automatic import of python-dowml

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+/dowml-1.9.0.tar.gz
diff --git a/python-dowml.spec b/python-dowml.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-dowml
+Version:	1.9.0
+Release:	1
+Summary:	Submit existing Decision Optimization instances to WML
+License:	Apache License 2.0
+URL:		https://github.com/nodet/dowml
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/10/7b/5df80f02354702dedea61cb29b925e7bc6bb27d4adc2562a420d3e3c0067/dowml-1.9.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-ibm-watson-machine-learning
+
+%description
+cancel  details  exit  inline  jobs  output   shell  solve   time  version
+delete  dump     help  inputs  log   outputs  size   status  type  wait
+dowml> type
+Current model type: cplex.
+Known types: cplex, cpo, opl, docplex.
+dowml> size
+Current size: S.
+Known sizes: S, M, L, XL.
+dowml> inputs inline
+dowml> solve examples/afiro.mps
+Job id: cd494377-4843-40a4-ae84-ede7f8c16eda
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: queued      cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> wait
+Job is running.
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> log
+[2022-06-28T09:59:08Z, INFO] CPLEX version 22010000
+[2022-06-28T09:59:08Z, WARNING] Changed parameter CPX_PARAM_THREADS from 0 to 1
+[2022-06-28T09:59:08Z, INFO] Param[1,067] = 1
+[2022-06-28T09:59:08Z, INFO] Param[1,130] = UTF-8
+[2022-06-28T09:59:08Z, INFO] Param[1,132] = -1
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Selected objective sense:  MINIMIZE
+[2022-06-28T09:59:08Z, INFO] Selected objective  name:  obj
+[2022-06-28T09:59:08Z, INFO] Selected RHS        name:  rhs
+[2022-06-28T09:59:08Z, INFO] Version identifier: 22.1.0.0 | 2022-03-30 | 54982fbec
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Threads                                 1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Output_CloneLog                         -1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Read_APIEncoding                        "UTF-8"
+[2022-06-28T09:59:08Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:08Z, INFO] LP Presolve eliminated 9 rows and 10 columns.
+[2022-06-28T09:59:08Z, INFO] Aggregator did 7 substitutions.
+[2022-06-28T09:59:08Z, INFO] Reduced LP has 11 rows, 15 columns, and 37 nonzeros.
+[2022-06-28T09:59:08Z, INFO] Presolve time = 0.00 sec. (0.03 ticks)
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Iteration log . . .
+[2022-06-28T09:59:08Z, INFO] Iteration:     1   Scaled dual infeas =             1.200000
+[2022-06-28T09:59:08Z, INFO] Iteration:     5   Dual objective     =          -464.753143
+[2022-06-28T09:59:09Z, INFO] There are no bound infeasibilities.
+[2022-06-28T09:59:09Z, INFO] There are no reduced-cost infeasibilities.
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) Ax-b resid.          = 1.77636e-14 (1.77636e-14)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) c-B'pi resid.        = 5.55112e-17 (5.55112e-17)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |x|                  = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |slack|              = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |pi|                 = 0.942857 (1.88571)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |red-cost|           = 10 (10)
+[2022-06-28T09:59:09Z, INFO] Condition number of scaled basis            = 1.5e+01
+[2022-06-28T09:59:09Z, INFO] optimal (1)
+dowml> type docplex
+dowml> solve examples/markshare.py examples/markshare1.mps.gz
+Job id: 6520e72b-727c-4bfe-adb5-a40d96cf5910
+dowml> wait
+Job is queued.
+Job is running..
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO]         Nodes                                         Cuts/
+[2022-06-28T09:59:17Z, INFO]    Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] *     0+    0                         7286.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     6     7286.0000        0.0000       11  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          263.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          230.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 15       15  100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 16       23  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          193.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] Detecting symmetries...
+[2022-06-28T09:59:17Z, INFO]       0     2        0.0000     7      193.0000        0.0000       23  100.00%
+[2022-06-28T09:59:17Z, INFO] Elapsed time = 0.01 sec. (2.91 ticks, tree = 0.01 MB, solutions = 4)
+[2022-06-28T09:59:17Z, INFO] *    70+   59                          166.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *    80+   67                          132.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   190+  155                          111.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   220+  166                           96.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   320+  240                           71.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  305                           67.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  303                           66.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   491   310      integral     0       38.0000        0.0000     1112  100.00%
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Performing restart 1
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Repeating presolve.
