1

my_logging_print.py

@@ -0,0 +1,6 @@
+class logging:
+    info = print
+    warning = print
+    debug = print
+    error = print
+    critical = print

my_static_tools.py

@@ -1,5 +1,6 @@
 from typing import Union, NamedTuple
-import io,os,re,sys,math,time,uuid,ctypes,pickle,random,shutil,string,urllib,decimal,datetime,itertools,traceback,collections #,statistics
+from collections.abc import Callable
+import io,os,re,sys,math,time,uuid,ctypes,pickle,random,shutil,string,urllib,decimal,datetime,itertools,traceback,collections,statistics
 import numpy as np, pandas as pd
 import plotly.express as px
 import huggingface_hub
@@ -47,14 +48,14 @@ def pandas_random_dataframe(n_cols:int = 15, n_rows:int = 100) -> pd.DataFrame:
 class HfRepo(NamedTuple):
     repo_id: str
     repo_type: str
-    token: str
+    get_token: Callable[[], str]
 
 class HF_tools:
     """ Huggingface tools """
 
-    def list_models_spaces(token: str, author = 'f64k'):
+    def list_models_spaces(get_token: Callable[[], str], author = 'f64k'):
         """ list models and spaces """
-        api = huggingface_hub.HfApi(token=token)
+        api = huggingface_hub.HfApi(token=get_token()) #
         #spaces = api.list_spaces(author=author)
         models = api.list_models(author=author)
         datasets = api.list_datasets(author=author)
@@ -68,7 +69,7 @@ class HF_tools:
             local_filename = os.path.join(".temp", new_filename)
             #df.to_csv('compressed_data.zip', index=False, compression={'method': 'zip', 'archive_name': 'data.csv'})
             dfToSave.to_csv(local_filename, index=False, sep=";", encoding="utf-8") # , compression="zip"
-            apiHF = huggingface_hub.HfApi(token=repo.token)
+            apiHF = huggingface_hub.HfApi(token=repo.get_token()) # os.getenv(repo.env_token)
             path_in_repo = os.path.basename(local_filename)
             if remote_subdir:
                 path_in_repo = f"{remote_subdir}/{path_in_repo}"
@@ -82,7 +83,7 @@ class HF_tools:
         #https://huggingface.co/datasets/f64k/gaziev/blob/main/TestData3_2204_noAB_gaziev.zip
         dict_res = {}
         for fl_name in lstCsvFiles:
-            try: file_loaded = huggingface_hub.hf_hub_download(filename=fl_name, repo_id=repo.repo_id, repo_type=repo.repo_type, token=repo.token)
+            try: file_loaded = huggingface_hub.hf_hub_download(filename=fl_name, repo_id=repo.repo_id, repo_type=repo.repo_type, token=repo.get_token())
             except: file_loaded = ""
             if os.path.exists(file_loaded):
                 compress = "zip" if file_loaded.lower().endswith("zip") else None
@@ -93,7 +94,7 @@ class HF_tools:
     def list_files_hf(repo: HfRepo) -> list[str]:
         """ List CSV and ZIP files in HF repo - список CSV и ZIP файлов (c уровнем вложенности) в репозитории """
         ### https://huggingface.co/docs/huggingface_hub/en/guides/hf_file_system
-        fs = huggingface_hub.HfFileSystem(token=repo.token, use_listings_cache=False) # , skip_instance_cache=True
+        fs = huggingface_hub.HfFileSystem(token=repo.get_token(), use_listings_cache=False) # , skip_instance_cache=True
         path_hf = f"{repo.repo_type}s/{repo.repo_id}/"
         #lst = fs.ls(path_hf, detail=False)
         lstGlob = fs.glob(path_hf + "**") # map(os.path.basename, lstGlob)

pages/2_TECT_IDXYZ.py

@@ -27,7 +27,7 @@ if True:
     #st.sidebar.write(dirParams)
 
 
-REPO = mst.HfRepo("f64k/gaziev", "dataset", st.secrets["HF_WRITE"])
+REPO = mst.HfRepo("f64k/gaziev", "dataset", lambda: st.secrets["HF_WRITE"])
 lstRepoFiles = hft.list_files_hf(REPO) # список уже имеющихся в репозитории файлов
 dictTestFilesIdXyz = {f.upper().replace("ID_XYZ/",""): f.upper() for f in lstRepoFiles if f.upper().startswith("ID_XYZ/")}
 

pages/4_Загрузка Просмотр CSV.py

@@ -9,7 +9,7 @@ from my_static_tools import XYZV_tools as xvt
 st.set_page_config(page_title="Загрузка + Просмотр", page_icon="💾", layout="wide", initial_sidebar_state="expanded")
 
 st.html(mst.STYLE_CORRECTION)
-REPO = mst.HfRepo("f64k/gaziev", "dataset", st.secrets["HF_WRITE"])
+REPO = mst.HfRepo("f64k/gaziev", "dataset", lambda: st.secrets["HF_WRITE"])
 
 st.sidebar.markdown("# 💾 Загрузка")
 st.sidebar.markdown("# 🧊 Просмотр")

pages/6_Chat.py

@@ -21,7 +21,7 @@ st.sidebar.markdown("# Переговоры 💬")
 #st.write(conn)
 #st.help(conn)
 
-REPO = mst.HfRepo("f64k/gaziev", "dataset", st.secrets["HF_WRITE"])
+REPO = mst.HfRepo("f64k/gaziev", "dataset", lambda: st.secrets["HF_WRITE"])
 lstRepoFiles = hft.list_files_hf(REPO) # список уже имеющихся в репозитории файлов
 dictTestFilesIdXyz = {f.upper().replace("ID_XYZ/",""): f.upper() for f in lstRepoFiles if f.upper().startswith("ID_XYZ/")}
 

pages/old/_просмотр_CSV.py

@@ -10,7 +10,7 @@ st.html(mst.STYLE_CORRECTION)
 #col1.metric("Temperature", "70 °F", "1.2 °F") #col2.metric("Wind", "9 mph", "-8%") #col3.metric("Humidity", "86%", "4%")
 
 
-REPO = mst.HfRepo("f64k/gaziev", "dataset", st.secrets["HF_WRITE"])
+REPO = mst.HfRepo("f64k/gaziev", "dataset", lambda: st.secrets["HF_WRITE"])
 st.sidebar.info("🧊💽 сохраненные\n таблицы CSV")
 
 lstTestFiles = [f for f in hft.list_files_hf(REPO) if not f.upper().startswith("ID_XYZ/")]

requirements.txt

@@ -7,9 +7,10 @@
 streamlit # https://libraries.io/pypi/streamlit/ # HAS pandas numpy
 #pandas
 #numpy
-ipywidgets # https://libraries.io/pypi/ipywidgets/ # HAS ipykernel
 huggingface_hub
 scikit-learn
 plotly
 psutil
+ipykernel # https://libraries.io/pypi/ipykernel/
+ipywidgets # https://libraries.io/pypi/ipywidgets/
 faker