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2022-03-07T03:06:35,568 Given no hashes to check 1 links for project 'decanter-ai-core-sdk': discarding no candidates
2022-03-07T03:06:35,599 Collecting decanter-ai-core-sdk==1.1.9
2022-03-07T03:06:35,604 Created temporary directory: /tmp/pip-unpack-umq1ouhn
2022-03-07T03:06:36,201 Downloading decanter-ai-core-sdk-1.1.9.tar.gz (661 kB)
2022-03-07T03:06:36,855 Added decanter-ai-core-sdk==1.1.9 from https://files.pythonhosted.org/packages/18/c8/9c95db9448228055864c140f20fc086dba15851c04cec3ba1055d8688661/decanter-ai-core-sdk-1.1.9.tar.gz#sha256=7c7166cdd3cc04919113a036f69a6f96a0285e62e3dfbbf342544d04e8b026d6 to build tracker '/tmp/pip-req-tracker-o07ks40j'
2022-03-07T03:06:36,857 Running setup.py (path:/tmp/pip-wheel-jbvjek1b/decanter-ai-core-sdk_d945a4f83b564fc58070724de6b97c91/setup.py) egg_info for package decanter-ai-core-sdk
2022-03-07T03:06:36,858 Created temporary directory: /tmp/pip-pip-egg-info-1bdh0sdj
2022-03-07T03:06:36,859 Preparing metadata (setup.py): started
2022-03-07T03:06:36,861 Running command python setup.py egg_info
2022-03-07T03:06:38,860 # MoBagel Decanter AI Core SDK
2022-03-07T03:06:38,861 [![PyPI version](https://badge.fury.io/py/decanter-ai-core-sdk.svg)](https://pypi.org/project/decanter-ai-core-sdk/)
2022-03-07T03:06:38,862 [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/MoBagel/decanter-ai-core-sdk)
2022-03-07T03:06:38,862 [![GitHub Super-Linter](https://github.com/MoBagel/decanter-ai-core-sdk/workflows/Lint%20Code%20Base/badge.svg)](https://github.com/marketplace/actions/super-linter)
2022-03-07T03:06:38,863 Decanter AI is a powerful AutoML tool which enables everyone to build ML models and make predictions without data science background. With Decanter AI Core SDK, you can integrate Decanter AI into your application more easily with Python.
2022-03-07T03:06:38,863 It supports actions such as data uploading, model training, and prediction to run in a more efficient way and access results more easily. You can also use Decanter AI Core SDK in Jupyter Notebook for better visualization.
2022-03-07T03:06:38,864 To know more about Decanter AI and how you can be benefited with AutoML, visit [MoBagel website](https://mobagel.com/product/) and contact us to try it out!
2022-03-07T03:06:38,865 ## System Requirement
2022-03-07T03:06:38,865 * python3.7
2022-03-07T03:06:38,866 ## Install
2022-03-07T03:06:38,866 Install and update using pip:
2022-03-07T03:06:38,867 ```bash
2022-03-07T03:06:38,867 pip install decanter-ai-core-sdk
2022-03-07T03:06:38,867 ```
2022-03-07T03:06:38,869 ## Basic Example: Upload Data
2022-03-07T03:06:38,869 ```python
2022-03-07T03:06:38,869 from decanter import core
2022-03-07T03:06:38,870 core.enable_default_logger()
2022-03-07T03:06:38,870 client = core.CoreClient(username=???, password=???, host=???)
2022-03-07T03:06:38,871 train_file = open(train_file_path, 'rb')
2022-03-07T03:06:38,871 train_data = client.upload(file=train_file, name="train")
2022-03-07T03:06:38,872 # in jupyter notebook just run the block
2022-03-07T03:06:38,872 # no need to call context.run()
2022-03-07T03:06:38,873 client.run()
2022-03-07T03:06:38,873 train_data.show()
2022-03-07T03:06:38,874 ```
2022-03-07T03:06:38,874 ```bash
2022-03-07T03:06:38,874 $ python -m example.file
2022-03-07T03:06:38,875 15:50:09 [ INFO] [Context] no event loop to close
2022-03-07T03:06:38,875 15:50:09 [ INFO] [Context] connect healthy :)
2022-03-07T03:06:38,875 Progress UploadTask_train: 55%|█████████████████████████████████████████
2022-03-07T03:06:38,876 ```
2022-03-07T03:06:38,876 ## Example Dataset Path
2022-03-07T03:06:38,877 * `examples/data/` - store the general dataset
2022-03-07T03:06:38,877 * `examples/data/ts_data` - store the time series dataset
2022-03-07T03:06:38,878 ## Example Code
2022-03-07T03:06:38,878 * General Data
2022-03-07T03:06:38,879 * Python Script: [example.py](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/example.py)
2022-03-07T03:06:38,879 * Jupyter: [jupyter_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_example.ipynb)
2022-03-07T03:06:38,879 * Time Series Data
2022-03-07T03:06:38,880 * Python Script: [auto_time_series_example.py](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/auto_time_series_example.py)
2022-03-07T03:06:38,880 Note:
2022-03-07T03:06:38,881 Since Jupyter already have an event loop (asyncio), SDK will just use the current event loop. See more in [here](https://www.notion.so/API-615d2fba4e7f45c4b5fe63cc192e481f#bb4f0a4b2847450abc4f80b025469170).