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.14 ticks)
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.19 ticks)
+[2022-06-28T09:59:17Z, INFO] Represolve time = 0.00 sec. (0.81 ticks)
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 17     3422  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     8       38.0000      Cuts: 17     3429  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3436  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3441  100.00%
+[2022-06-28T09:59:18Z, INFO]    3918  1669        0.0000     6       38.0000        0.0000     8018  100.00%
+[2022-06-28T09:59:18Z, INFO]    6508  2914        0.0000     6       38.0000        0.0000    14256  100.00%
+[2022-06-28T09:59:19Z, INFO]    9718  4470        0.0000     6       38.0000        0.0000    22692  100.00%
+[2022-06-28T09:59:19Z, INFO] Began writing nodes to disk (directory ./cpxY2cKqj created)
+[2022-06-28T09:59:22Z, INFO]   10638  4956       13.6062     6       38.0000        0.0000    25327  100.00%
+[2022-06-28T09:59:23Z, INFO]   13478  6155        0.0000     6       38.0000        0.0000    33717  100.00%
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+     1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+=>   2: completed   6520e72b-727c-4bfe-adb5-a40d96cf5910  2022-06-28 11:59:13  docplex  22.1   S     markshare.py, markshare1.mps.gz
+dowml> dump
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/details.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare.py
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare1.mps.gz
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/model.lp
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/solution.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/kpis.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/stats.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/log.txt
+dowml> shell ls -l *-*-*-*-*
+total 88
+-rw-rw-r--  1 nodet  staff  5506 Jun 28 11:59 details.json
+-rw-rw-r--  1 nodet  staff    37 Jun 28 11:59 kpis.csv
+-rw-rw-r--  1 nodet  staff  7299 Jun 28 11:59 log.txt
+-rw-rw-r--  1 nodet  staff   671 Jun 28 11:59 markshare.py
+-rw-rw-r--  1 nodet  staff  1607 Jun 28 11:59 markshare1.mps.gz
+-rw-rw-r--  1 nodet  staff  4197 Jun 28 11:59 model.lp
+-rw-rw-r--  1 nodet  staff  1769 Jun 28 11:59 solution.json
+-rw-rw-r--  1 nodet  staff   344 Jun 28 11:59 stats.csv
+dowml> delete *
+```
+## WML credentials
+The DOWML client requires some information in order to connect to the Watson
+Machine Learning service.  Two pieces of information are required, and the others
+are optional.
+### Required items
+- The `apikey` is a secret that identifies the IBM Cloud user. One typically creates
+  one key per application or service, in order to be able to revoke them individually
+  if needed.
+  To generate such a key, open https://cloud.ibm.com/iam/apikeys, and click the blue
+  'Create an IBM Cloud API key' on the right.
+- The `url` is the base URL for the REST calls to WML.  The possible values are
+  found in https://cloud.ibm.com/apidocs/machine-learning#endpoint-url, 
+  and depend on which region you want to use.
+- As an alternative to the `url` value, you can use a more user-friendly and 
+  easier to remember `region`, with a value that is either `us-south`, `eu-de`,
+  `eu-gb` or `jp-tok`.  From this value, _dowml_ will deduce the correct URL to use.
+  To avoid ambiguities or duplications, it is not allowed to use both `url` and
+  `region`.
+### Optional items
+Watson Studio and Watson Machine Learning use _spaces_ to group together, and
+isolate from each other, the assets that belong to a single project.  These assets 
+include the data files submitted, the results of the jobs, and the _deployments_
+(software and hardware configurations) that run these jobs.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.
+To create a new space, the DOWML client will need both `cos_resource_crn` and
+`ml_instance_crn` to have been specified in the credentials.
+- `space_id`: identifier of an existing space to connect to.  Navigate to the 
+  'Spaces' tab of your Watson Studio site (e.g. 
+  https://eu-de.dataplatform.cloud.ibm.com/ml-runtime/spaces if you are using
+  the instance in Germany), right-click on the name of an existing space to
+  copy the link. The id of the space is the string of numbers, letters and dashes
+  between the last `/` and the `?`.
+- `cos_resource_crn`: WML needs to store some data in a Cloud Object Storage 
+  instance.  Open
+  https://cloud.ibm.com/resources and locate the 'Storage' section.  Create an
+  instance of the Cloud Object Storage service if needed. Once it's listed on
+  the resource page, click anywhere on the line for that service, except on its
+  name.  This will open a pane on the right which lists the CRN.  Click on the
+  symbol at the right to copy this information.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+- `ml_instance_crn`: similarly, you need to identify an instance of Machine 
+  Learning service to use
+  to solve your jobs.  In the same page https://cloud.ibm.com/resources, open the
+  'Services' section.  The 'Product' columns tells you the type of service.  If
+  you don't have a 'Machine Learning' instance already, create one.  Then click
+  on the corresponding line anywhere except on the name, and copy the CRN displayed
+  in the pane that open on the right.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+## CP4D credentials
+The credentials to connect to the WML service _in a (private) CP4D instance_ are 
+different from those above that pertain to CP4D _as a service_.  The credentials
+look like this:
+```
+{
+   "instance_id": "openshift",
+   "version": "4.0",
+   "url": "...",
+   "username": "...",
+   "apikey": "...",
+   "space_id": "..."
