Skip to main content

CodeFactor Documentation Status

filerecords is a python command line tool to better keep track of files and directories for data science projects (or any kind of big directory structure). It works similar to GIT but instead of keeping track of the actual file contents it keeps a registry of comments and flags. This allows users to comment their important files and directories to add more detailed descriptions than just a good file name or directory name.

example

Short overview

This is a brief listing of all commands. More details on their use can be found in the documentation on readthedocs.

To create a new registry within a directory use:

records init 

To add a comment about a file or directory use: This will add new comments to file entries while preserving the old ones.

records comment the_file -c "the comment" -f flag1 flag2 ...

To remove a file or directory from the registry use: (by default this will also remove the file in the filesystem!)

records rm the_file

To move a file or directory while keeping the records use: (by default this will also move the file in the filesystem!)

records mv the_current_path the_new_path

To remove/undo the last comment from a file or directory use:

records undo the_file

This also works for flags:

records undo the_file -f the_flag_to_remove 

To get a file's records use:

records lookup the_file

this will print the latest comment to the terminal.

To read the entire records of a file use:

record read the_file

To search for files and directories based on flags or regex patterns use:

records list -f flag1 -e the_regex_pattern

This can be restricted to files in the current working directory by:

records ls 

instead of the full list command.

To only add a flag (but no comment) to a file use:

records flag the_file -f flag1 

This could also be achieved using

records comment the_file -f flag1 

To define new flag groups to the registry use:

records flag -g group1 : flag1 flag2 -g group2 : flag3 flag4

To remove all file records from the registry use:

records clear

To completely remove a registry use:

records destroy

To export the registry either in YAML or markdown format use:

records export yaml|md|both

Metadata

Release files for filerecords 0.0.1

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

Source distribution (sdist)

Source distribution for filerecords 0.0.1
File Size Uploaded Provenance
filerecords-0.0.1.tar.gz 32.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for filerecords 0.0.1
File Interpreter ABI Platform
filerecords-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 73.5 kB

Release files / filerecords-0.0.1.tar.gz

Download URL filerecords-0.0.1.tar.gz
Size 32.3 kB
Tags Source
SHA-256 checksum
How to use checksums
6fb9df45d057794f1b796a001c83170537bb9d77475076a1f04ba4ed288efce6
BLAKE2b-256 checksum
How to use checksums
175ca4969c357113169c1a9d6140ef2299b7dcc35509f3eef14c4cec9b3bd3c4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.8.12

Release files / filerecords-0.0.1-py3-none-any.whl

Download URL filerecords-0.0.1-py3-none-any.whl
Size 41.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1985a0150e4cccfaa52d5371efea08188f5e4c07415d258c0c415ead0a54293f
BLAKE2b-256 checksum
How to use checksums
5ac1b99dafe6d94af2d78ec6f8472cb18a9dc1561c5b7cf3b52e08e98fa41714
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.8.12

Security for filerecords 0.0.1

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

This release

0.0.1 This release

2 release files No provenance

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