automatic import of python-coinstac-computation

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+/coinstac-computation-1.0.2.tar.gz
diff --git a/python-coinstac-computation.spec b/python-coinstac-computation.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-coinstac-computation
+Version:	1.0.2
+Release:	1
+Summary:	Generic computation implementation on COINSTAC.
+License:	MIT
+URL:		https://github.com/trendscenter/coinstac-computation
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ea/99/7e70962defea4d05e5d9ab73b9f941890481f0846d3fbe7bc777e58936ec/coinstac-computation-1.0.2.tar.gz
+BuildArch:	noarch
+
+
+%description
+#### **ComputationPhase** signature:
+```python
+from coinstac_computation import  ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def _initialize(self):
+      """Put anything that needs to be initialized only once here"""
+      pass
+    def compute(self):
+        out = {}
+        """To end multi-iterative phase, and go to the next phase, in local or remote set:"""
+        out['jump_to_next'] = True
+        """To stop the computation, In remote set:"""
+        out['success'] = True
+        return out
+```
+### Example: Gather max even numbers from each site
+#### A full working use case is in the [examples/basic](./examples/basic) directory where:
+* Local sites filters out even numbers and sends to the remote.
+* Remote finds the max across sites and returns the final result to each of the sites.
+* Sites save final result.
+#### inputspec.json data:
+```json
+[
+  {
+    "data": {
+      "value": [10, 3, 5, 6, 7, 8, 12, 38, 32, 789, 776, 441]
+    }
+  },
+  {
+    "data": {
+      "value": [12, 33, 88, 61, 37, 58, 103, 3386, 312, 9, 77, 41]
+    }
+  }
+]
+```
+### Local node pipeline:
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        data = []
+        for d in self.input['data']:
+            if d % 2 == 0:
+                data.append(d)
+        return {'filtered_data': data}
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        with open(f"{self.out_dir + os.sep + 'results.txt'}", 'w') as out:
+            out.write(f"{self.input['aggregated_data']}")
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+### Remote node pipeline:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+class PhaseCollectMaxEvenData(ComputationPhase):
+    def compute(self):
+        data = []
+        for site, site_vars in self.input.items():
+            site_max = max(site_vars['filtered_data'])
+            data.append(site_max)
+        return {'aggregated_data': data}
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseCollectMaxEvenData)
+remote.add_phase(PhaseEndWithSuccess)
+```
+### Entry point:
+```python
+import coinstac
+from local_pipeline import local
+from remote_pipeline import remote
+coinstac.start(local, remote)
+```
+### Run:
+```
+cd examples/basic/
+~/coinstac-computation/examples/basic/$ docker build -t base . && coinstac-simulator
+```
+<hr />
+### Advanced use cases:
+#### 1. Multiple local <---> remote iterations [example](./examples/multi_iterations):
+* Each sites cast a vote(positive vote if number is even) for multiple(default=51) times.
+* Remote gathers the votes and returns the final voting result to all sites at the end.
+* Sites save the final result.
+#### Overview:
+1. Specify when to end the iterative phase with a phase jump signal as `jump_to_next=True`:
+```python
+class PhaseSubmitVote(ComputationPhase):
+    def _initialize(self):
+        """This method runs only once"""
+        self.cache['data_index'] = 0
+        self.cache['data'] = []
+        for line in open(self.base_dir + os.sep + self.input_args['data_source']).readlines():
+            self.cache['data'].append(float(line.strip()))
+    def compute(self):
+        out = {
+            'vote': self.cache['data'][self.cache['data_index']] % 2 == 0,
+        }
+        self.cache['data_index'] += 1
+        """Send a jump to next phase signal"""
+        out['jump_to_next'] = self.cache['data_index'] > len(self.cache['data']) - 1
+        return out
+```
+2. Add the phase as multi-iterations:
+```python
+local.add_phase(PhaseSubmitVote, multi_iterations=True)
+```
+#### 2. Send data across local <---> remote [example](./examples/data_transfer):
+To make it simple, we send a matrix of size 1000 by 1000 to remote, aggregate it by averaging, and return to each site.