+}
+```
+- The `url` is the URL of your CP4D instance, with no `/` at the end. 
+- The `username` and `apikey` for your user on this cluster.  You can
+get the API key in the 'Profile and settings' dialog that's accessible from your
+avatar menu in the top-right of the screen.
+- `space_id`: the identifier of an existing space to connect to.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.  On CPD,
+unlike for Cloud, no `cos_resource_crn` or `ml_instance_crn` are required.
+## Using data assets in Watson Studio
+The DOWML library has two modes of operation with respect to sending the models
+to the WML service: inline data, or using data assets in Watson Studio.  By default,
+data assets are used for inputs, while inline data is used for outputs. 
+This can be changed with the `inputs` and `outputs` commands.
+With inline data, the model is sent directly to the WML service in the _solve_
+request itself, and the output is part of the job details that are downloaded when
+asking for information about the job.  
+This is the simplest, but it has a number of drawbacks:
+- Sending a large model may take a long time, because of network throughput.  Sending
+a very large REST request is not at all guaranteed to succeed.  Similarly, if your
+job has large outputs, the job may fail while trying to process them.
+- When solving several times the same model (e.g. to evaluate different parameters),
+the model has to be sent each time.
+- In order to display the names of the files that were sent, the _jobs_ command
+needs to request this information, and it comes with the content of the files
+  themselves.  In other words, every _jobs_ command requires downloading the content
+  of all the inline data files for all the jobs that exist in the space.
+Using data assets in Watson Studio as an intermediate step alleviate all these issues:
+- Once the model has been uploaded to Watson Studio, it will be reused for
+subsequent jobs without the need to upload it again.
+- The job requests refer to the files indirectly, via URLs.  Therefore, they don't
+take much space, and listing the jobs doesn't imply to download the content of the
+  files.
+- Uploading to Watson Studio is done through specialized code that doesn't just send a single
+request.  Rather, it divides the upload in multiple reasonably sized chunks that each
+  are uploaded individually, with restart if necessary.  Uploading big files is
+  therefore much less prone to failure.
+
+%package -n python3-dowml
+Summary:	Submit existing Decision Optimization instances to WML
+Provides:	python-dowml
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-dowml
+cancel  details  exit  inline  jobs  output   shell  solve   time  version
+delete  dump     help  inputs  log   outputs  size   status  type  wait
+dowml> type
+Current model type: cplex.
+Known types: cplex, cpo, opl, docplex.
+dowml> size
+Current size: S.
+Known sizes: S, M, L, XL.
+dowml> inputs inline
+dowml> solve examples/afiro.mps
+Job id: cd494377-4843-40a4-ae84-ede7f8c16eda
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: queued      cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> wait
+Job is running.
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> log
+[2022-06-28T09:59:08Z, INFO] CPLEX version 22010000
+[2022-06-28T09:59:08Z, WARNING] Changed parameter CPX_PARAM_THREADS from 0 to 1
+[2022-06-28T09:59:08Z, INFO] Param[1,067] = 1
+[2022-06-28T09:59:08Z, INFO] Param[1,130] = UTF-8
+[2022-06-28T09:59:08Z, INFO] Param[1,132] = -1
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Selected objective sense:  MINIMIZE
+[2022-06-28T09:59:08Z, INFO] Selected objective  name:  obj
+[2022-06-28T09:59:08Z, INFO] Selected RHS        name:  rhs
+[2022-06-28T09:59:08Z, INFO] Version identifier: 22.1.0.0 | 2022-03-30 | 54982fbec
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Threads                                 1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Output_CloneLog                         -1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Read_APIEncoding                        "UTF-8"
+[2022-06-28T09:59:08Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:08Z, INFO] LP Presolve eliminated 9 rows and 10 columns.
+[2022-06-28T09:59:08Z, INFO] Aggregator did 7 substitutions.
+[2022-06-28T09:59:08Z, INFO] Reduced LP has 11 rows, 15 columns, and 37 nonzeros.
+[2022-06-28T09:59:08Z, INFO] Presolve time = 0.00 sec. (0.03 ticks)
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Iteration log . . .
