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+/Faker-Events-1.6.0.tar.gz
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+%global _empty_manifest_terminate_build 0
+Name:		python-Faker-Events
+Version:	1.6.0
+Release:	1
+Summary:	Generates Events with formatted fake data for streams.
+License:	MIT
+URL:		https://github.com/johnbrandborg/faker-events
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/2a/67/288ec541eb57a6232cff13b60654529e810ac211e43eb495ade6ab0b94d4/Faker-Events-1.6.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-faker
+Requires:	python3-croniter
+Requires:	python3-flake8
+Requires:	python3-pytest
+Requires:	python3-pytest-cov
+Requires:	python3-kafka-python
+Requires:	python3-boto3
+
+%description
+# Faker Events
+[![Python appliction](https://github.com/johnbrandborg/faker-events/workflows/Python%20application/badge.svg)](https://github.com/johnbrandborg/faker-events/actions?query=workflow%3A%22Python+application%22)
+[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=johnbrandborg_faker-events&metric=alert_status)](https://sonarcloud.io/dashboard?id=johnbrandborg_faker-events)
+[![PyPI version](https://badge.fury.io/py/Faker-Events.svg)](https://pypi.org/project/Faker-Events/)
+
+Generates Events with formatted fake data for streams. The intention is for
+ development and testing purposes without relying on real data.
+
+## Usage
+Faker Events allows you to create multiple data structures, and events that
+occur randomly or schedule, after which are sent to a data stream or system,
+through the message handler.
+
+The structures can be defined as Python Dictionaries, and processed using a
+function referred to as the profiler.
+
+The Faker package is utilised to generate the data on the profiles.
+Understanding how Faker works is recommended and you can find the documentation
+for it [here](https://faker.readthedocs.io/en/stable/).
+
+Beyond the profiles though for the custom event types any python data
+generation software can be used.
+
+### Installation
+By default faker-events simply prints to standard out.  To use a stream, give
+the option when installing.
+
+**Kafka**
+```bash
+pip install faker-events[kafka]
+```
+
+**Kinesis**
+```bash
+pip install faker-events[kinesis]
+```
+
+### Starting a Stream
+Create an Event Generator and start using Live Stream. By default only 1
+profile is created.  Giving large numbers of profiles can take sometime to
+build, but you can always save them by supplying the profile file name.
+
+Set the "Events Per Minute" when creating the event to change the maximum
+allowed, but subject to system performance also.  The default is 60 per
+minute with a variance of 25%.  Setting the variance to 0% will cause the
+events to not be random.
+
+If you want to see an example of this without writing code, run faker_events
+from the command line.  For help in using the CLI use the -h parameter.
+
+```shell
+faker-events -n 10 -p profiles.json
+```
+
+Output
+```json
+{"event_time": "2022-05-19T22:43:39.683304", "type": "example", "event_id": "1", "user_id": "1009", "first_name": "Brandon", "last_name": "Braun", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:40.291519", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.001050", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.358616", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.356265", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 71, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.788833", "type": "example", "event_id": "6", "user_id": "1003", "first_name": "Nathaniel", "last_name": "Garrett", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.106967", "type": "example", "event_id": "7", "user_id": "1000", "first_name": "Jeffrey", "last_name": "Owens", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.754115", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 77, "status": "normal"}
+{"event_time": "2022-05-19T22:43:44.121750", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 93, "status": "normal"}
+```
+
+If you would like to know more about how this Event Flow was created, read the
+[Example documentation](https://github.com/johnbrandborg/faker-events/blob/main/docs/Example.MD).
+
+
+#### Running a Faker Event Script
+
+You can work with Faker Events interactively in Python, or you can just use
+the class structures in a Python script, and call it using the command line
+interface.
+
+```shell
+faker-events -s fake_users_flow.py -n 1
+```
+
+If you prefer to use Python diretly, use the `start` method on an
+EventGenerator instance, to begin the steam.