2022-03-07T03:06:38,881 More details about asyncio in [learn asyncio](https://docs.python.org/3/library/asyncio.html)
2022-03-07T03:06:38,881 ```python
2022-03-07T03:06:38,882 import asyncio
2022-03-07T03:06:38,882 loop = asyncio.get_running_loop()
2022-03-07T03:06:38,882 loop.is_running()
2022-03-07T03:06:38,883 ```
2022-03-07T03:06:38,883 ## Tutorial for Jupyter Notebook
2022-03-07T03:06:38,884 1. first you need to install jupyter lab: `pip install jupyterlab`
2022-03-07T03:06:38,884 2. this is required for progress bar to display correctly: `pip install ipywidgets`
2022-03-07T03:06:38,884 3. (optional, conda venv for jupyter notebook) `conda install nb_conda`
2022-03-07T03:06:38,884 4. `jupyter lab`
2022-03-07T03:06:38,885 * this should open your browser to jupyter lab page.
2022-03-07T03:06:38,885 * If you want to learn how to build ML models with Decanter AI, visit our [jupyter_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_example.ipynb) for step by step tutorial.
2022-03-07T03:06:38,885 * If you need to handle running tasks well, refer to our [jupyter_jobs_handle_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_jobs_handle_example.ipynb).
2022-03-07T03:06:38,886 ## Development Guide and Flow
2022-03-07T03:06:38,887 * If you are curious about why Decanter AI Core SDK does certain things the way it does and not differently, visit our [Development Guide](https://mobagel.github.io/decanter-ai-core-sdk/notes/design.html)
2022-03-07T03:06:38,888 ## Documentation
2022-03-07T03:06:38,888 To understand how we design Decanter AI Core SDK, `doc/` contains the complete documentation, including the design system, the use of each API, and the required dependencies to install. Refer to our [document page](https://mobagel.github.io/decanter-ai-core-sdk/index.html) to navigate the complete information.
2022-03-07T03:06:38,889 ## Contributing
2022-03-07T03:06:38,889 For guidance on setting up a development environment and how to make a contribution to Decanter AI Core SDK, see the [contributing guidelines](https://mobagel.github.io/decanter-ai-core-sdk/notes/contributing.html).
2022-03-07T03:06:38,890 ## Links
2022-03-07T03:06:38,890 For more details on design, guidance on setting up a development environment, and SDK usage.