+[2022-06-28T09:59:08Z, INFO] Iteration:     1   Scaled dual infeas =             1.200000
+[2022-06-28T09:59:08Z, INFO] Iteration:     5   Dual objective     =          -464.753143
+[2022-06-28T09:59:09Z, INFO] There are no bound infeasibilities.
+[2022-06-28T09:59:09Z, INFO] There are no reduced-cost infeasibilities.
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) Ax-b resid.          = 1.77636e-14 (1.77636e-14)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) c-B'pi resid.        = 5.55112e-17 (5.55112e-17)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |x|                  = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |slack|              = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |pi|                 = 0.942857 (1.88571)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |red-cost|           = 10 (10)
+[2022-06-28T09:59:09Z, INFO] Condition number of scaled basis            = 1.5e+01
+[2022-06-28T09:59:09Z, INFO] optimal (1)
+dowml> type docplex
+dowml> solve examples/markshare.py examples/markshare1.mps.gz
+Job id: 6520e72b-727c-4bfe-adb5-a40d96cf5910
+dowml> wait
+Job is queued.
+Job is running..
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO]         Nodes                                         Cuts/
+[2022-06-28T09:59:17Z, INFO]    Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] *     0+    0                         7286.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     6     7286.0000        0.0000       11  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          263.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          230.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 15       15  100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 16       23  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          193.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] Detecting symmetries...
+[2022-06-28T09:59:17Z, INFO]       0     2        0.0000     7      193.0000        0.0000       23  100.00%
+[2022-06-28T09:59:17Z, INFO] Elapsed time = 0.01 sec. (2.91 ticks, tree = 0.01 MB, solutions = 4)
+[2022-06-28T09:59:17Z, INFO] *    70+   59                          166.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *    80+   67                          132.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   190+  155                          111.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   220+  166                           96.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   320+  240                           71.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  305                           67.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  303                           66.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   491   310      integral     0       38.0000        0.0000     1112  100.00%
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Performing restart 1
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Repeating presolve.
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.14 ticks)
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.19 ticks)
+[2022-06-28T09:59:17Z, INFO] Represolve time = 0.00 sec. (0.81 ticks)
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 17     3422  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     8       38.0000      Cuts: 17     3429  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3436  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3441  100.00%
+[2022-06-28T09:59:18Z, INFO]    3918  1669        0.0000     6       38.0000        0.0000     8018  100.00%
+[2022-06-28T09:59:18Z, INFO]    6508  2914        0.0000     6       38.0000        0.0000    14256  100.00%
+[2022-06-28T09:59:19Z, INFO]    9718  4470        0.0000     6       38.0000        0.0000    22692  100.00%
+[2022-06-28T09:59:19Z, INFO] Began writing nodes to disk (directory ./cpxY2cKqj created)
+[2022-06-28T09:59:22Z, INFO]   10638  4956       13.6062     6       38.0000        0.0000    25327  100.00%
+[2022-06-28T09:59:23Z, INFO]   13478  6155        0.0000     6       38.0000        0.0000    33717  100.00%
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+     1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+=>   2: completed   6520e72b-727c-4bfe-adb5-a40d96cf5910  2022-06-28 11:59:13  docplex  22.1   S     markshare.py, markshare1.mps.gz
+dowml> dump
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/details.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare.py
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare1.mps.gz
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/model.lp
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/solution.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/kpis.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/stats.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/log.txt
+dowml> shell ls -l *-*-*-*-*
+total 88
+-rw-rw-r--  1 nodet  staff  5506 Jun 28 11:59 details.json
+-rw-rw-r--  1 nodet  staff    37 Jun 28 11:59 kpis.csv
+-rw-rw-r--  1 nodet  staff  7299 Jun 28 11:59 log.txt
+-rw-rw-r--  1 nodet  staff   671 Jun 28 11:59 markshare.py
+-rw-rw-r--  1 nodet  staff  1607 Jun 28 11:59 markshare1.mps.gz
+-rw-rw-r--  1 nodet  staff  4197 Jun 28 11:59 model.lp
+-rw-rw-r--  1 nodet  staff  1769 Jun 28 11:59 solution.json
+-rw-rw-r--  1 nodet  staff   344 Jun 28 11:59 stats.csv
+dowml> delete *
+```
+## WML credentials
+The DOWML client requires some information in order to connect to the Watson
+Machine Learning service.  Two pieces of information are required, and the others
+are optional.
+### Required items
+- The `apikey` is a secret that identifies the IBM Cloud user. One typically creates
+  one key per application or service, in order to be able to revoke them individually
+  if needed.
