mb_base - pypi Package Compare versions

Comparing version 1.1.19 to 2.0.2

mb/plt/emb_viz.py

@@ -10,2 +10,3 @@ ## file to view pca / umap / tsne embeddings in 2d or 3d with tf projector and plotly
 import numpy as np
+from mb.utils.logging import logg
 
@@ -31,18 +32,14 @@ __all__ = ['get_emb','viz_emb','generate_sprite_images']
     if type(df) is not pd.DataFrame:
-        if logger:
-            logger.info('Type of df :{}'.format(str(type(df))))
+        logg.info('Type of df :{}'.format(str(type(df))),logger=logger)
         df = pd.load_any_df(df)
-        if logger:
-            logger.info('Loaded dataframe from path {}'.format(str(df)))
+        logg.info('Loaded dataframe from path {}'.format(str(df)),logger=logger)
     
-    if logger:
-        logger.info('Data shape {}'.format(str(df.shape)))
-        logger.info('Data columns {}'.format(str(df.columns)))
-        logger.info('Performing {} on {} embeddings'.format(emb_type,emb))
-    
+    logg.info('Data shape {}'.format(str(df.shape)),logger=logger)
+    logg.info('Data columns {}'.format(str(df.columns)),logger=logger)
+    logg.info('Performing {} on {} embeddings'.format(emb_type,emb),logger=logger)
+
     if emb_type=='pca':
         pca = PCA(n_components=dim)
         pca_emb = pca.fit_transform(list(df[emb]))
-        if logger:
-            logger.info('First PCA transform result : {}'.format(str(pca_emb[0])))
+        logg.info('First PCA transform result : {}'.format(str(pca_emb[0])),logger=logger)
         temp_res = list(pca_emb)
@@ -55,4 +52,3 @@
         tsne_emb = tsne.fit_transform(k1)
-        if logger:
-            logger.info('First TSNE transform result : {}'.format(str(tsne_emb[0])))
+        logg.info('First TSNE transform result : {}'.format(str(tsne_emb[0])),logger=logger)
         temp_res = list(tsne_emb)
@@ -64,9 +60,7 @@
         except ImportError:
-            if logger:
-                logger.info('umap not installed, installing umap')
+            logg.info('umap not installed, installing umap',logger=logger)
             os.system('pip install umap-learn')
             import umap
         umap_emb = umap.UMAP(n_components=2,**kwargs).fit_transform(list(df[emb]))
-        if logger:
-            logger.info('First UMAP transform result : {}'.format(str(umap_emb[0])))
+        logg.info('First UMAP transform result : {}'.format(str(umap_emb[0])),logger=logger)
         temp_res = list(umap_emb)
@@ -77,4 +71,3 @@
         df.drop(emb,axis=1,inplace=True)
-        if logger:
-            logger.info('Dropped original embedding column')
+        logg.info('Dropped original embedding column',logger=logger)
             
@@ -109,4 +102,3 @@ if file_save:
     if type(df) != pd.DataFrame:
-        if logger:
-            logger.info('Type of df :{}'.format(str(type(df))))
+        logg.info('Type of df :{}'.format(str(type(df))),logger=logger)
         df = pd.load_any_df(df)
@@ -121,4 +113,3 @@
     emb_data = emb_data.reshape(-1,2) #change this for 3d
-    if logger:
-        logger.info('Embedding data shape {}'.format(str(emb_data.shape)))
+    logg.info('Embedding data shape {}'.format(str(emb_data.shape)),logger=logger)
     
@@ -234,3 +225,3 @@ if target_column:
             loc_sprite_image = os.path.join(log_dir,'sprite_image.png')
-            generate_sprite_images(df[image_tb], file_save=loc_sprite_image, img_size=28 ,logger=None)        
+            generate_sprite_images(df[image_tb], file_save=loc_sprite_image, img_size=28 ,logger=logger)        
         