2022-03-07T03:06:38,891 * Decanter AI Introduction:
2022-03-07T03:06:38,891 * Decanter AI SDK Introduction:
2022-03-07T03:06:38,892 * Code:
2022-03-07T03:06:38,892 * Installation:
2022-03-07T03:06:38,892 * API interface:
2022-03-07T03:06:38,893 running egg_info
2022-03-07T03:06:38,893 creating /tmp/pip-pip-egg-info-1bdh0sdj/decanter_ai_core_sdk.egg-info
2022-03-07T03:06:38,894 writing manifest file '/tmp/pip-pip-egg-info-1bdh0sdj/decanter_ai_core_sdk.egg-info/SOURCES.txt'
2022-03-07T03:06:38,918 writing manifest file '/tmp/pip-pip-egg-info-1bdh0sdj/decanter_ai_core_sdk.egg-info/SOURCES.txt'
2022-03-07T03:06:39,045 Preparing metadata (setup.py): finished with status 'done'
2022-03-07T03:06:39,056 Source in /tmp/pip-wheel-jbvjek1b/decanter-ai-core-sdk_d945a4f83b564fc58070724de6b97c91 has version 1.1.9, which satisfies requirement decanter-ai-core-sdk==1.1.9 from https://files.pythonhosted.org/packages/18/c8/9c95db9448228055864c140f20fc086dba15851c04cec3ba1055d8688661/decanter-ai-core-sdk-1.1.9.tar.gz#sha256=7c7166cdd3cc04919113a036f69a6f96a0285e62e3dfbbf342544d04e8b026d6
2022-03-07T03:06:39,058 Removed decanter-ai-core-sdk==1.1.9 from https://files.pythonhosted.org/packages/18/c8/9c95db9448228055864c140f20fc086dba15851c04cec3ba1055d8688661/decanter-ai-core-sdk-1.1.9.tar.gz#sha256=7c7166cdd3cc04919113a036f69a6f96a0285e62e3dfbbf342544d04e8b026d6 from build tracker '/tmp/pip-req-tracker-o07ks40j'
2022-03-07T03:06:39,073 Created temporary directory: /tmp/pip-unpack-h_v5iydn
2022-03-07T03:06:39,074 Building wheels for collected packages: decanter-ai-core-sdk
2022-03-07T03:06:39,082 Created temporary directory: /tmp/pip-wheel-3gyyvef4
2022-03-07T03:06:39,083 Building wheel for decanter-ai-core-sdk (setup.py): started
2022-03-07T03:06:39,085 Destination directory: /tmp/pip-wheel-3gyyvef4
2022-03-07T03:06:39,085 Running command python setup.py bdist_wheel
2022-03-07T03:06:40,536 # MoBagel Decanter AI Core SDK
2022-03-07T03:06:40,538 [![PyPI version](https://badge.fury.io/py/decanter-ai-core-sdk.svg)](https://pypi.org/project/decanter-ai-core-sdk/)
2022-03-07T03:06:40,538 [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/MoBagel/decanter-ai-core-sdk)
2022-03-07T03:06:40,539 [![GitHub Super-Linter](https://github.com/MoBagel/decanter-ai-core-sdk/workflows/Lint%20Code%20Base/badge.svg)](https://github.com/marketplace/actions/super-linter)
2022-03-07T03:06:40,539 Decanter AI is a powerful AutoML tool which enables everyone to build ML models and make predictions without data science background. With Decanter AI Core SDK, you can integrate Decanter AI into your application more easily with Python.
2022-03-07T03:06:40,540 It supports actions such as data uploading, model training, and prediction to run in a more efficient way and access results more easily. You can also use Decanter AI Core SDK in Jupyter Notebook for better visualization.
2022-03-07T03:06:40,541 To know more about Decanter AI and how you can be benefited with AutoML, visit [MoBagel website](https://mobagel.com/product/) and contact us to try it out!
2022-03-07T03:06:40,541 ## System Requirement
2022-03-07T03:06:40,542 * python3.7
2022-03-07T03:06:40,543 ## Install
2022-03-07T03:06:40,543 Install and update using pip:
2022-03-07T03:06:40,543 ```bash
2022-03-07T03:06:40,544 pip install decanter-ai-core-sdk
2022-03-07T03:06:40,544 ```
2022-03-07T03:06:40,545 ## Basic Example: Upload Data
2022-03-07T03:06:40,545 ```python
2022-03-07T03:06:40,545 from decanter import core
2022-03-07T03:06:40,546 core.enable_default_logger()
2022-03-07T03:06:40,546 client = core.CoreClient(username=???, password=???, host=???)
2022-03-07T03:06:40,547 train_file = open(train_file_path, 'rb')
2022-03-07T03:06:40,547 train_data = client.upload(file=train_file, name="train")
2022-03-07T03:06:40,548 # in jupyter notebook just run the block
2022-03-07T03:06:40,548 # no need to call context.run()
2022-03-07T03:06:40,549 client.run()
2022-03-07T03:06:40,549 train_data.show()
2022-03-07T03:06:40,550 ```
2022-03-07T03:06:40,550 ```bash
2022-03-07T03:06:40,550 $ python -m example.file
2022-03-07T03:06:40,551 15:50:09 [ INFO] [Context] no event loop to close
2022-03-07T03:06:40,551 15:50:09 [ INFO] [Context] connect healthy :)
2022-03-07T03:06:40,551 Progress UploadTask_train: 55%|█████████████████████████████████████████
2022-03-07T03:06:40,552 ```
2022-03-07T03:06:40,552 ## Example Dataset Path
2022-03-07T03:06:40,552 * `examples/data/` - store the general dataset
2022-03-07T03:06:40,553 * `examples/data/ts_data` - store the time series dataset
2022-03-07T03:06:40,554 ## Example Code
2022-03-07T03:06:40,554 * General Data
2022-03-07T03:06:40,554 * Python Script: [example.py](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/example.py)
2022-03-07T03:06:40,555 * Jupyter: [jupyter_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_example.ipynb)
2022-03-07T03:06:40,555 * Time Series Data
2022-03-07T03:06:40,555 * Python Script: [auto_time_series_example.py](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/auto_time_series_example.py)
2022-03-07T03:06:40,556 Note:
2022-03-07T03:06:40,556 Since Jupyter already have an event loop (asyncio), SDK will just use the current event loop. See more in [here](https://www.notion.so/API-615d2fba4e7f45c4b5fe63cc192e481f#bb4f0a4b2847450abc4f80b025469170).
