%global _empty_manifest_terminate_build 0 Name: python-ibmcloudsql Version: 0.5.13 Release: 1 Summary: Python client for interacting with IBM Cloud Data Engine service License: Apache 2.0 URL: https://github.com/IBM-Cloud/sql-query-clients Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a5/8c/785034007f3da2e28d2819734efb978248c637000041218e696721ea3ce8/ibmcloudsql-0.5.13.tar.gz BuildArch: noarch %description # ibmcloudsql Allows you to run SQL statements in the IBM Cloud on data stored on object storage:: ## Building and testing the library locally ### Set up Python environment Run `source ./setup_env.sh` which creates and activates a clean virtual Python environment. It uses Python 2.7 by default. Adapt line 2 inside the script if you want a different version. ### Install the local code in your Python environment Run `./_install.sh`. ### Test the library locally 1. Create a file `ibmcloudsql/test_credentials.py` with the following three lines and your according properties: ``` apikey='' instance_crn='' result_location='' ... ``` see details in the template file 2. Run `python ibmcloudsql/test.py`. ### Packaging and publishing distribution 1. Make sure to increase `version=...` in `setup.py` before creating a new package. 2. Run `package.sh`. It will prompt for user and password that must be authorized for package `ibmcloudsql` on pypi.org. ## Example usage ``` import ibmcloudsql my_ibmcloud_apikey = '' my_instance_crn='' my_target_cos_url='//[]>' sqlClient = SQLQuery(my_ibmcloud_apikey, my_instance_crn) sqlClient.run_sql('SELECT * FROM cos://us-geo/sql/orders.parquet STORED AS PARQUET LIMIT 5 INTO {} STORED AS CSV'.format(my_target_cos_url)).head() ``` ## Demo notebook You can use IBM Watson Studio with the following [demo notebook](https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/440b3665-367f-4fc9-86d8-4fe7eae13b18/view?access_token=3c1471a6970890fe28cadf118215df44e82c2472a83c4051e3ff80fe505448ed) that shows some elaborate examples of using various aspects of ibmcloudsql. ## SQLQuery method list * `SQLQuery(api_key, instance_crn, target_cos_url=None, token=None, client_info='')` Constructor * `logon(force=False, token=None)` Needs to be called before any other method below. It exchanges the `api_key` set at initialization for a temporary oauth token. The invocation is a No-Op if previous logon is less than 5 minutes ago. You can force logon anyway with optional paramater `force=True`. When you have inititialized the client without an `api_key` but instead specified a custom `token` then you can specify a fresh `token to logon method to update the client with that. * `submit_sql(sql_text, pagesize=None)` Returns `jobId`as string. Optional pagesize parameter (in rows) for paginated result objects. * `wait_for_job(jobId)` Waits for job to end and returns job completion state (either `completed` or `failed`) * `get_result(jobId, pagenumber=None)` returns SQL result data frame for entire result or for specified page of results. * `list_results(jobId)` Returns a data frame with the list of result objects written * `delete_result(jobId)` Deletes all result set objects in cloud object storage for the given jobId * `rename_exact_result(jobId)` Renames single partitioned query result to exact single object name without folder hierarchy. * `get_job(jobId)` Returns details for the given SQL job as a json object * `get_jobs()` Returns the list of recent 30 submitted SQL jobs with all details as a data frame * `run_sql(sql_text)` Compound method that calls `submit_sql`, `wait_for_job` and `wait_for_job` in sequenceA * `sql_ui_link()` Returns browser link for Data Engine web console for currently configured instance * `get_cos_summary(cos_url)` Returns summary for stored number of objects and volume for a given cos url as a json * `list_cos_objects(cos_url)` Returns a data frame with the list of objects found in the given cos url * `export_job_history(cos_url)` Exports new jobs as parquet file to the given `cos_url`. * `export_tags_for_cos_objects(cos_url, export_target_cos_file)` Exports all objects as a parquet file to the given `cos_url` that have tags configured along with the value for each tag. ## Exceptions * `RateLimitedException(message)` raised when jobs can't be submitted due to 429 / Plan limit for concurrent queries has been reached ## Constructor options * `api_key`: IAM API key. When this parameter is set to `None` then you must specify an own valid IAM otauth token in the parameter `token`. * `instance_crn`: Data Engine instance CRN identifier * `target_cos_url`: Optional default target URL. Don't use when you want to provide target URL in SQL statement text. * `token`: Optional custom IAM oauth token. When you specify this then you must set `api_key` parameter to `None`. * `client_info`: Optional string to identify your client application in IBM Cloud for PD reasons. * `max_tries`: Optional integer to specify maximum attempts when dealing with request rate limit. Default value is `1`, which means it will through exception `RateLimitedException` when response status code is `429`. It will enable _exponential backoff_ when specifying any positive number greater than `1`. For instance, given `max_tries=5`, assuming it will get response status code `429` for 4 times until the 5th attempt will get response status code `201`, the wait time will be `2s`, `4s`, `8s` and `16s` for each attempts. ## Limitations Data Engine Python SDK does not support Pyinstaller. %package -n python3-ibmcloudsql Summary: Python client for interacting with IBM Cloud Data Engine service Provides: python-ibmcloudsql BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-ibmcloudsql # ibmcloudsql Allows you to run SQL statements in the IBM Cloud on data stored on object storage:: ## Building and testing the library locally ### Set up Python environment Run `source ./setup_env.sh` which creates and activates a clean virtual Python environment. It uses Python 2.7 by default. Adapt line 2 inside the script if you want a different version. ### Install the local code in your Python environment Run `./_install.sh`. ### Test the library locally 1. Create a file `ibmcloudsql/test_credentials.py` with the following three lines and your according properties: ``` apikey='' instance_crn='' result_location='' ... ``` see details in the template file 2. Run `python ibmcloudsql/test.py`. ### Packaging and publishing distribution 1. Make sure to increase `version=...` in `setup.py` before creating a new package. 2. Run `package.sh`. It will prompt for user and password that must be authorized for package `ibmcloudsql` on pypi.org. ## Example usage ``` import ibmcloudsql my_ibmcloud_apikey = '' my_instance_crn='' my_target_cos_url='//[]>' sqlClient = SQLQuery(my_ibmcloud_apikey, my_instance_crn) sqlClient.run_sql('SELECT * FROM cos://us-geo/sql/orders.parquet STORED AS PARQUET LIMIT 5 INTO {} STORED AS CSV'.format(my_target_cos_url)).head() ``` ## Demo notebook You can use IBM Watson Studio with the following [demo notebook](https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/440b3665-367f-4fc9-86d8-4fe7eae13b18/view?access_token=3c1471a6970890fe28cadf118215df44e82c2472a83c4051e3ff80fe505448ed) that shows some elaborate examples of using various aspects of ibmcloudsql. ## SQLQuery method list * `SQLQuery(api_key, instance_crn, target_cos_url=None, token=None, client_info='')` Constructor * `logon(force=False, token=None)` Needs to be called before any other method below. It exchanges the `api_key` set at initialization for a temporary oauth token. The invocation is a No-Op if previous logon is less than 5 minutes ago. You can force logon anyway with optional paramater `force=True`. When you have inititialized the client without an `api_key` but instead specified a custom `token` then you can specify a fresh `token to logon method to update the client with that. * `submit_sql(sql_text, pagesize=None)` Returns `jobId`as string. Optional pagesize parameter (in rows) for paginated result objects. * `wait_for_job(jobId)` Waits for job to end and returns job completion state (either `completed` or `failed`) * `get_result(jobId, pagenumber=None)` returns SQL result data frame for entire result or for specified page of results. * `list_results(jobId)` Returns a data frame with the list of result objects written * `delete_result(jobId)` Deletes all result set objects in cloud object storage for the given jobId * `rename_exact_result(jobId)` Renames single partitioned query result to exact single object name without folder hierarchy. * `get_job(jobId)` Returns details for the given SQL job as a json object * `get_jobs()` Returns the list of recent 30 submitted SQL jobs with all details as a data frame * `run_sql(sql_text)` Compound method that calls `submit_sql`, `wait_for_job` and `wait_for_job` in sequenceA * `sql_ui_link()` Returns browser link for Data Engine web console for currently configured instance * `get_cos_summary(cos_url)` Returns summary for stored number of objects and volume for a given cos url as a json * `list_cos_objects(cos_url)` Returns a data frame with the list of objects found in the given cos url * `export_job_history(cos_url)` Exports new jobs as parquet file to the given `cos_url`. * `export_tags_for_cos_objects(cos_url, export_target_cos_file)` Exports all objects as a parquet file to the given `cos_url` that have tags configured along with the value for each tag. ## Exceptions * `RateLimitedException(message)` raised when jobs can't be submitted due to 429 / Plan limit for concurrent queries has been reached ## Constructor options * `api_key`: IAM API key. When this parameter is set to `None` then you must specify an own valid IAM otauth token in the parameter `token`. * `instance_crn`: Data Engine instance CRN identifier * `target_cos_url`: Optional default target URL. Don't use when you want to provide target URL in SQL statement text. * `token`: Optional custom IAM oauth token. When you specify this then you must set `api_key` parameter to `None`. * `client_info`: Optional string to identify your client application in IBM Cloud for PD reasons. * `max_tries`: Optional integer to specify maximum attempts when dealing with request rate limit. Default value is `1`, which means it will through exception `RateLimitedException` when response status code is `429`. It will enable _exponential backoff_ when specifying any positive number greater than `1`. For instance, given `max_tries=5`, assuming it will get response status code `429` for 4 times until the 5th attempt will get response status code `201`, the wait time will be `2s`, `4s`, `8s` and `16s` for each attempts. ## Limitations Data Engine Python SDK does not support Pyinstaller. %package