+
+
+#### Saving the Profile Data
+
+The profile information created by Faker Events can be saved, so multiple runs
+of the python script will contain the same profile details.
+
+```shell
+faker-events -s fake_users_flow.py -n 100 -p profiles.json
+```
+
+### Using Stream Handlers
+Once you have installed Faker Events with the Stream type you want you
+can now use a stream handler to send the JSON messages to Kakfa, or
+Kinesis.
+
+**Kafka**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kafka', host='kafka:9092', name='example')
+EventGenerator.set_stream(example)
+```
+
+**Kinesis**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kinesis', name='example', key='key')
+EventGenerator.set_stream(example)
+```
+
+Creating a custom Stream handler is easy.  Just create a Class that has a
+`send` method, which takes the Dictionary of data, and then deliveries it.
+
+**Custom Handler**
+```python
+class CustomStream():
+    def __init__(self, *args, **kwargs):
+        # Store Parameters and Connect to destination
+
+    def send(self, message: Dict) -> None:
+        # Do something with the message
+```
+
+### Starting a Batch
+Create an Event Generator and use the batch method, with a start and finish
+datetime object, and the frequncy like on the live stream.
+
+```python
+from datetime import datetime, timedelta
+
+from faker_events import EventGenerator
+
+start = datetime(2019, 1, 1)  # No one wants to relive 2020...
+finish = start + timedelta(seconds=10)
+
+EventGenerator.batch(start, finish)
+```
+
+## Data Points
+### Event Data Points
+The Event Type has some basic data points about the event that can be used
+within the profiled method. (Access the Attribute using the 'event' within the
+profiler)
+
+* id - The id of the particular event, based on the event dictionary.
+* time - The time the event occured (ISO Format).
+* data - Event Data for updates or augmented assignments.
+
+By default the Event time is local time.  Set the timezone on the generator
+when required.
+
+### Profile Data Points
+When you use the Event Generator, the profiles you will use are created by the
+Profile Generator.  Each profile holds a number of data points. Below is a
+list of attributes that can be used on the 'profile' within the Event Profiler
+function.
+
+* id
+* uuid
+* username
+* gender
+* first_name
+* last_name
+* prefix_name
+* suffix_name
+* birthdate
+* blood_group
+* email
+* employer
+* job
+* full_address1
+* building_number1
+* street_name1
+* street_suffix1
+* state1
+* postcode1
+* city1
+* phone1
+* full_address2
+* building_number2
+* street_name2
+* street_suffix2
+* state2
+* postcode2
+* city2
+* phone2
+* driver_license
+* license_plate
+
+## Profiling Events
+Creating an Event is as easy as just creating a dictionary that is passed into
+the Event Class.  The Event Instance is then just set on the Event Generator,
+and you can then use the 'create_events' method which will return a generator,
+or us the 'start' or 'batch' methods that will handle the generator.
+
+If you want event values to be dynamic, create a profiler functions. The
+function should take two arguments; event and profile.  These carry the attributes
+listed above into the function for updating event values, or even creating new
+key value pairs.
+
+Update the event yourself by using 'event.data', which contains the dictionary
+passed into the Event Class.  The other option is to return a dictionary with
+the key value pairs you want to update.  The Event instance will handle updating
+the values.
+
+The profile is a randomly selected profile from the profiles created by the
+Event Generator.  You can use details from the profile to build our events
+that simulate customers, or entities.
+
+```python
+from faker import Faker
+from faker_events import Event, EventGenerator
+
+fake = Faker()
+
+event = {
+    'Fixed': 'Doesnt Change',
+    'Once': fake.color(),
+    'Always': '',
+    'Profiled': '',
+}
+
+def profiler(event, profile):
+    return {
+        'Always': fake.boolean(),
+        'Profiled': profile.email,
+    }
+
+EventGenerator.set_first_events(Event(event, profiler))
+```
+
+## Event Sequences
+#### Ordered
+You can sequence the events by setting the next event to occur, and occurence
+on how many times it will happen. To have events occur more than once, increase
+the limit.