@@ -250,7 +241,6 @@ from tensorboard.plugins import projector
         
-        if logger:
-            logger.info('Run tensorboard --logdir={} to view embeddings'.format(log_dir))
-            logger.info('if on jupyter notebook, run below code to view embeddings in notebook')
-            logger.info('%load_ext tensorboard')
-            logger.info('%tensorboard --logdir={}'.format(log_dir))
+        logg.info('Run tensorboard --logdir={} to view embeddings'.format(log_dir),logger=logger)
+        logg.info('if on jupyter notebook, run below code to view embeddings in notebook',logger=logger)
+        logg.info('%load_ext tensorboard',logger=logger)
+        logg.info('%tensorboard --logdir={}'.format(log_dir),logger=logger)
 
@@ -257,0 +247,0 @@

METADATA

 Metadata-Version: 2.4
 Name: mb_base
-Version: 1.1.19
+Version: 2.0.2
 Summary: Meta Package for mb_* packages
@@ -5,0 +5,0 @@ Author: ['Malav Bateriwala']

RECORD

 mb/numpy/__init__.py,sha256=paJ-HHrMmhCCBXA9GVOGoWUjB82J4sJ6bczyaL0xY2E,323
 mb/pandas/__init__.py,sha256=aoUqtk-zSychmd4ALxg1-Vu8Ii3Hpska_nCy6shVEqQ,45
 mb/plt/__init__.py,sha256=Ya4j8QIe5BCbMesMr1W8L9LP-FBy9LZbUow0XatJczA,54
-mb/plt/emb_viz.py,sha256=8FDurXmS_bRHG0bV-25_JLljFiZRrvtbqcWzQceMLKk,11044
+mb/plt/emb_viz.py,sha256=dWGZepldJvFC2YNrkCSIKqc0tE-Sf8d8YJ0QjYbQkXw,10999
 mb/plt/utils.py,sha256=eE48STXqeradeImdnL12E1B6isgqa31koP536zjfAgw,2845
-mb/utils/__init__.py,sha256=A9wwxJCd4Pezd_tO0opRpggIOxZayl84dBE14FXmiFk,65
-mb/utils/pip_update.py,sha256=JaDWg6snnKP4zxS-IjV0r50HqmXI6bnwLJVljS9mWoI,775
-mb_base-1.1.19.dist-info/METADATA,sha256=BJcpD_S6Bbvey824tAY-bmDZS2necvn68_ko3Wk5Nkg,274
-mb_base-1.1.19.dist-info/WHEEL,sha256=_zCd3N1l69ArxyTb8rzEoP9TpbYXkqRFSNOD5OuxnTs,91
-mb_base-1.1.19.dist-info/top_level.txt,sha256=2T5lqIVZs7HUr0KqUMPEaPF59QXcr0ErDy6K-J88ycM,3
-mb_base-1.1.19.dist-info/RECORD,,
+mb_base-2.0.2.dist-info/METADATA,sha256=PAH9frivgPqIR1DOvfSz4vtHYdjTAzQjhwOHMN5qwXw,273
+mb_base-2.0.2.dist-info/WHEEL,sha256=YCfwYGOYMi5Jhw2fU4yNgwErybb2IX5PEwBKV4ZbdBo,91
+mb_base-2.0.2.dist-info/top_level.txt,sha256=2T5lqIVZs7HUr0KqUMPEaPF59QXcr0ErDy6K-J88ycM,3
+mb_base-2.0.2.dist-info/RECORD,,

WHEEL

 Wheel-Version: 1.0
-Generator: setuptools (80.9.0)
+Generator: setuptools (82.0.0)
 Root-Is-Purelib: true
 Tag: py3-none-any
 

mb/utils/__init__.py

-from mb_utils.src import *
-from .pip_update import update_package

mb/utils/pip_update.py

-import subprocess
-from typing import Optional
-
-__all__ = ['update_package']
-
-def update_package(package_name, logger: Optional[str]=None) -> None:
-    # Check if package is up-to-date
-    result = subprocess.run(['pip', 'check', package_name], capture_output=True, text=True)
-    if 'up-to-date' in result.stdout:
-        if logger:
-            logger.info(f"{package_name} is already up-to-date.")
-        return
-    # Install latest version of package
-    result = subprocess.run(['pip', 'install', '--upgrade', package_name], capture_output=True, text=True)
-    if result.returncode == 0:
-        if logger:
-            logger.info(f"{package_name} has been updated.")
-    else:
-        if logger:
-            logger.info(f"Error updating {package_name}: {result.stderr}")

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