+Local: 
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+import numpy as np
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = np.random.randn(*self.input['matrix_shape'])
+        out.update(**self.send("site_matrix", data))
+        return out
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        data = self.recv('averaged_matrix')
+        np.save(self.out_dir + os.sep + "averaged_matrix.npy", data)
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+Remote:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+import numpy as np
+class PhaseAggregateMatrix(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = self.recv("site_matrix")
+        mean_data = np.array(data).mean(0)
+        out.update(**self.send("averaged_matrix", mean_data))
+        return out
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseAggregateMatrix)
+remote.add_phase(PhaseEndWithSuccess)
+```
+<hr />
+### Sample logs from local0
+```
+[INPUT] 14:27:36 02/04/2022 
+  ->{'data_source': 'data_file.txt'}
+[CACHE] 14:27:36 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 0, 'PhaseSaveResult': 0}}}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:36 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': False, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 3, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 3, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+```
+### Sample logs from remote
+```
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 0, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 3, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1], [4, 0]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+```
+<hr />
+### Development notes:
+* Make sure you have:
+  * **docker** installed and running.
+  * **nodejs** installed.
+  * **coinstac-simulator** package installed. `npm install --global coinstac-simulator`
+* Must set `debug=False` while deploying.
+* Backward compatible to the older library(compspecVersion=1):
+  * Add the following snippet at the end of local and remote pipeline scripts.
+  ```python
+  if __name__ == "__main__":
+      local.to_stdout()
+  ```
+  * Use [version 1.0](./examples/basic/compspecv1.json) compspec format.
+  * Comment out line `CMD ["python", "entry.py"]` in the `Dockerfile`.
+  * You can also use a **remote debugger** in pycharm as [here](https://www.jetbrains.com/help/pycharm/remote-debugging-with-product.html#remote-debug-config).
+### Thanks!
+
+%package -n python3-coinstac-computation
+Summary:	Generic computation implementation on COINSTAC.
+Provides:	python-coinstac-computation
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-coinstac-computation
+#### **ComputationPhase** signature:
+```python
+from coinstac_computation import  ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def _initialize(self):
+      """Put anything that needs to be initialized only once here"""
+      pass
+    def compute(self):
+        out = {}
+        """To end multi-iterative phase, and go to the next phase, in local or remote set:"""
+        out['jump_to_next'] = True
+        """To stop the computation, In remote set:"""
+        out['success'] = True
+        return out
+```
+### Example: Gather max even numbers from each site
+#### A full working use case is in the [examples/basic](./examples/basic) directory where:
+* Local sites filters out even numbers and sends to the remote.
+* Remote finds the max across sites and returns the final result to each of the sites.
+* Sites save final result.
+#### inputspec.json data:
+```json
+[
+  {
+    "data": {
+      "value": [10, 3, 5, 6, 7, 8, 12, 38, 32, 789, 776, 441]
+    }
+  },
+  {
+    "data": {
+      "value": [12, 33, 88, 61, 37, 58, 103, 3386, 312, 9, 77, 41]
+    }
+  }
+]
+```
+### Local node pipeline:
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        data = []
+        for d in self.input['data']:
+            if d % 2 == 0:
+                data.append(d)
+        return {'filtered_data': data}
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        with open(f"{self.out_dir + os.sep + 'results.txt'}", 'w') as out:
+            out.write(f"{self.input['aggregated_data']}")
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+### Remote node pipeline:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+class PhaseCollectMaxEvenData(ComputationPhase):
+    def compute(self):
+        data = []
+        for site, site_vars in self.input.items():
+            site_max = max(site_vars['filtered_data'])
+            data.append(site_max)
+        return {'aggregated_data': data}
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseCollectMaxEvenData)
+remote.add_phase(PhaseEndWithSuccess)
+```
+### Entry point:
+```python
+import coinstac
+from local_pipeline import local
+from remote_pipeline import remote
+coinstac.start(local, remote)
+```
+### Run:
+```
+cd examples/basic/
+~/coinstac-computation/examples/basic/$ docker build -t base . && coinstac-simulator
+```
+<hr />
+### Advanced use cases:
+#### 1. Multiple local <---> remote iterations [example](./examples/multi_iterations):
+* Each sites cast a vote(positive vote if number is even) for multiple(default=51) times.