+  To generate such a key, open https://cloud.ibm.com/iam/apikeys, and click the blue
+  'Create an IBM Cloud API key' on the right.
+- The `url` is the base URL for the REST calls to WML.  The possible values are
+  found in https://cloud.ibm.com/apidocs/machine-learning#endpoint-url, 
+  and depend on which region you want to use.
+- As an alternative to the `url` value, you can use a more user-friendly and 
+  easier to remember `region`, with a value that is either `us-south`, `eu-de`,
+  `eu-gb` or `jp-tok`.  From this value, _dowml_ will deduce the correct URL to use.
+  To avoid ambiguities or duplications, it is not allowed to use both `url` and
+  `region`.
+### Optional items
+Watson Studio and Watson Machine Learning use _spaces_ to group together, and
+isolate from each other, the assets that belong to a single project.  These assets 
+include the data files submitted, the results of the jobs, and the _deployments_
+(software and hardware configurations) that run these jobs.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.
+To create a new space, the DOWML client will need both `cos_resource_crn` and
+`ml_instance_crn` to have been specified in the credentials.
+- `space_id`: identifier of an existing space to connect to.  Navigate to the 
+  'Spaces' tab of your Watson Studio site (e.g. 
+  https://eu-de.dataplatform.cloud.ibm.com/ml-runtime/spaces if you are using
+  the instance in Germany), right-click on the name of an existing space to
+  copy the link. The id of the space is the string of numbers, letters and dashes
+  between the last `/` and the `?`.
+- `cos_resource_crn`: WML needs to store some data in a Cloud Object Storage 
+  instance.  Open
+  https://cloud.ibm.com/resources and locate the 'Storage' section.  Create an
+  instance of the Cloud Object Storage service if needed. Once it's listed on
+  the resource page, click anywhere on the line for that service, except on its
+  name.  This will open a pane on the right which lists the CRN.  Click on the
+  symbol at the right to copy this information.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+- `ml_instance_crn`: similarly, you need to identify an instance of Machine 
+  Learning service to use
+  to solve your jobs.  In the same page https://cloud.ibm.com/resources, open the
+  'Services' section.  The 'Product' columns tells you the type of service.  If
+  you don't have a 'Machine Learning' instance already, create one.  Then click
+  on the corresponding line anywhere except on the name, and copy the CRN displayed
+  in the pane that open on the right.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+## CP4D credentials
+The credentials to connect to the WML service _in a (private) CP4D instance_ are 
+different from those above that pertain to CP4D _as a service_.  The credentials
+look like this:
+```
+{
+   "instance_id": "openshift",
+   "version": "4.0",
+   "url": "...",
+   "username": "...",
+   "apikey": "...",
+   "space_id": "..."
+}
+```
+- The `url` is the URL of your CP4D instance, with no `/` at the end. 
+- The `username` and `apikey` for your user on this cluster.  You can
+get the API key in the 'Profile and settings' dialog that's accessible from your
+avatar menu in the top-right of the screen.
+- `space_id`: the identifier of an existing space to connect to.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.  On CPD,
+unlike for Cloud, no `cos_resource_crn` or `ml_instance_crn` are required.
+## Using data assets in Watson Studio
+The DOWML library has two modes of operation with respect to sending the models
+to the WML service: inline data, or using data assets in Watson Studio.  By default,
+data assets are used for inputs, while inline data is used for outputs. 
+This can be changed with the `inputs` and `outputs` commands.
+With inline data, the model is sent directly to the WML service in the _solve_
+request itself, and the output is part of the job details that are downloaded when
+asking for information about the job.  
+This is the simplest, but it has a number of drawbacks:
+- Sending a large model may take a long time, because of network throughput.  Sending
+a very large REST request is not at all guaranteed to succeed.  Similarly, if your
+job has large outputs, the job may fail while trying to process them.
+- When solving several times the same model (e.g. to evaluate different parameters),
+the model has to be sent each time.
+- In order to display the names of the files that were sent, the _jobs_ command
+needs to request this information, and it comes with the content of the files
+  themselves.  In other words, every _jobs_ command requires downloading the content
+  of all the inline data files for all the jobs that exist in the space.
+Using data assets in Watson Studio as an intermediate step alleviate all these issues:
+- Once the model has been uploaded to Watson Studio, it will be reused for
+subsequent jobs without the need to upload it again.
+- The job requests refer to the files indirectly, via URLs.  Therefore, they don't
+take much space, and listing the jobs doesn't imply to download the content of the
+  files.
+- Uploading to Watson Studio is done through specialized code that doesn't just send a single
+request.  Rather, it divides the upload in multiple reasonably sized chunks that each
+  are uploaded individually, with restart if necessary.  Uploading big files is
+  therefore much less prone to failure.