+
+Either the 'next' attribute can be set with a statement, or the bitwise operator
+can be use to set the next event.
+
+```python
+from faker_events import Event, EventGenerator
+
+a = Event({'Name': 'A'})
+b = Event({'Name': 'B'}, limit=2)
+c = Event({'Name': 'C'})
+
+a.next = b
+b.next = c
+
+# Short form:
+# a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A"}
+{"Name": "B"}
+{"Name": "B"}
+{"Name": "C"}
+```
+
+#### Grouping
+If you need to two different events to be grouped together, you can set the
+group_by parameter to true on the Event instance creation.  This will cause the
+start and batch methods to send them together.
+
+You can also use the '&' operator (rather than '>>') to set the next event but
+grouped together so the event_time is the same.  Try not to mix the operators
+into long mixed sequences as it can cause problems with the ordering.
+
+### Persistant State
+When creating event flows there is some concepts around how Faker Events works
+that you should get familiar with.
+
+1. The dictionary created is used only as a template for Events
+2. Dictionaries that are identical will be treated as the same flow
+3. Profile Functions should declare a puprose and what needs to be change
+4. Event limit is for each profile created by the generator. (Default is 1)
+
+The following example shows how we create a type of event with the dictionary
+'customer', and then a flow in which a new customer event is made, followed by
+a job change for the customer.
+
+The generator has 2 profiles, and 1 of each event type, resulting in 4 events.
+(Events with a limit of 0 will occur as long as the stream is running, without
+ attempting to switch to the next event, even if one is set.)
+
+```python
+from faker_events import Event, EventGenerator
+from faker import Faker
+
+faker = Faker()
+
+customer = {'Name': 'Unknown', 'Job': None, 'Created': None, 'Updated': None}
+
+def new_customer(event, profile):
+    return {
+        "Name": profile.first_name,
+        "Job": profile.job,
+        "Created": event.time,
+        "Updated": event.time
+    }
+
+def change_job(event, profile):
+    return {
+        "Job": faker.job(),
+        "Updated": event.time
+    }
+
+new_customer_event = Event(customer, new_customer)
+customer_marriged_event = Event(customer, change_job)
+
+new_customer_event >> customer_marriged_event
+
+EventGenerator.set_first_events(new_customer_event)
+```
+
+Output (with two profiles)
+```json
+{"Name": "Ian", "Job": "Medical technical officer", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:55.809062"}
+{"Name": "Eduardo", "Job": "Conservation officer, nature", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:56.316593"}
+{"Name": "Ian", "Job": "Database administrator", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:56.773134"}
+{"Name": "Eduardo", "Job": "Ergonomist", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:57.694891"}
+```
+
+If you need to update the details of the profile, or add persistant data from
+the events you can do so within the Profiled method of the Event instance.
+When using sequenced events, the profile can be used to retrieve the data from
+previous events.
+
+```python
+from faker_events import Event, EventGenerator
+
+
+event_a = {'Name': 'A', 'LastEvent': 'none'}
+
+def profiler_a(event, profile):
+    profile.LastEvent = 'EventA'
+
+event_b = {'Name': 'B', 'LastEvent': 'none'}
+
+def profiler_b(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+    profile.LastEvent = 'EventB'
+
+event_c = {'Name': 'C', 'LastEvent': 'none'}
+
+def profiler_c(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+
+a = Event(event_a, profiler_a, 1)
+b = Event(event_b, profiler_b, 1)
+c = Event(event_c, profiler_c, 1)
+
+a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A", "LastEvent": "none"}
+{"Name": "B", "LastEvent": "EventA"}
+{"Name": "C", "LastEvent": "EventB"}
+```
+
+### Multiple Event Flows
+By grouping the events in lists, the Event Generator is able to work through
+multiple Event Flows for each profile created, creating complex event streams.
