pystdf4 0.1.2

A Python library for reading and writing STDF4 files

📦 PyStdf4

PyStdf4 is a modern, high-performance Python library for creating and parsing STDF (Standard Test Data Format) v4 files, widely used in semiconductor testing and manufacturing.

It provides a clean, Pythonic interface that abstracts low-level binary handling, letting engineers focus on data modeling instead of byte-level details.

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🔍 Overview

With PyStdf4, you can efficiently:

• Generate STDF v4 files using structured Python objects
• Build records with a robust, extensible field/record system
• Work with a high-performance dynamic byte buffer optimized for large datasets
• Integrate seamlessly into automated test and analysis pipelines

⚠️ STDF file parsing (reader API) is under active development.

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🧪 Example Usage

Installation

python -m pip install pystdf4

Writing an STDF v4 file

import time
from pystdf4 import Stdf4Writer

with Stdf4Writer('example.stdf') as stdf:
    # File Attributes Record
    stdf.FAR(CPU_TYPE=2, STDF_VER=4)

    # Master Information Record
    stdf.MIR(
        SETUP_T=int(time.time()),
        START_T=int(time.time()),
        STAT_NUM=0,
        BURN_TIM=0,
        LOT_ID="Example Lot",
        JOB_NAM="Example Job",
        PART_TYP="",
        NODE_NAM="",
        TSTR_TYP="",
    )

    # Add other records here...

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📋 STDF Record Implementation Status

Record	Type	Sub	Status	Notes
FAR	0	10	✔️ Complete	Required first record
ATR	0	20	✔️ Complete	Audit trail
MIR	1	10	✔️ Complete	Lot-level info
MRR	1	20	✔️ Complete	End of lot summary
PCR	1	30	✔️ Complete	Part statistics
HBR	1	40	✔️ Complete	Physical bin counts
SBR	1	50	✔️ Complete	Logical bin counts
PMR	1	60	✔️ Complete	Pin mapping
PGR	1	62	✔️ Complete	Pin grouping
PLR	1	63	✔️ Complete	Pin display properties
RDR	1	70	✔️ Complete	Retest info
SDR	1	80	✔️ Complete	Site configuration
WIR	2	10	✔️ Complete	Wafer start marker
WRR	2	20	✔️ Complete	Wafer summary
WCR	2	30	✔️ Complete	Wafer config
PIR	5	10	✔️ Complete	Part start marker
PRR	5	20	✔️ Complete	Part results
TSR	10	30	✔️ Complete	Test summary
PTR	15	10	✔️ Complete	Parametric test
MPR	15	15	⚠️ Incomplete	Multiple parametric
FTR	15	20	⚠️ Incomplete	Functional test
BPS	20	10	✔️ Complete	Program section start
EPS	20	20	✔️ Complete	Program section end
GDR	50	10	⚠️ Incomplete	User-defined data
DTR	50	30	✔️ Complete	Datalog comments

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📘 STDF v4 Data Types and Python Implementation

STDF Type Codes

STDF defines compact type codes specifying how values are stored and interpreted in records. Below is a concise overview of commonly used types:

Code	Description	C Type Specifier	Notes
C*12	Fixed-length char (12 bytes)	char[12]	Left-justified, pad with spaces
C*n	Variable-length char (1-byte length prefix)	char[]	Length 0–255
C*f	External-length string	char[]	Length defined by another field
U*1	1-byte unsigned integer	unsigned char	0–255
U*2	2-byte unsigned integer	unsigned short	0–65,535
U*4	4-byte unsigned integer	unsigned long	0–4,294,967,295
I*1	1-byte signed integer	char	–128 to 127
I*2	2-byte signed integer	short	–32,768 to 32,767
I*4	4-byte signed integer	long	–2,147,483,648 to 2,147,483,647
R*4	4-byte float (IEEE 754)	float	Single precision
R*8	8-byte float (IEEE 754)	double	Double precision
B*6	Fixed-length binary (6 bytes)	char[6]	Raw binary
V*n	Variable-type field	—	First byte = type code, up to 255 bytes data
B*n	Variable-length binary (1-byte length prefix)	char[]	Data starts at second byte
D*n	Variable-length bit field	char[]	First two bytes = bit count; padding zeros
N*1	Nibble array (4-bit units)	char	High nibble zeroed if odd count
kxTYPE	Array of specified type	TYPE[]	Length determined by another field

For full STDF v4 type reference, see pystdf4/doc/stdf-spec.pdf.

Python Implementation

PyStdf4 uses a hierarchy of classes to represent STDF fields and records, with each class implementing a specific type of field or record. The hierarchy is as follows:

FieldBase(pyT) (ABC)
├── ImmediateField(pyT)
│   ├── C_1, C_12, B_1, B_6
│   ├── C_n, B_n, C_f
│   └── D_n, N_1 [⚠️ Not Implemented Yet]
│
├── DeferredField(pyT)
│   ├── U_1, U_2, U_4
│   ├── I_1, I_2, I_4
│   └── R_4, R_8
│
├── VariableField
│   └── V_n [⚠️ Not Implemented Yet]
│
└── ArrayField
    ├── kxU_1, kxU_2, kxC_n
    └── kxN_1 [⚠️ Not Implemented Yet]

These classes handle type conversion, byte parsing, and STDF serialization, ensuring consistency between Python objects and STDF binary data.

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🗺️ Roadmap

Version	Goals
v0.x	✅ Core STDF types & common records ⬜ Fully functional StdfWriter ⬜ Robust Pythonic writing API
v1.x	⬜ SmartWriter (auto record creation) ⬜ High-level APIs for stats & aggregation ⬜ Intelligent record dependency handling
v2.x	⬜ StdfReader (efficient parsing) ⬜ Integration with analysis pipelines ⬜ Full read/write compatibility

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📜 License

MIT © 2025 — Developed for efficient and reliable STDF data manipulation in modern semiconductor workflows.