+
+%package help
+Summary:	Development documents and examples for dowml
+Provides:	python3-dowml-doc
+%description help
+cancel  details  exit  inline  jobs  output   shell  solve   time  version
+delete  dump     help  inputs  log   outputs  size   status  type  wait
+dowml> type
+Current model type: cplex.
+Known types: cplex, cpo, opl, docplex.
+dowml> size
+Current size: S.
+Known sizes: S, M, L, XL.
+dowml> inputs inline
+dowml> solve examples/afiro.mps
+Job id: cd494377-4843-40a4-ae84-ede7f8c16eda
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: queued      cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> wait
+Job is running.
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+=>   1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+dowml> log
+[2022-06-28T09:59:08Z, INFO] CPLEX version 22010000
+[2022-06-28T09:59:08Z, WARNING] Changed parameter CPX_PARAM_THREADS from 0 to 1
+[2022-06-28T09:59:08Z, INFO] Param[1,067] = 1
+[2022-06-28T09:59:08Z, INFO] Param[1,130] = UTF-8
+[2022-06-28T09:59:08Z, INFO] Param[1,132] = -1
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Selected objective sense:  MINIMIZE
+[2022-06-28T09:59:08Z, INFO] Selected objective  name:  obj
+[2022-06-28T09:59:08Z, INFO] Selected RHS        name:  rhs
+[2022-06-28T09:59:08Z, INFO] Version identifier: 22.1.0.0 | 2022-03-30 | 54982fbec
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Threads                                 1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Output_CloneLog                         -1
+[2022-06-28T09:59:08Z, INFO] CPXPARAM_Read_APIEncoding                        "UTF-8"
+[2022-06-28T09:59:08Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:08Z, INFO] LP Presolve eliminated 9 rows and 10 columns.
+[2022-06-28T09:59:08Z, INFO] Aggregator did 7 substitutions.
+[2022-06-28T09:59:08Z, INFO] Reduced LP has 11 rows, 15 columns, and 37 nonzeros.
+[2022-06-28T09:59:08Z, INFO] Presolve time = 0.00 sec. (0.03 ticks)
+[2022-06-28T09:59:08Z, INFO]
+[2022-06-28T09:59:08Z, INFO] Iteration log . . .
+[2022-06-28T09:59:08Z, INFO] Iteration:     1   Scaled dual infeas =             1.200000
+[2022-06-28T09:59:08Z, INFO] Iteration:     5   Dual objective     =          -464.753143
+[2022-06-28T09:59:09Z, INFO] There are no bound infeasibilities.
+[2022-06-28T09:59:09Z, INFO] There are no reduced-cost infeasibilities.
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) Ax-b resid.          = 1.77636e-14 (1.77636e-14)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) c-B'pi resid.        = 5.55112e-17 (5.55112e-17)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |x|                  = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |slack|              = 500 (500)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |pi|                 = 0.942857 (1.88571)
+[2022-06-28T09:59:09Z, INFO] Max. unscaled (scaled) |red-cost|           = 10 (10)
+[2022-06-28T09:59:09Z, INFO] Condition number of scaled basis            = 1.5e+01
+[2022-06-28T09:59:09Z, INFO] optimal (1)
+dowml> type docplex
+dowml> solve examples/markshare.py examples/markshare1.mps.gz
+Job id: 6520e72b-727c-4bfe-adb5-a40d96cf5910
+dowml> wait
+Job is queued.
+Job is running..
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:16Z, WARNING] Python 3.9 is used as default with pandas 1.3 libraries.
+[2022-06-28T09:59:17Z, INFO] Reading markshare1.mps.gz...
+.
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO]         Nodes                                         Cuts/
+[2022-06-28T09:59:17Z, INFO]    Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] *     0+    0                         7286.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     6     7286.0000        0.0000       11  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          263.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          230.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 15       15  100.00%
+[2022-06-28T09:59:17Z, INFO]       0     0        0.0000     7      230.0000      Cuts: 16       23  100.00%
+[2022-06-28T09:59:17Z, INFO] *     0+    0                          193.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] Detecting symmetries...
+[2022-06-28T09:59:17Z, INFO]       0     2        0.0000     7      193.0000        0.0000       23  100.00%
+[2022-06-28T09:59:17Z, INFO] Elapsed time = 0.01 sec. (2.91 ticks, tree = 0.01 MB, solutions = 4)
+[2022-06-28T09:59:17Z, INFO] *    70+   59                          166.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *    80+   67                          132.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   190+  155                          111.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   220+  166                           96.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   320+  240                           71.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  305                           67.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   420+  303                           66.0000        0.0000           100.00%
+[2022-06-28T09:59:17Z, INFO] *   491   310      integral     0       38.0000        0.0000     1112  100.00%
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Performing restart 1
+[2022-06-28T09:59:17Z, INFO]
+[2022-06-28T09:59:17Z, INFO] Repeating presolve.
