%global _empty_manifest_terminate_build 0 Name: python-pandablob Version: 0.0.5 Release: 1 Summary: Functions to easily transform Azure blobs into pandas DataFrames and vice versa. License: MIT URL: https://github.com/uijl/pandablob Source0: https://mirrors.nju.edu.cn/pypi/web/packages/44/b4/f0652652709c410ce3039df278757f807d01897db47a1b3e1cb915634872/pandablob-0.0.5a.tar.gz BuildArch: noarch %description ![PyTest](https://github.com/uijl/pandablob/workflows/PyTest/badge.svg) [![PyPI Latest Release](https://img.shields.io/pypi/v/pandablob.svg)](https://pypi.org/project/pandablob/) [![Downloads](https://pepy.tech/badge/pandablob)](https://pepy.tech/project/pandablob) # PandaBlob Functions to easily transform Azure blobs into pandas DataFrames and vice versa. ## Installation Installing PandaBlob via [pip](https://pip.pypa.io) is the preferred method, as it will always install the most recent stable release. If you do not have [pip](https://pip.pypa.io) installed, this [Python installation guide](http://docs.python-guide.org/en/latest/starting/installation/) can guide you through the process. To install PandaBlob, run this command in your terminal: ```bash # Use pip to install PandaBlob pip install pandablob ``` Downloading and installing PandaBlob from source is also possible, follow the code below. ```bash # Download the package git clone https://github.com/uijl/pandablob # Go to the correct folder cd pandablob # Install package pip install -e . ``` ## Usage The code snip below shows how you can use PandaBlob, all you need is a _[BlobClient](https://docs.microsoft.com/nl-nl/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python)_ and possibly a pandas DataFrame or some keyword arguments for pandas. ```python # Import the Azure SDK and pandablob import pandablob from azure.storage.blob import ContainerClient # Your Azure Credentials account_url = "https://my_account_url.blob.core.windows.net/" token = "your_key_string" container = "your_container" blobname = "your_blob_name.csv" container_client = ContainerClient(account_url, container, credential=token) blob_client = container_client.get_blob_client(blob=blobname) # Specifiy your pandas keyword arguments pandas_kwargs = {"index_col": 0} # Read the blob as a pandas DataFrame df = pandablob.blob_to_df(blob_client, pandas_kwargs) ``` ## Potential errors There are three common errors that can be returned. Two are related to the blob storage and one because of the current limitations of pandablob. - **ResourceExistsError** - If the specified blob is already on the blob, this error is returned. There are two options, you can add the `overwrite=True` argument to your `df_to_blob` function or you can catch the exception. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceExistsError`; - **ResourceNotFoundError** - If the specified blob is not found, this error is returned. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceNotFoundError`; - **TypeError** - This error is returned by pandablob if you want to upload or download an extensiontype that is not yet supported. Currently only the following extensions are supported: `.csv` `.json` `.txt`, `.xls` and `.xlsx`. ## To do list: Some other stuff that needs to be done: - [ ] Include other files; - [x] Easier downloading a .csv file; - [x] Added MIT license. %package -n python3-pandablob Summary: Functions to easily transform Azure blobs into pandas DataFrames and vice versa. Provides: python-pandablob BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pandablob ![PyTest](https://github.com/uijl/pandablob/workflows/PyTest/badge.svg) [![PyPI Latest Release](https://img.shields.io/pypi/v/pandablob.svg)](https://pypi.org/project/pandablob/) [![Downloads](https://pepy.tech/badge/pandablob)](https://pepy.tech/project/pandablob) # PandaBlob Functions to easily transform Azure blobs into pandas DataFrames and vice versa. ## Installation Installing PandaBlob via [pip](https://pip.pypa.io) is the preferred method, as it will always install the most recent stable release. If you do not have [pip](https://pip.pypa.io) installed, this [Python installation guide](http://docs.python-guide.org/en/latest/starting/installation/) can guide you through the process. To install PandaBlob, run this command in your terminal: ```bash # Use pip to install PandaBlob pip install pandablob ``` Downloading and installing PandaBlob from source is also possible, follow the code below. ```bash # Download the package git clone https://github.com/uijl/pandablob # Go to the correct folder cd pandablob # Install package pip install -e . ``` ## Usage The code snip below shows how you can use PandaBlob, all you need is a _[BlobClient](https://docs.microsoft.com/nl-nl/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python)_ and possibly a pandas DataFrame or some keyword arguments for pandas. ```python # Import the Azure SDK and pandablob import pandablob from azure.storage.blob import ContainerClient # Your Azure Credentials account_url = "https://my_account_url.blob.core.windows.net/" token = "your_key_string" container = "your_container" blobname = "your_blob_name.csv" container_client = ContainerClient(account_url, container, credential=token) blob_client = container_client.get_blob_client(blob=blobname) # Specifiy your pandas keyword arguments pandas_kwargs = {"index_col": 0} # Read the blob as a pandas DataFrame df = pandablob.blob_to_df(blob_client, pandas_kwargs) ``` ## Potential errors There are three common errors that can be returned. Two are related to the blob storage and one because of the current limitations of pandablob. - **ResourceExistsError** - If the specified blob is already on the blob, this error is returned. There are two options, you can add the `overwrite=True` argument to your `df_to_blob` function or you can catch the exception. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceExistsError`; - **ResourceNotFoundError** - If the specified blob is not found, this error is returned. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceNotFoundError`; - **TypeError** - This error is returned by pandablob if you want to upload or download an extensiontype that is not yet supported. Currently only the following extensions are supported: `.csv` `.json` `.txt`, `.xls` and `.xlsx`. ## To do list: Some other stuff that needs to be done: - [ ] Include other files; - [x] Easier downloading a .csv file; - [x] Added MIT license. %package help Summary: Development documents and examples for pandablob Provides: python3-pandablob-doc %description help ![PyTest](https://github.com/uijl/pandablob/workflows/PyTest/badge.svg) [![PyPI Latest Release](https://img.shields.io/pypi/v/pandablob.svg)](https://pypi.org/project/pandablob/) [![Downloads](https://pepy.tech/badge/pandablob)](https://pepy.tech/project/pandablob) # PandaBlob Functions to easily transform Azure blobs into pandas DataFrames and vice versa. ## Installation Installing PandaBlob via [pip](https://pip.pypa.io) is the preferred method, as it will always install the most recent stable release. If you do not have [pip](https://pip.pypa.io) installed, this [Python installation guide](http://docs.python-guide.org/en/latest/starting/installation/) can guide you through the process. To install PandaBlob, run this command in your terminal: ```bash # Use pip to install PandaBlob pip install pandablob ``` Downloading and installing PandaBlob from source is also possible, follow the code below. ```bash # Download the package git clone https://github.com/uijl/pandablob # Go to the correct folder cd pandablob # Install package pip install -e . ``` ## Usage The code snip below shows how you can use PandaBlob, all you need is a _[BlobClient](https://docs.microsoft.com/nl-nl/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python)_ and possibly a pandas DataFrame or some keyword arguments for pandas. ```python # Import the Azure SDK and pandablob import pandablob from azure.storage.blob import ContainerClient # Your Azure Credentials account_url = "https://my_account_url.blob.core.windows.net/" token = "your_key_string" container = "your_container" blobname = "your_blob_name.csv" container_client = ContainerClient(account_url, container, credential=token) blob_client = container_client.get_blob_client(blob=blobname) # Specifiy your pandas keyword arguments pandas_kwargs = {"index_col": 0} # Read the blob as a pandas DataFrame df = pandablob.blob_to_df(blob_client, pandas_kwargs) ``` ## Potential errors There are three common errors that can be returned. Two are related to the blob storage and one because of the current limitations of pandablob. - **ResourceExistsError** - If the specified blob is already on the blob, this error is returned. There are two options, you can add the `overwrite=True` argument to your `df_to_blob` function or you can catch the exception. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceExistsError`; - **ResourceNotFoundError** - If the specified blob is not found, this error is returned. If you wish to enter it in an except statement, you can import it using `from azure.core.exceptions import ResourceNotFoundError`; - **TypeError** - This error is returned by pandablob if you want to upload or download an extensiontype that is not yet supported. Currently only the following extensions are supported: `.csv` `.json` `.txt`, `.xls` and `.xlsx`. ## To do list: Some other stuff that needs to be done: - [ ] Include other files; - [x] Easier downloading a .csv file; - [x] Added MIT license. %prep %autosetup -n pandablob-0.0.5 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-pandablob -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.0.5-1 - Package Spec generated