoice Conversion & eBay Reconciliation Toolkit

Invoice PDF extraction, table cleanup, master CSV creation, and eBay reconciliation workbook delivery

conversion-ready
01

Collect

PDF / eBay Files

02

Extract

Tables / Regex

03

Normalize

Clean / Shape

04

Reconcile

Match / Review

05

Publish

CSV / Workbook

Extraction checks

Parse / Clean / Match
PDF table extraction
Regex fallback
Credit memo cleanup
Header normalization
Master CSV output
eBay reconciliation

Output signals

Review preview
Invoices parsed128

Structured extraction with fallback handling

Credits flagged22

Credit memo separation for cleanup review

Reconciled rows684

Aligned for downstream eBay matching

Exceptions31

Rows held for manual review and validation

Delivered outputs

Per-PDF WorkbookMaster CSVClean Invoice OutputCredit Memo ReviewReconciliation WorkbookException Queue
PDF-to-Table
Structured extraction mode
Reconciled
Invoice-to-eBay review flow
Workbook-ready
Operational output format

Business problem

Invoice PDFs and eBay transaction exports required manual extraction, manual cleanup, and repeated matching work. The raw documents were difficult to reuse directly because tables were not always clean, layouts could vary, and credit memo behavior often needed special handling.

The process needed a more reliable bridge between document files and usable operational data. Instead of copy/paste and workbook-by-workbook cleanup, the workflow needed structured parsing, cleanup logic, and outputs designed for reconciliation and follow-up review.

System built

Built pdfplumber parsing, regex fallback, cleanup logic, per-PDF workbook generation, master CSV outputs, and reconciliation workbook creation for invoice and eBay review workflows.

The toolkit turns semi-structured PDF invoices into cleaner tabular outputs, then pushes those outputs into a more practical financial and operational review flow. That makes the data easier to validate, easier to reconcile, and easier to reuse later.

Review controls

Signals reviewed

The toolkit checks document structure, extraction quality, cleanup behavior, reconciliation readiness, and workbook completeness so the output can support both operational processing and audit review.

Invoice PDF intake
Credit memo detection
pdfplumber table extraction
Regex fallback parsing
Line cleanup and normalization
Per-document workbook creation
Master CSV assembly
eBay transaction matching
Reconciliation exception review
Credit / debit separation
Operational workbook packaging
Audit-ready output structure

Processing workflow

How it works

01

Collect

Gather invoice PDFs, source folders, and supporting eBay transaction exports into one controlled intake flow.

The process starts with structured input handling so invoice documents and reconciliation references can be processed consistently instead of manually opened one by one.

02

Extract

Read invoice tables from PDF files with pdfplumber and fallback patterns when the layout is less reliable.

Extraction is designed to work across inconsistent PDF layouts by combining structured table parsing with regex-based backup logic.

03

Normalize

Clean invoice rows, standardize values, separate credits, and shape line items into reliable tabular records.

Normalization turns raw document text into something usable for downstream workbooks, master CSV outputs, and reconciliation review.

04

Reconcile

Compare the extracted invoice data against eBay-related transaction records to surface aligned and exception cases.

Instead of treating invoice conversion as a standalone task, the system pushes the data into a financial review flow that makes matching and exception handling easier.

05

Publish

Generate per-PDF workbooks, master CSV outputs, and reconciliation-friendly workbook artifacts for review.

Outputs are organized to support operational use, manual validation, and easier handoff to stakeholders.

System layers

What the toolkit coordinates

Document intake

Collects invoice PDFs and supporting transaction files into a repeatable starting point for extraction and review.

Parsing engine

Uses pdfplumber table extraction plus regex fallback logic to deal with mixed or imperfect invoice layouts.

Cleanup layer

Standardizes values, separates credit memo behavior, and reshapes the raw lines into cleaner analytical records.

Reconciliation output

Pushes converted invoice data into workbooks and CSV outputs that support eBay matching, exception review, and reporting.

Impact signals

What the workflow improved

PDF table extraction turned into structured rows

Invoice and credit memo cleanup in one workflow

Master CSV generation for downstream review

eBay reconciliation-ready outputs

Cleaner handoff from documents to usable data

Operational value

From document cleanup to usable reconciliation outputs

Less manual extraction

Reduces the need to manually retype or inspect invoice data line by line from PDF files.

Better data quality

Applies cleanup and fallback parsing so outputs are more reliable than one-off copy/paste methods.

Stronger reconciliation

Brings invoice conversion and eBay review into the same system, making it easier to spot mismatches and exceptions.

Reusable outputs

Creates per-document workbooks and master files that are easier to audit, share, and reuse later.

Why this project matters

PDF invoices become more valuable when they are converted into clean, reviewable data instead of remaining trapped in document form.

This project shows how a document-heavy workflow can be turned into a repeatable data operation. PDF parsing, fallback extraction, cleanup logic, and structured output generation all work together to reduce manual effort and improve reliability.

The eBay reconciliation layer adds even more value because the result is not only converted data, but data that can support downstream financial review, exception handling, and decision-making.

Confidentiality note

Visuals and descriptions are sanitized conceptual representations. They do not expose private company data, raw invoice PDFs, customer records, eBay exports, account details, operational screenshots, proprietary workbook formulas, or source-document contents.