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.14 ticks)
+[2022-06-28T09:59:17Z, INFO] Tried aggregator 1 time.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 6 rows, 56 columns, and 306 nonzeros.
+[2022-06-28T09:59:17Z, INFO] Reduced MIP has 50 binaries, 6 generals, 0 SOSs, and 0 indicators.
+[2022-06-28T09:59:17Z, INFO] Presolve time = 0.00 sec. (0.19 ticks)
+[2022-06-28T09:59:17Z, INFO] Represolve time = 0.00 sec. (0.81 ticks)
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 17     3422  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     8       38.0000      Cuts: 17     3429  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3436  100.00%
+[2022-06-28T09:59:17Z, INFO]    1518     0        0.0000     7       38.0000      Cuts: 14     3441  100.00%
+[2022-06-28T09:59:18Z, INFO]    3918  1669        0.0000     6       38.0000        0.0000     8018  100.00%
+[2022-06-28T09:59:18Z, INFO]    6508  2914        0.0000     6       38.0000        0.0000    14256  100.00%
+[2022-06-28T09:59:19Z, INFO]    9718  4470        0.0000     6       38.0000        0.0000    22692  100.00%
+[2022-06-28T09:59:19Z, INFO] Began writing nodes to disk (directory ./cpxY2cKqj created)
+[2022-06-28T09:59:22Z, INFO]   10638  4956       13.6062     6       38.0000        0.0000    25327  100.00%
+[2022-06-28T09:59:23Z, INFO]   13478  6155        0.0000     6       38.0000        0.0000    33717  100.00%
+Job is completed.
+Job has finished with status 'completed'.
+dowml> jobs
+     #  status      id                                    creation date        type     ver.   size  inputs
+     1: completed   cd494377-4843-40a4-ae84-ede7f8c16eda  2022-06-28 11:59:06  cplex    22.1   S     afiro.mps
+=>   2: completed   6520e72b-727c-4bfe-adb5-a40d96cf5910  2022-06-28 11:59:13  docplex  22.1   S     markshare.py, markshare1.mps.gz
+dowml> dump
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/details.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare.py
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/markshare1.mps.gz
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/model.lp
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/solution.json
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/kpis.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/stats.csv
+Storing 6520e72b-727c-4bfe-adb5-a40d96cf5910/log.txt
+dowml> shell ls -l *-*-*-*-*
+total 88
+-rw-rw-r--  1 nodet  staff  5506 Jun 28 11:59 details.json
+-rw-rw-r--  1 nodet  staff    37 Jun 28 11:59 kpis.csv
+-rw-rw-r--  1 nodet  staff  7299 Jun 28 11:59 log.txt
+-rw-rw-r--  1 nodet  staff   671 Jun 28 11:59 markshare.py
+-rw-rw-r--  1 nodet  staff  1607 Jun 28 11:59 markshare1.mps.gz
+-rw-rw-r--  1 nodet  staff  4197 Jun 28 11:59 model.lp
+-rw-rw-r--  1 nodet  staff  1769 Jun 28 11:59 solution.json
+-rw-rw-r--  1 nodet  staff   344 Jun 28 11:59 stats.csv
+dowml> delete *
+```
+## WML credentials
+The DOWML client requires some information in order to connect to the Watson
+Machine Learning service.  Two pieces of information are required, and the others
+are optional.
+### Required items
+- The `apikey` is a secret that identifies the IBM Cloud user. One typically creates
+  one key per application or service, in order to be able to revoke them individually
+  if needed.
+  To generate such a key, open https://cloud.ibm.com/iam/apikeys, and click the blue
+  'Create an IBM Cloud API key' on the right.
+- The `url` is the base URL for the REST calls to WML.  The possible values are
+  found in https://cloud.ibm.com/apidocs/machine-learning#endpoint-url, 
+  and depend on which region you want to use.
+- As an alternative to the `url` value, you can use a more user-friendly and 
+  easier to remember `region`, with a value that is either `us-south`, `eu-de`,
+  `eu-gb` or `jp-tok`.  From this value, _dowml_ will deduce the correct URL to use.
+  To avoid ambiguities or duplications, it is not allowed to use both `url` and
+  `region`.