+* Remote gathers the votes and returns the final voting result to all sites at the end.
+* Sites save the final result.
+#### Overview:
+1. Specify when to end the iterative phase with a phase jump signal as `jump_to_next=True`:
+```python
+class PhaseSubmitVote(ComputationPhase):
+    def _initialize(self):
+        """This method runs only once"""
+        self.cache['data_index'] = 0
+        self.cache['data'] = []
+        for line in open(self.base_dir + os.sep + self.input_args['data_source']).readlines():
+            self.cache['data'].append(float(line.strip()))
+    def compute(self):
+        out = {
+            'vote': self.cache['data'][self.cache['data_index']] % 2 == 0,
+        }
+        self.cache['data_index'] += 1
+        """Send a jump to next phase signal"""
+        out['jump_to_next'] = self.cache['data_index'] > len(self.cache['data']) - 1
+        return out
+```
+2. Add the phase as multi-iterations:
+```python
+local.add_phase(PhaseSubmitVote, multi_iterations=True)
+```
+#### 2. Send data across local <---> remote [example](./examples/data_transfer):
+To make it simple, we send a matrix of size 1000 by 1000 to remote, aggregate it by averaging, and return to each site.
+Local: 
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+import numpy as np
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = np.random.randn(*self.input['matrix_shape'])
+        out.update(**self.send("site_matrix", data))
+        return out
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        data = self.recv('averaged_matrix')
+        np.save(self.out_dir + os.sep + "averaged_matrix.npy", data)
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+Remote:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+import numpy as np
+class PhaseAggregateMatrix(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = self.recv("site_matrix")
+        mean_data = np.array(data).mean(0)
+        out.update(**self.send("averaged_matrix", mean_data))
+        return out
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseAggregateMatrix)
+remote.add_phase(PhaseEndWithSuccess)
+```
+<hr />
+### Sample logs from local0
+```
+[INPUT] 14:27:36 02/04/2022 
+  ->{'data_source': 'data_file.txt'}
+[CACHE] 14:27:36 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 0, 'PhaseSaveResult': 0}}}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:36 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': False, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 3, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 3, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+```
+### Sample logs from remote
+```
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 0, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 3, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1], [4, 0]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+```
+<hr />
+### Development notes:
+* Make sure you have:
+  * **docker** installed and running.
+  * **nodejs** installed.
+  * **coinstac-simulator** package installed. `npm install --global coinstac-simulator`
+* Must set `debug=False` while deploying.
+* Backward compatible to the older library(compspecVersion=1):
+  * Add the following snippet at the end of local and remote pipeline scripts.
+  ```python
+  if __name__ == "__main__":
+      local.to_stdout()
+  ```
+  * Use [version 1.0](./examples/basic/compspecv1.json) compspec format.
+  * Comment out line `CMD ["python", "entry.py"]` in the `Dockerfile`.
+  * You can also use a **remote debugger** in pycharm as [here](https://www.jetbrains.com/help/pycharm/remote-debugging-with-product.html#remote-debug-config).
+### Thanks!
+
+%package help
+Summary:	Development documents and examples for coinstac-computation
+Provides:	python3-coinstac-computation-doc
+%description help
+#### **ComputationPhase** signature:
+```python
+from coinstac_computation import  ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def _initialize(self):
+      """Put anything that needs to be initialized only once here"""
+      pass
+    def compute(self):
+        out = {}
+        """To end multi-iterative phase, and go to the next phase, in local or remote set:"""
+        out['jump_to_next'] = True
+        """To stop the computation, In remote set:"""
+        out['success'] = True
+        return out
+```
+### Example: Gather max even numbers from each site
+#### A full working use case is in the [examples/basic](./examples/basic) directory where:
+* Local sites filters out even numbers and sends to the remote.