2022-03-07T03:06:40,556 More details about asyncio in [learn asyncio](https://docs.python.org/3/library/asyncio.html)
2022-03-07T03:06:40,557 ```python
2022-03-07T03:06:40,557 import asyncio
2022-03-07T03:06:40,558 loop = asyncio.get_running_loop()
2022-03-07T03:06:40,558 loop.is_running()
2022-03-07T03:06:40,558 ```
2022-03-07T03:06:40,559 ## Tutorial for Jupyter Notebook
2022-03-07T03:06:40,559 1. first you need to install jupyter lab: `pip install jupyterlab`
2022-03-07T03:06:40,559 2. this is required for progress bar to display correctly: `pip install ipywidgets`
2022-03-07T03:06:40,560 3. (optional, conda venv for jupyter notebook) `conda install nb_conda`
2022-03-07T03:06:40,560 4. `jupyter lab`
2022-03-07T03:06:40,560 * this should open your browser to jupyter lab page.
2022-03-07T03:06:40,561 * If you want to learn how to build ML models with Decanter AI, visit our [jupyter_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_example.ipynb) for step by step tutorial.
2022-03-07T03:06:40,561 * If you need to handle running tasks well, refer to our [jupyter_jobs_handle_example.ipynb](https://github.com/MoBagel/decanter-ai-core-sdk/blob/master/examples/jupyter_jobs_handle_example.ipynb).
2022-03-07T03:06:40,562 ## Development Guide and Flow
2022-03-07T03:06:40,562 * If you are curious about why Decanter AI Core SDK does certain things the way it does and not differently, visit our [Development Guide](https://mobagel.github.io/decanter-ai-core-sdk/notes/design.html)
2022-03-07T03:06:40,563 ## Documentation
2022-03-07T03:06:40,563 To understand how we design Decanter AI Core SDK, `doc/` contains the complete documentation, including the design system, the use of each API, and the required dependencies to install. Refer to our [document page](https://mobagel.github.io/decanter-ai-core-sdk/index.html) to navigate the complete information.
2022-03-07T03:06:40,564 ## Contributing
2022-03-07T03:06:40,565 For guidance on setting up a development environment and how to make a contribution to Decanter AI Core SDK, see the [contributing guidelines](https://mobagel.github.io/decanter-ai-core-sdk/notes/contributing.html).
2022-03-07T03:06:40,566 ## Links
2022-03-07T03:06:40,566 For more details on design, guidance on setting up a development environment, and SDK usage.
2022-03-07T03:06:40,567 * Decanter AI Introduction:
2022-03-07T03:06:40,567 * Decanter AI SDK Introduction:
2022-03-07T03:06:40,567 * Code:
2022-03-07T03:06:40,567 * Installation:
2022-03-07T03:06:40,568 * API interface:
2022-03-07T03:06:41,080 running bdist_wheel
2022-03-07T03:06:41,089 running build
2022-03-07T03:06:41,089 running build_py
2022-03-07T03:06:41,099 creating build
2022-03-07T03:06:41,099 creating build/lib
2022-03-07T03:06:41,100 creating build/lib/decanter
2022-03-07T03:06:41,103 copying src/decanter/__init__.py -> build/lib/decanter
2022-03-07T03:06:41,107 creating build/lib/decanter/core
2022-03-07T03:06:41,109 copying src/decanter/core/client.py -> build/lib/decanter/core
2022-03-07T03:06:41,113 copying src/decanter/core/context.py -> build/lib/decanter/core
2022-03-07T03:06:41,117 copying src/decanter/core/__init__.py -> build/lib/decanter/core
2022-03-07T03:06:41,121 copying src/decanter/core/plot.py -> build/lib/decanter/core
2022-03-07T03:06:41,126 creating build/lib/decanter/core/enums
2022-03-07T03:06:41,127 copying src/decanter/core/enums/time_units.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,131 copying src/decanter/core/enums/__init__.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,134 copying src/decanter/core/enums/evaluators.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,137 copying src/decanter/core/enums/numerical_group_by_methods.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,140 copying src/decanter/core/enums/algorithms.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,144 copying src/decanter/core/enums/categorical_group_by_method.py -> build/lib/decanter/core/enums
