Zedda

Zero Effort Data Discovery & Analytics

C++17-powered EDA and data cleaning engine for Python.

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Guide · API reference · How it works · Contributing · Security

What is Zedda

Zedda profiles, cleans, and validates datasets from a single Python call. Its core is written in C++17 and streams data in constant memory, so it scales from a 900-row CSV to a terabyte-scale Parquet file without changing how you use it.

Installation

pip install --upgrade pip                  # Ensure pip >= 22.3 for abi3 wheel recognition
pip install zedda                          # CSV only — zero native deps
pip install "zedda[parquet]"               # adds Parquet/Arrow/Feather support
pip install "zedda[clean]"                 # adds fuzzy typo detection
pip install "zedda[ai]"                    # adds AI Q&A (zd.ask with Groq/OpenAI)
pip install "zedda[parquet,clean,ai]"      # everything together

Platform support:

Platform Base install [parquet] extra
Linux x86_64 (glibc >= 2.17 / musl) ✅ prebuilt wheel ✅ prebuilt pyarrow wheel
Linux ARM64 (aarch64) ✅ prebuilt wheel ✅ prebuilt pyarrow wheel
macOS Intel (x86_64) ✅ prebuilt wheel ✅ prebuilt pyarrow wheel
macOS Apple Silicon (ARM64) ✅ prebuilt wheel ✅ prebuilt pyarrow wheel
Windows x86_64 ✅ prebuilt wheel ✅ prebuilt pyarrow wheel
Windows ARM64 ✅ prebuilt wheel ⚠️ pyarrow has no win_arm64 wheel — Parquet requires manual build
Python 3.13 free-threaded (cp313t) ⚠️ Not yet supported — use standard Python 3.13

conda users: Zedda is not yet on conda-forge. Install via pip inside your conda environment:

conda activate myenv
pip install zedda

How to use

import zedda as zd

zd.profile("data.csv")  # full EDA report in terminal
zd.scan("data.csv")  # silent scan for CI/CD pipelines
zd.compare("train.csv", "test.csv")  # train/test drift detection
zd.fix("data.csv", apply=True)  # generate or apply pandas fix code
zd.ask("data.csv", "any nulls here?")  # plain-English dataset Q&A
zd.ml_ready("data.csv")  # readiness score for ML training
zd.warnings("data.csv")  # list all issues ranked by severity
zd.clean("data.csv", output="clean.csv")  # safe, backed-up auto-clean
zd.merge(["jan.csv", "feb.csv"], "out")  # safely combine multiple files
zd.report("data.csv", output="rep.html")  # export full report to offline HTML

Every function also accepts a pandas DataFrame directly — a file path is never required.

import pandas as pd

df = pd.read_csv("data.csv")
zd.profile(df)

See the full list of available functions in the API reference, and how the underlying engine works in How it works.

Installation from source

git clone https://github.com/Zedda-Labs/Zedda.git --recursive
cd Zedda
# C++17 build tools (cmake, ninja) are required
pip install cmake ninja
pip install -e ".[dev]"
pytest tests/

Contributing

Issues and pull requests are welcome. See CONTRIBUTING.md.

License

MIT — see LICENSE.

Project links

Data verified by PyPI on Jul 25, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Latest release

4 maintainers

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Avatar for hitesh0106 from gravatar.com hitesh0106 Avatar for princeeee1234 from gravatar.com princeeee1234 Avatar for tirthpatel90 from gravatar.com tirthpatel90
+1 more Avatar for Zedda from gravatar.com Zedda

Credits

Author/Maintainer: Zedda-Labs

GitHub Statistics

Data verified by PyPI on Jul 25, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python <3.15, >=3.9

Provides Extra

parquet ai clean dev

Tags

eda data-science profiling csv parquet pandas fast cli analysis sampling arrow

Classifiers

Report project as malware

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This release

0.4.8 This release

37 files

0.4.7

37 files

0.4.6

7 files

0.4.4

26 files

0.4.2

21 files

0.4.0

21 files

0.3.2

21 files

0.3.1

21 files

0.3.0

21 files

0.2.2

21 files

0.2.1

21 files

0.2.0

21 files

0.1.5

21 files

0.1.4

21 files

0.1.3

21 files

0.1.2

21 files

0.1.1

21 files

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