+* Remote finds the max across sites and returns the final result to each of the sites.
+* Sites save final result.
+#### inputspec.json data:
+```json
+[
+  {
+    "data": {
+      "value": [10, 3, 5, 6, 7, 8, 12, 38, 32, 789, 776, 441]
+    }
+  },
+  {
+    "data": {
+      "value": [12, 33, 88, 61, 37, 58, 103, 3386, 312, 9, 77, 41]
+    }
+  }
+]
+```
+### Local node pipeline:
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        data = []
+        for d in self.input['data']:
+            if d % 2 == 0:
+                data.append(d)
+        return {'filtered_data': data}
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        with open(f"{self.out_dir + os.sep + 'results.txt'}", 'w') as out:
+            out.write(f"{self.input['aggregated_data']}")
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+### Remote node pipeline:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+class PhaseCollectMaxEvenData(ComputationPhase):
+    def compute(self):
+        data = []
+        for site, site_vars in self.input.items():
+            site_max = max(site_vars['filtered_data'])
+            data.append(site_max)
+        return {'aggregated_data': data}
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseCollectMaxEvenData)
+remote.add_phase(PhaseEndWithSuccess)
+```
+### Entry point:
+```python
+import coinstac
+from local_pipeline import local
+from remote_pipeline import remote
+coinstac.start(local, remote)
+```
+### Run:
+```
+cd examples/basic/
+~/coinstac-computation/examples/basic/$ docker build -t base . && coinstac-simulator
+```
+<hr />
+### Advanced use cases:
+#### 1. Multiple local <---> remote iterations [example](./examples/multi_iterations):
+* Each sites cast a vote(positive vote if number is even) for multiple(default=51) times.
+* Remote gathers the votes and returns the final voting result to all sites at the end.
+* Sites save the final result.
+#### Overview:
+1. Specify when to end the iterative phase with a phase jump signal as `jump_to_next=True`:
+```python
+class PhaseSubmitVote(ComputationPhase):
+    def _initialize(self):
+        """This method runs only once"""
+        self.cache['data_index'] = 0
+        self.cache['data'] = []
+        for line in open(self.base_dir + os.sep + self.input_args['data_source']).readlines():
+            self.cache['data'].append(float(line.strip()))
+    def compute(self):
+        out = {
+            'vote': self.cache['data'][self.cache['data_index']] % 2 == 0,
+        }
+        self.cache['data_index'] += 1
+        """Send a jump to next phase signal"""
+        out['jump_to_next'] = self.cache['data_index'] > len(self.cache['data']) - 1
+        return out
+```
+2. Add the phase as multi-iterations:
+```python
+local.add_phase(PhaseSubmitVote, multi_iterations=True)
+```
+#### 2. Send data across local <---> remote [example](./examples/data_transfer):
+To make it simple, we send a matrix of size 1000 by 1000 to remote, aggregate it by averaging, and return to each site.