2022-03-07T03:06:41,148 creating build/lib/decanter/core/extra
2022-03-07T03:06:41,150 copying src/decanter/core/extra/const.py -> build/lib/decanter/core/extra
2022-03-07T03:06:41,153 copying src/decanter/core/extra/__init__.py -> build/lib/decanter/core/extra
2022-03-07T03:06:41,156 copying src/decanter/core/extra/utils.py -> build/lib/decanter/core/extra
2022-03-07T03:06:41,159 copying src/decanter/core/extra/decorators.py -> build/lib/decanter/core/extra
2022-03-07T03:06:41,164 creating build/lib/decanter/core/jobs
2022-03-07T03:06:41,165 copying src/decanter/core/jobs/task.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,170 copying src/decanter/core/jobs/experiment.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,174 copying src/decanter/core/jobs/__init__.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,178 copying src/decanter/core/jobs/job.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,181 copying src/decanter/core/jobs/data_setup.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,185 copying src/decanter/core/jobs/data_upload.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,189 copying src/decanter/core/jobs/predict_result.py -> build/lib/decanter/core/jobs
2022-03-07T03:06:41,194 creating build/lib/decanter/core/core_api
2022-03-07T03:06:41,195 copying src/decanter/core/core_api/body_obj.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,200 copying src/decanter/core/core_api/setup_input.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,203 copying src/decanter/core/core_api/worker.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,206 copying src/decanter/core/core_api/api.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,210 copying src/decanter/core/core_api/__init__.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,213 copying src/decanter/core/core_api/predict_input.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,216 copying src/decanter/core/core_api/train_input.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,220 copying src/decanter/core/core_api/model.py -> build/lib/decanter/core/core_api
2022-03-07T03:06:41,242 /usr/local/lib/python3.7/dist-packages/setuptools/command/install.py:37: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
2022-03-07T03:06:41,242 setuptools.SetuptoolsDeprecationWarning,
2022-03-07T03:06:41,246 running install
2022-03-07T03:06:41,309 running install_lib
2022-03-07T03:06:41,316 creating build/bdist.linux-armv7l
2022-03-07T03:06:41,317 creating build/bdist.linux-armv7l/wheel
2022-03-07T03:06:41,320 creating build/bdist.linux-armv7l/wheel/decanter
2022-03-07T03:06:41,323 creating build/bdist.linux-armv7l/wheel/decanter/core
2022-03-07T03:06:41,331 creating build/bdist.linux-armv7l/wheel/decanter/core/enums
2022-03-07T03:06:41,357 creating build/bdist.linux-armv7l/wheel/decanter/core/extra
2022-03-07T03:06:41,376 creating build/bdist.linux-armv7l/wheel/decanter/core/jobs
2022-03-07T03:06:41,405 creating build/bdist.linux-armv7l/wheel/decanter/core/core_api
2022-03-07T03:06:41,441 running install_egg_info
2022-03-07T03:06:41,482 running egg_info
2022-03-07T03:06:41,540 writing manifest file 'src/decanter_ai_core_sdk.egg-info/SOURCES.txt'
2022-03-07T03:06:41,543 Copying src/decanter_ai_core_sdk.egg-info to build/bdist.linux-armv7l/wheel/decanter_ai_core_sdk-1.1.9-py3.7.egg-info
2022-03-07T03:06:41,562 running install_scripts
2022-03-07T03:06:42,025 Building wheel for decanter-ai-core-sdk (setup.py): finished with status 'done'
2022-03-07T03:06:42,034 Created wheel for decanter-ai-core-sdk: filename=decanter_ai_core_sdk-1.1.9-py3-none-any.whl size=41044 sha256=2999c6d9f6223b81437133618b2e7fab7ecd080a02d75ae89710572ac2191a42
2022-03-07T03:06:42,036 Stored in directory: /tmp/pip-ephem-wheel-cache-lirroz6k/wheels/28/7f/92/7393fd327f0a07ab3fc1dd8fbd8dc98d1d831f4466b56cf4b2
2022-03-07T03:06:42,062 Successfully built decanter-ai-core-sdk
2022-03-07T03:06:42,074 Removed build tracker: '/tmp/pip-req-tracker-o07ks40j'