+### Optional items
+Watson Studio and Watson Machine Learning use _spaces_ to group together, and
+isolate from each other, the assets that belong to a single project.  These assets 
+include the data files submitted, the results of the jobs, and the _deployments_
+(software and hardware configurations) that run these jobs.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.
+To create a new space, the DOWML client will need both `cos_resource_crn` and
+`ml_instance_crn` to have been specified in the credentials.
+- `space_id`: identifier of an existing space to connect to.  Navigate to the 
+  'Spaces' tab of your Watson Studio site (e.g. 
+  https://eu-de.dataplatform.cloud.ibm.com/ml-runtime/spaces if you are using
+  the instance in Germany), right-click on the name of an existing space to
+  copy the link. The id of the space is the string of numbers, letters and dashes
+  between the last `/` and the `?`.
+- `cos_resource_crn`: WML needs to store some data in a Cloud Object Storage 
+  instance.  Open
+  https://cloud.ibm.com/resources and locate the 'Storage' section.  Create an
+  instance of the Cloud Object Storage service if needed. Once it's listed on
+  the resource page, click anywhere on the line for that service, except on its
+  name.  This will open a pane on the right which lists the CRN.  Click on the
+  symbol at the right to copy this information.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+- `ml_instance_crn`: similarly, you need to identify an instance of Machine 
+  Learning service to use
+  to solve your jobs.  In the same page https://cloud.ibm.com/resources, open the
+  'Services' section.  The 'Product' columns tells you the type of service.  If
+  you don't have a 'Machine Learning' instance already, create one.  Then click
+  on the corresponding line anywhere except on the name, and copy the CRN displayed
+  in the pane that open on the right.  This item is required only for 
+  the DOWML client to be able to create a space.  If you specified a `space_id`,
+  it is not required.
+## CP4D credentials
+The credentials to connect to the WML service _in a (private) CP4D instance_ are 
+different from those above that pertain to CP4D _as a service_.  The credentials
+look like this:
+```
+{
+   "instance_id": "openshift",
+   "version": "4.0",
+   "url": "...",
+   "username": "...",
+   "apikey": "...",
+   "space_id": "..."
+}
+```
+- The `url` is the URL of your CP4D instance, with no `/` at the end. 
+- The `username` and `apikey` for your user on this cluster.  You can
+get the API key in the 'Profile and settings' dialog that's accessible from your
+avatar menu in the top-right of the screen.
+- `space_id`: the identifier of an existing space to connect to.
+The DOWML client will connect to the space specified by the user using
+either the `--space` command-line argument or the `space_id` item in the credentials.
+If neither of these are specified, the client will look for a space named 
+_dowml-space_, and will try to create such a space if one doesn't exist.  On CPD,
+unlike for Cloud, no `cos_resource_crn` or `ml_instance_crn` are required.
+## Using data assets in Watson Studio
+The DOWML library has two modes of operation with respect to sending the models
+to the WML service: inline data, or using data assets in Watson Studio.  By default,
+data assets are used for inputs, while inline data is used for outputs. 
+This can be changed with the `inputs` and `outputs` commands.
+With inline data, the model is sent directly to the WML service in the _solve_
+request itself, and the output is part of the job details that are downloaded when
+asking for information about the job.  
+This is the simplest, but it has a number of drawbacks:
+- Sending a large model may take a long time, because of network throughput.  Sending
+a very large REST request is not at all guaranteed to succeed.  Similarly, if your
+job has large outputs, the job may fail while trying to process them.
+- When solving several times the same model (e.g. to evaluate different parameters),
+the model has to be sent each time.
+- In order to display the names of the files that were sent, the _jobs_ command
+needs to request this information, and it comes with the content of the files
+  themselves.  In other words, every _jobs_ command requires downloading the content
+  of all the inline data files for all the jobs that exist in the space.
+Using data assets in Watson Studio as an intermediate step alleviate all these issues:
+- Once the model has been uploaded to Watson Studio, it will be reused for
+subsequent jobs without the need to upload it again.
+- The job requests refer to the files indirectly, via URLs.  Therefore, they don't
+take much space, and listing the jobs doesn't imply to download the content of the
+  files.
+- Uploading to Watson Studio is done through specialized code that doesn't just send a single
+request.  Rather, it divides the upload in multiple reasonably sized chunks that each
+  are uploaded individually, with restart if necessary.  Uploading big files is
+  therefore much less prone to failure.
+
+%prep
+%autosetup -n dowml-1.9.0
+
+%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-dowml -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 1.9.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..cf7a49c
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+5be8393094b20258fbd329a7cb89face  dowml-1.9.0.tar.gz