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Small library for common tasks

Project description

Helper package for coding and automation

Version 0.1.73

  • research/base_exp: add base experiment class to handle common experiment tasks, including performance calculation and saving results.

Version 0.1.67

  • now use uv for venv management
  • research/perfcalc: support both torchmetrics and custom metrics for performance calculation

Version 0.1.61

  • add util/video: add VideoUtils class to handle common video-related tasks
  • add util/gpu_mon: add GPUMonitor class to monitor GPU usage and performance

Version 0.1.59

  • add util/perfcalc: abstract class for performance calculation. This class need to be inherited and implemented with specific performance calculation logic.

Version 0.1.55

  • add util/dataclass_util to help dynamically create dataclass classes from dictionary or YAML file, including support for nested dataclasses. From there, we can use dataclass_wizard to create a list of dataclass classes with the help from ChatGPT.

Version 0.1.52

  • add research/perftb module to allow creating and managing performance tables for experiments, including filtering by datasets, metrics, and experiments.

Version 0.1.50

  • add pprint_local_path to print local path (file/directory) in clickable link (as file URI)

  • add research package to help with research tasks, including benchquery for benchmarking queries from dataframe

  • add wandb module to allow easy sync offline data to Weights & Biases (wandb) and batch clear wandb runs.

Version 0.1.47

  • add pprint_box to print object/string in a box frame (like in inspect)

Version 0.1.46

  • filter the warning message of UserWarning: Unable to import Axes3D.
  • auto_wrap_text for fn_display_df to avoid long text in the table

Version 0.1.42

  • add <rich_color.py>: add basic color list (for easy usage)

Version 0.1.41

  • add <rich_color.py> to display rich color information in python package (rcolor_str, rcolor_pallet_all, etc.)

Version 0.1.40

  • update <csvfile.py> to use itables and pygwalker to display dataframe in jupyter notebook.

Version 0.1.38

  • add <torchloader.py> to search for best cfg for torch dataloader (num_workers, batch_size, pin_memory, et.)

Version 0.1.37

  • add <dataset.py> to help split classification dataset into train/val(test)

Version 0.1.33

  • add plot.py module to plot DL model training history (with columlns: epoch, train_accuracy, val_accuracy, train_loss, val_loss) using seaborn and matplotlib

Version 0.1.29

  • for tele_noti module, kaleido==0.1.* is required for plotly since kaleido 0.2.* is not working (taking for ever to generate image)

Version 0.1.24

  • rename sys to system to avoid conflict with built-in sys module
  • add tele_noti module to send notification to telegram after a specific interval for training progress monitoring

Version 0.1.22

  • add cuda.py module to check CUDA availability (for both pytorch and tensorflow)

Version 0.1.21

  • using networkx and omegaconf to allow yaml file inheritance and override

Version 0.1.15

  • __init__.py: add common logging library; also console_log decorator to log function (start and end)

Version 0.1.10

  • filesys: fix typo on "is_exit" to "is_exist"
  • gdrive: now support uploading file to folder and return direct link (shareable link)

Version 0.1.9

  • add dependencies requirement.txt

Version 0.1.8

Fix bugs:

  • [performance] instead of inserting directly new rows into table dataframe, first insert it into in-memory row_pool_dict, that fill data in that dict into the actual dataframe when needed.

Version 0.1.7

Fix bugs:

  • fix insert into table so slow by allowing insert multiple rows at once

Version 0.1.6

New features:

  • add DFCreator for manipulating table (DataFrame) - create, insert row, display, write to file

Version 0.1.5

New Features

  • add cmd module
  • new package structure

Version 0.1.4

New Features

  • add support to create Bitbucket Project from template

Version 0.1.2

New Features

  • add support to upload local to google drive.

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