feat: add analytics (#335)

* feat: add telemetry features.

* feat: add analytics to streamlit app

* docs: Add analytics information to the documentation.

* fix: fix issues related with imports

* fix: add request

* fix: remove print

* fix: cleaning code

---------

Co-authored-by: Fabiana Clemente <[email protected]>

docs/support/analytics.md

@@ -0,0 +1,44 @@
+
+# Analytics & Telemetry
+
+## Overview
+
+`ydata-synthetic` is a powerful library designed to generate synthetic data. 
+As part of our ongoing efforts to improve user experience and functionality, `ydata-synthetic`
+includes a telemetry feature. This feature collects anonymous usage data, helping us understand
+how the library is used and identify areas for improvement.
+
+The primary goal of collecting telemetry data is to:
+
+- Enhance the functionality and performance of the ydata-synthetic library
+- Prioritize new features based on user engagement
+- Identify common issues and bugs to improve overall user experience
+
+### Data Collected
+The telemetry system collects non-personal, anonymous information such as:
+
+- Python version
+- `ydata-synthetic` version
+- Frequency of use of `ydata-synthetic` features
+- Errors or exceptions thrown within the library
+
+## Disabling usage analytics
+
+We respect your choice to not participate in our telemetry collection. 
+If you prefer to disable telemetry, you can do so by setting an environment 
+variable on your system. Disabling telemetry will not affect the functionality
+of the ydata-profiling library, except for the ability to contribute to its usage analytics.
+
+### Set an Environment Variable
+In your notebook or script make sure to set YDATA_SYNTHETIC_NO_ANALYTICS 
+environment variable to `True`.
+
+````python
+    import os
+
+    os.environ['YDATA_SYNTHETIC_NO_ANALYTICS']='True'
+````
+
+
+
+

mkdocs.yml

@@ -34,6 +34,7 @@ nav:
     - Help & Troubleshooting: 'support/help-troubleshooting.md'
     - Contribution Guidelines: 'support/contribute.md'
     - Contribution Guidelines: 'support/contribute.md'
+    - Analytics: 'support/analytics.md'
   - Reference:
       - Changelog: 'reference/changelog.md'
       - API:

src/ydata_synthetic/streamlit_app/pages/1_Train_a_synthesizer.py

@@ -1,18 +1,24 @@
 from typing import Union
 import os
 import json
+import logging
+
 import streamlit as st
 
 from ydata.sdk.synthesizers import RegularSynthesizer
 from ydata.sdk.common.client import get_client
 
+from ydata_synthetic.utils.logger import SynthesizersLogger
 from ydata_synthetic.synthesizers import ModelParameters, TrainParameters
 from ydata_synthetic.synthesizers.regular.model import Model
 
 from ydata_synthetic.streamlit_app.pages.functions.load_data import upload_file
 from ydata_synthetic.streamlit_app.pages.functions.train import DataType, __CONDITIONAL_MODELS
 from ydata_synthetic.streamlit_app.pages.functions.train import init_synth, advanced_setttings, training_parameters
 
+logger = SynthesizersLogger(name='streamlitSynthesizer.logger')
+logger.setLevel(logging.INFO)
+
 def get_available_models(type: Union[str, DataType]):
 
     dtype = DataType(type)
@@ -114,6 +120,8 @@ def run():
 
             st.subheader("3. Train your synthesizer")
             if st.button('Click here to start the training process', disabled=not valid_token):
+
+                logger.info_def_report(model='fabric')
                 model = RegularSynthesizer()
                 with st.spinner("Please wait while your synthesizer trains..."):
                     dtypes = {}

src/ydata_synthetic/synthesizers/regular/model.py

@@ -2,6 +2,7 @@
     Main synthesizer class
 """
 from enum import Enum, unique
+import logging
 
 from joblib import load
 
@@ -17,6 +18,10 @@
 from ydata_synthetic.synthesizers.regular.ctgan.model import CTGAN
 from ydata_synthetic.synthesizers.regular.gmm.model import GMM
 
+from ydata_synthetic.utils.logger import SynthesizersLogger
+
+logger = SynthesizersLogger(name='regularsynthesizer.logger')
+logger.setLevel(logging.INFO)
 
 @unique
 class Model(Enum):
@@ -54,6 +59,8 @@ def __new__(cls, modelname: str, model_parameters =None, **kwargs):
             model=Model(modelname).function(**kwargs)
         else:
             model=Model(modelname).function(model_parameters, **kwargs)
+
+        logger.info_def_report(model=modelname)
         return model
 
     @staticmethod

src/ydata_synthetic/synthesizers/timeseries/model.py

@@ -3,13 +3,18 @@
 """
 from enum import Enum, unique
 import os
+import logging
 from joblib import load
 
 from tensorflow import config as tfconfig
 
 from ydata_synthetic.synthesizers.timeseries.timegan.model import TimeGAN
 from ydata_synthetic.synthesizers.timeseries.doppelganger.model import DoppelGANger
 
+from ydata_synthetic.utils.logger import SynthesizersLogger
+
+logger = SynthesizersLogger(name='timseriesSynthesizer.logger')
+logger.setLevel(logging.INFO)
 
 @unique
 class Model(Enum):
@@ -28,6 +33,7 @@ def function(self):
 class TimeSeriesSynthesizer():
     "Abstraction class "
     def __new__(cls, modelname: str, model_parameters=None, **kwargs):
+        logger.info_def_report(model=modelname)
         return Model(modelname).function(model_parameters, **kwargs)
 
     @staticmethod

src/ydata_synthetic/utils/logger.py

@@ -0,0 +1,23 @@
+"""
+    ydata-synthetic logger
+"""
+from __future__ import absolute_import, division, print_function
+
+import logging
+
+from ydata_synthetic.utils.utils import analytics_features
+
+class SynthesizersLogger(logging.Logger):
+    def __init__(self, name, level=logging.INFO):
+        super().__init__(name, level)
+
+    def info(
+            self,
+            msg: object,
+        ) -> None:
+        super().info(f'[SYNTHESIZER] - {msg}.')
+
+    def info_def_report(self, model: str):
+        analytics_features(model=model)
+
+        super().info(f'[SYNTHESIZER] Creating a synthetic data generator with the following model - {model}.')

src/ydata_synthetic/utils/utils.py

@@ -0,0 +1,32 @@
+"""
+    Utility functions that are common to ydata-synthetic project
+"""
+import os
+import subprocess
+import platform
+import requests
+
+from ydata_synthetic.version import __version__
+def analytics_features(model: str):
+    endpoint= "https://packages.ydata.ai/ydata-synthetic?"
+
+    if bool(os.getenv("YDATA_SYNTHETIC_NO_ANALYTICS"))!= True:
+        package_version = __version__
+        try:
+            subprocess.check_output("nvidia-smi")
+            gpu_present = True
+        except Exception:
+            gpu_present = False
+
+        python_version = ".".join(platform.python_version().split(".")[:2])
+
+        try:
+            request_message = f"{endpoint}version={package_version}" \
+                                 f"&python_version={python_version}" \
+                                 f"&model={model}" \
+                                 f"&os={platform.system()}" \
+                                 f"&gpu={str(gpu_present)}"
+
+            requests.get(request_message)
+        except Exception:
+            pass