Skip to main content

labdata

Tools to copy data and manage data analysis in an experimental neuroscience lab.

This is built after labdata-tools and integrates with S3 and a database through datajoint.

Concepts

Experiments often involve many computers in the lab and data has to be copied to a server(and sometimes backed up). In this process files can be corrupted, data loss and so on, specially if manually copying files. Further, in some cases, tasks have to be performed on the files (those might involve compressing, formatting, etc).

What labdata does to copy files: 1. After data are acquired, labdata performs a md5 checksum of the file to be copied and copies the file to a server. 2. After the copy, the checksum and datapath are placed on the Upload database table. 3. The computer/server that manages the copy to the permanent storage server will read the database table. The server will perform a checksum on the file to ensure the copy from the acquisition computer was ok. 4. If needed it will compress data or do whatever is specified in the preference file rules (see upload_rules) 5. Data will be put in S3 and added to the Files

Instalation

Clone the repository to a folder in your computer and do:

pip install . or pip install -e . to if you want that the source code follows git.

Metadata

Release files for labdata 0.1.23

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

Source distribution (sdist)

Source distribution for labdata 0.1.23
File Size Uploaded
labdata-0.1.23.tar.gz 447.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for labdata 0.1.23
File Interpreter ABI Platform
labdata-0.1.23-py3-none-any.whl Python 3 none any Details

Total release size: 925.8 kB

Release files / labdata-0.1.23.tar.gz

Download URL labdata-0.1.23.tar.gz
Size 447.6 kB
Tags Source
SHA-256 checksum
How to use checksums
179b8ef995e285e643ba1168bdfbc4aee6bdb06e3c355c2d3ede68dd3c7352fb
BLAKE2b-256 checksum
How to use checksums
67c562d8d1deb5fadc68db873a4a68f4f73ab0763fa65ae1233652f90b082809
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.6

Release files / labdata-0.1.23-py3-none-any.whl

Download URL labdata-0.1.23-py3-none-any.whl
Size 478.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
bd0a8823293f850b22cc544fdf429f9127ace46b22841bc64b72ce8440da2d5e
BLAKE2b-256 checksum
How to use checksums
e89bf4218774108c4829d3a9f952dcdda0e27471a505efdd68dcf13ddaba4d62
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.6

Release history Release notifications | RSS feed

This release

0.1.23 This release

2 release files

0.1.22

2 release files

0.1.21

2 release files

0.1.20

2 release files

0.1.19

2 release files

0.1.18

2 release files

0.1.17

2 release files

0.1.12

2 release files

0.1.11

2 release files

0.1.9

2 release files

0.1.8

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

0.0.24

2 release files

0.0.23

2 release files

0.0.22

2 release files

0.0.21

2 release files

0.0.20

2 release files

0.0.19

2 release files

0.0.17

2 release files

0.0.16

2 release files

0.0.15

2 release files

0.0.14

2 release files

0.0.12

2 release files

0.0.11

2 release files

0.0.10

2 release files

0.0.9

2 release files

0.0.8

2 release files

0.0.7

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.3

3 release files

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