help Summary: Development documents and examples for ibmcloudsql Provides: python3-ibmcloudsql-doc %description help # ibmcloudsql Allows you to run SQL statements in the IBM Cloud on data stored on object storage:: ## Building and testing the library locally ### Set up Python environment Run `source ./setup_env.sh` which creates and activates a clean virtual Python environment. It uses Python 2.7 by default. Adapt line 2 inside the script if you want a different version. ### Install the local code in your Python environment Run `./_install.sh`. ### Test the library locally 1. Create a file `ibmcloudsql/test_credentials.py` with the following three lines and your according properties: ``` apikey='' instance_crn='' result_location='' ... ``` see details in the template file 2. Run `python ibmcloudsql/test.py`. ### Packaging and publishing distribution 1. Make sure to increase `version=...` in `setup.py` before creating a new package. 2. Run `package.sh`. It will prompt for user and password that must be authorized for package `ibmcloudsql` on pypi.org. ## Example usage ``` import ibmcloudsql my_ibmcloud_apikey = '' my_instance_crn='' my_target_cos_url='//[]>' sqlClient = SQLQuery(my_ibmcloud_apikey, my_instance_crn) sqlClient.run_sql('SELECT * FROM cos://us-geo/sql/orders.parquet STORED AS PARQUET LIMIT 5 INTO {} STORED AS CSV'.format(my_target_cos_url)).head() ``` ## Demo notebook You can use IBM Watson Studio with the following [demo notebook](https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/440b3665-367f-4fc9-86d8-4fe7eae13b18/view?access_token=3c1471a6970890fe28cadf118215df44e82c2472a83c4051e3ff80fe505448ed) that shows some elaborate examples of using various aspects of ibmcloudsql. ## SQLQuery method list * `SQLQuery(api_key, instance_crn, target_cos_url=None, token=None, client_info='')` Constructor * `logon(force=False, token=None)` Needs to be called before any other method below. It exchanges the `api_key` set at initialization for a temporary oauth token. The invocation is a No-Op if previous logon is less than 5 minutes ago. You can force logon anyway with optional paramater `force=True`. When you have inititialized the client without an `api_key` but instead specified a custom `token` then you can specify a fresh `token to logon method to update the client with that. * `submit_sql(sql_text, pagesize=None)` Returns `jobId`as string. Optional pagesize parameter (in rows) for paginated result objects. * `wait_for_job(jobId)` Waits for job to end and returns job completion state (either `completed` or `failed`) * `get_result(jobId, pagenumber=None)` returns SQL result data frame for entire result or for specified page of results. * `list_results(jobId)` Returns a data frame with the list of result objects written * `delete_result(jobId)` Deletes all result set objects in cloud object storage for the given jobId * `rename_exact_result(jobId)` Renames single partitioned query result to exact single object name without folder hierarchy. * `get_job(jobId)` Returns details for the given SQL job as a json object * `get_jobs()` Returns the list of recent 30 submitted SQL jobs with all details as a data frame * `run_sql(sql_text)` Compound method that calls `submit_sql`, `wait_for_job` and `wait_for_job` in sequenceA * `sql_ui_link()` Returns browser link for Data Engine web console for currently configured instance * `get_cos_summary(cos_url)` Returns summary for stored number of objects and volume for a given cos url as a json * `list_cos_objects(cos_url)` Returns a data frame with the list of objects found in the given cos url * `export_job_history(cos_url)` Exports new jobs as parquet file to the given `cos_url`. * `export_tags_for_cos_objects(cos_url, export_target_cos_file)` Exports all objects as a parquet file to the given `cos_url` that have tags configured along with the value for each tag. ## Exceptions * `RateLimitedException(message)` raised when jobs can't be submitted due to 429 / Plan limit for concurrent queries has been reached ## Constructor options * `api_key`: IAM API key. When this parameter is set to `None` then you must specify an own valid IAM otauth token in the parameter `token`. * `instance_crn`: Data Engine instance CRN identifier * `target_cos_url`: Optional default target URL. Don't use when you want to provide target URL in SQL statement text. * `token`: Optional custom IAM oauth token. When you specify this then you must set `api_key` parameter to `None`. * `client_info`: Optional string to identify your client application in IBM Cloud for PD reasons. * `max_tries`: Optional integer to specify maximum attempts when dealing with request rate limit. Default value is `1`, which means it will through exception `RateLimitedException` when response status code is `429`. It will enable _exponential backoff_ when specifying any positive number greater than `1`. For instance, given `max_tries=5`, assuming it will get response status code `429` for 4 times until the 5th attempt will get response status code `201`, the wait time will be `2s`, `4s`, `8s` and `16s` for each attempts. ## Limitations Data Engine Python SDK does not support Pyinstaller. %prep %autosetup -n ibmcloudsql-0.5.13 %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-ibmcloudsql -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 0.5.13-1 - Package Spec generated