+
+```python
+from faker_events import Event, EventGenerator
+
+flow_a1 = Event({"Name": "A1"})
+flow_aa1 = Event({"Name": "AA1"})
+flow_aa2 = Event({"Name": "AA2"})
+
+flow_b1 = Event({"Name": "B1"})
+flow_bb1 = Event({"Name": "BB1"})
+flow_bb2 = Event({"Name": "BB2"})
+
+flow_a1 >> [flow_aa1, flow_aa2]
+flow_b1 >> [flow_bb1, flow_bb2]
+
+EventGeneratoe.set_first_events([flow_a1, flow_b1])
+```
+
+Output
+```json
+{"Name": "B1"}
+{"Name": "BB2"}
+{"Name": "A1"}
+{"Name": "AA1"}
+{"Name": "AA2"}
+{"Name": "BB1"}
+```
+
+### To Do List
+- [ ] Scheduling events with Cron syntax in Batch Mode.
+- [ ] Edge Case testing to produce bad or corrupted data on purpose.
+
+## License
+Faker-Events is released under the MIT License. See the bundled LICENSE file for details.
+
+## Credits
+* [Daniele Faraglia](https://github.com/joke2k) & [Flavio Curella](https://github.com/fcurella) / [Faker](https://github.com/joke2k/faker)
+
+
+
+
+%package -n python3-Faker-Events
+Summary:	Generates Events with formatted fake data for streams.
+Provides:	python-Faker-Events
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-Faker-Events
+# Faker Events
+[![Python appliction](https://github.com/johnbrandborg/faker-events/workflows/Python%20application/badge.svg)](https://github.com/johnbrandborg/faker-events/actions?query=workflow%3A%22Python+application%22)
+[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=johnbrandborg_faker-events&metric=alert_status)](https://sonarcloud.io/dashboard?id=johnbrandborg_faker-events)
+[![PyPI version](https://badge.fury.io/py/Faker-Events.svg)](https://pypi.org/project/Faker-Events/)
+
+Generates Events with formatted fake data for streams. The intention is for
+ development and testing purposes without relying on real data.
+
+## Usage
+Faker Events allows you to create multiple data structures, and events that
+occur randomly or schedule, after which are sent to a data stream or system,
+through the message handler.
+
+The structures can be defined as Python Dictionaries, and processed using a
+function referred to as the profiler.
+
+The Faker package is utilised to generate the data on the profiles.
+Understanding how Faker works is recommended and you can find the documentation
+for it [here](https://faker.readthedocs.io/en/stable/).
+
+Beyond the profiles though for the custom event types any python data
+generation software can be used.
+
+### Installation
+By default faker-events simply prints to standard out.  To use a stream, give
+the option when installing.
+
+**Kafka**
+```bash
+pip install faker-events[kafka]
+```
+
+**Kinesis**
+```bash
+pip install faker-events[kinesis]
+```
+
+### Starting a Stream
+Create an Event Generator and start using Live Stream. By default only 1
+profile is created.  Giving large numbers of profiles can take sometime to
+build, but you can always save them by supplying the profile file name.
+
+Set the "Events Per Minute" when creating the event to change the maximum
+allowed, but subject to system performance also.  The default is 60 per
+minute with a variance of 25%.  Setting the variance to 0% will cause the
+events to not be random.
+
+If you want to see an example of this without writing code, run faker_events
+from the command line.  For help in using the CLI use the -h parameter.
+
+```shell
+faker-events -n 10 -p profiles.json
+```
+
+Output
+```json
+{"event_time": "2022-05-19T22:43:39.683304", "type": "example", "event_id": "1", "user_id": "1009", "first_name": "Brandon", "last_name": "Braun", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:40.291519", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.001050", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.358616", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.356265", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 71, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.788833", "type": "example", "event_id": "6", "user_id": "1003", "first_name": "Nathaniel", "last_name": "Garrett", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.106967", "type": "example", "event_id": "7", "user_id": "1000", "first_name": "Jeffrey", "last_name": "Owens", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.754115", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 77, "status": "normal"}
+{"event_time": "2022-05-19T22:43:44.121750", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 93, "status": "normal"}
+```
+
+If you would like to know more about how this Event Flow was created, read the
+[Example documentation](https://github.com/johnbrandborg/faker-events/blob/main/docs/Example.MD).
