Skip to main content

ExeTera

Welcome to the ExeTera Readme! This page and the accompanying github wiki show you how to make use of ExeTera to create reproducible analysis pipelines for large tabular datasets.

Please take a moment to read this page, and also take a look at the Wiki, which contains in-depth documentation on the concepts behind this software, usage examples, and developer resources such as the roadmap for future releases.

Current release and requirements

Documentation Status PyPI Version Testing codecov

Requires python 3.7+


Usage

The ExeTera allows you to import data from CSV sources into HDF5, a columnar data format more suited to performing analytics. This is done through exetera import.

exetera import

exetera import \
  -s path/to/covid_schema.json \
  -i "patients:path/to/patient_data.csv, assessments:path/to/assessmentdata.csv, tests:path/to/covid_test_data.csv, diet:path/to/diet_study_data.csv" \
  -o /path/to/output_dataset_name.hdf5 \
  --include "patients:(id,country_code,blood_group), assessments:(id,patient_id,chest_pain)" \
  --exclude "tests:(country_code)"

Arguments

  • -s/--schema: The location and name of the schema file
  • -te/--territories: If set, this only imports the listed territories. If left unset, all territories are imported
  • -i/--inputs : A comma separated list of 'name:file' pairs. This should be put in parentheses if it contains any whitespace. See the example above.
  • -o/--output_hdf5: The path and name to where the resulting hdf5 dataset should be written
  • -ts/--timestamp: An override for the timestamp to be written (defaults to datetime.now(timezone.utc))
  • -w/--overwrite: If set, overwrite any existing dataset with the same name; appends to existing dataset otherwise
  • -n/--include: If set, filters out all fields apart from those in the list.
  • -x/--exclude: If set, filters out the fields in this list.

Expect this script to take about an hour or more to execute on very large datasets.

How do I work on the resulting dataset?

This is done through the python exetera API.

from exetera.core.session import Session

with Session() as s:
    src = s.open_dataset('/path/to/my/source/dataset', 'r', 'src')
    dest = s.open_dataset('/path/to/my/result/dataset', 'w', 'dest')

    # code...

See the wiki for detailed examples of how to interact with the hdf5 datastore.

Changes

The ChangeLog can now be found on the ExeTera wiki

Metadata

Release files for exetera 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for exetera 0.6.0
File Interpreter ABI Platform
exetera-0.6.0-py3-none-any.whl Python 3 none any Details

Release files / exetera-0.6.0-py3-none-any.whl

Download URL exetera-0.6.0-py3-none-any.whl
Size 105.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0a7bd4bb3065d387ee8d362ac10f1f03c31d3a8b2588da405db258fd2ff5b14e
BLAKE2b-256 checksum
How to use checksums
404dc35a67e6ff8afb47af2d38f8bb31167aaf9ac234eeac433d17a8d70924de
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.7.12

Security for exetera 0.6.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page