+Local: 
+```python
+import os
+from coinstac_computation import COINSTACPyNode, ComputationPhase
+import numpy as np
+class PhaseLoadData(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = np.random.randn(*self.input['matrix_shape'])
+        out.update(**self.send("site_matrix", data))
+        return out
+class PhaseSaveResult(ComputationPhase):
+    def compute(self):
+        data = self.recv('averaged_matrix')
+        np.save(self.out_dir + os.sep + "averaged_matrix.npy", data)
+local = COINSTACPyNode(mode='local', debug=True)
+local.add_phase(PhaseLoadData)
+local.add_phase(PhaseSaveResult)
+```
+Remote:
+```python
+from coinstac_computation import COINSTACPyNode, ComputationPhase, PhaseEndWithSuccess
+import numpy as np
+class PhaseAggregateMatrix(ComputationPhase):
+    def compute(self):
+        out = {}
+        data = self.recv("site_matrix")
+        mean_data = np.array(data).mean(0)
+        out.update(**self.send("averaged_matrix", mean_data))
+        return out
+remote = COINSTACPyNode(mode='remote', debug=True)
+remote.add_phase(PhaseAggregateMatrix)
+remote.add_phase(PhaseEndWithSuccess)
+```
+<hr />
+### Sample logs from local0
+```
+[INPUT] 14:27:36 02/04/2022 
+  ->{'data_source': 'data_file.txt'}
+[CACHE] 14:27:36 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 0, 'PhaseSaveResult': 0}}}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:36 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 1, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 1, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': False, 'jump_to_next': False}}
+[INPUT] 14:27:37 02/04/2022 
+  ->{}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 2, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 2, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+  <-{'PIPELINE:LOCAL': {'index': 0, 'iterations': {'PhaseSubmitVote': 3, 'PhaseSaveResult': 0}}, 'input_args': {'data_source': 'data_file.txt'}, 'next_phase': 'PhaseSubmitVote', 'data_index': 3, 'data': [712.0, 309.0, 574.0, 838.0, 296.0, 349.0, 781.0, 749.0, 360.0, 702.0, 253.0, 831.0, 911.0, 14.0, 259.0, 805.0, 494.0, 501.0, 549.0, 624.0, 919.0, 836.0, 362.0, 373.0, 563.0, 134.0, 610.0, 875.0, 328.0, 299.0, 874.0, 387.0, 743.0, 233.0, 834.0, 870.0, 685.0, 342.0, 79.0, 270.0, 314.0, 42.0, 364.0, 902.0, 755.0, 248.0, 815.0, 4.0, 21.0, 423.0, 302.0], 'PHASE:PhaseSubmitVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {'vote': True, 'jump_to_next': False}}
+```
+### Sample logs from remote
+```
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 0, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 1, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+[INPUT] 14:27:37 02/04/2022 
+  ->{'local0': {'vote': True, 'jump_to_next': False}, 'local3': {'vote': True, 'jump_to_next': False}, 'local2': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': True, 'jump_to_next': False}}
+[CACHE] 14:27:37 02/04/2022 
+  ->{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 2, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1]], 'PHASE:PhaseCollectVote': True}
+  <-{'PIPELINE:REMOTE': {'index': 0, 'iterations': {'PhaseCollectVote': 3, 'PhaseSendGlobalResults': 0, 'PhaseEndWithSuccess': 0}}, 'input_args': {'local0': {'vote': True, 'jump_to_next': False}, 'local1': {'vote': False, 'jump_to_next': False}, 'local2': {'vote': False, 'jump_to_next': False}, 'local3': {'vote': False, 'jump_to_next': False}}, 'next_phase': 'PhaseCollectVote', 'vote_ballot': [[1, 3], [3, 1], [4, 0]], 'PHASE:PhaseCollectVote': True}
+[OUTPUT] 14:27:37 02/04/2022 
+  <-{'output': {}, 'success': False}
+```
+<hr />
+### Development notes:
+* Make sure you have:
+  * **docker** installed and running.
+  * **nodejs** installed.
+  * **coinstac-simulator** package installed. `npm install --global coinstac-simulator`
+* Must set `debug=False` while deploying.
+* Backward compatible to the older library(compspecVersion=1):
+  * Add the following snippet at the end of local and remote pipeline scripts.
+  ```python
+  if __name__ == "__main__":
+      local.to_stdout()
+  ```
+  * Use [version 1.0](./examples/basic/compspecv1.json) compspec format.
+  * Comment out line `CMD ["python", "entry.py"]` in the `Dockerfile`.
+  * You can also use a **remote debugger** in pycharm as [here](https://www.jetbrains.com/help/pycharm/remote-debugging-with-product.html#remote-debug-config).
+### Thanks!
+
+%prep
+%autosetup -n coinstac-computation-1.0.2
+
+%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-coinstac-computation -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.2-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..aaee775
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+bfd2df4f5a6e5cd6d0ace70539efc5f1  coinstac-computation-1.0.2.tar.gz