+
+
+#### Running a Faker Event Script
+
+You can work with Faker Events interactively in Python, or you can just use
+the class structures in a Python script, and call it using the command line
+interface.
+
+```shell
+faker-events -s fake_users_flow.py -n 1
+```
+
+If you prefer to use Python diretly, use the `start` method on an
+EventGenerator instance, to begin the steam.
+
+
+#### Saving the Profile Data
+
+The profile information created by Faker Events can be saved, so multiple runs
+of the python script will contain the same profile details.
+
+```shell
+faker-events -s fake_users_flow.py -n 100 -p profiles.json
+```
+
+### Using Stream Handlers
+Once you have installed Faker Events with the Stream type you want you
+can now use a stream handler to send the JSON messages to Kakfa, or
+Kinesis.
+
+**Kafka**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kafka', host='kafka:9092', name='example')
+EventGenerator.set_stream(example)
+```
+
+**Kinesis**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kinesis', name='example', key='key')
+EventGenerator.set_stream(example)
+```
+
+Creating a custom Stream handler is easy.  Just create a Class that has a
+`send` method, which takes the Dictionary of data, and then deliveries it.
+
+**Custom Handler**
+```python
+class CustomStream():
+    def __init__(self, *args, **kwargs):
+        # Store Parameters and Connect to destination
+
+    def send(self, message: Dict) -> None:
+        # Do something with the message
+```
+
+### Starting a Batch
+Create an Event Generator and use the batch method, with a start and finish
+datetime object, and the frequncy like on the live stream.
+
+```python
+from datetime import datetime, timedelta
+
+from faker_events import EventGenerator
+
+start = datetime(2019, 1, 1)  # No one wants to relive 2020...
+finish = start + timedelta(seconds=10)
+
+EventGenerator.batch(start, finish)
+```
+
+## Data Points
+### Event Data Points
+The Event Type has some basic data points about the event that can be used
+within the profiled method. (Access the Attribute using the 'event' within the
+profiler)
+
+* id - The id of the particular event, based on the event dictionary.
+* time - The time the event occured (ISO Format).
+* data - Event Data for updates or augmented assignments.
+
+By default the Event time is local time.  Set the timezone on the generator
+when required.
+
+### Profile Data Points
+When you use the Event Generator, the profiles you will use are created by the
+Profile Generator.  Each profile holds a number of data points. Below is a
+list of attributes that can be used on the 'profile' within the Event Profiler
+function.
+
+* id
+* uuid
+* username
+* gender
+* first_name
+* last_name
+* prefix_name
+* suffix_name
+* birthdate
+* blood_group
+* email
+* employer
+* job
+* full_address1
+* building_number1
+* street_name1
+* street_suffix1
+* state1
+* postcode1
+* city1
+* phone1
+* full_address2
+* building_number2
+* street_name2
+* street_suffix2
+* state2
+* postcode2
+* city2
+* phone2
+* driver_license
+* license_plate
+
+## Profiling Events
+Creating an Event is as easy as just creating a dictionary that is passed into
+the Event Class.  The Event Instance is then just set on the Event Generator,
+and you can then use the 'create_events' method which will return a generator,
+or us the 'start' or 'batch' methods that will handle the generator.
+
+If you want event values to be dynamic, create a profiler functions. The
+function should take two arguments; event and profile.  These carry the attributes
+listed above into the function for updating event values, or even creating new
+key value pairs.
+
+Update the event yourself by using 'event.data', which contains the dictionary
+passed into the Event Class.  The other option is to return a dictionary with
+the key value pairs you want to update.  The Event instance will handle updating
+the values.
+
+The profile is a randomly selected profile from the profiles created by the
+Event Generator.  You can use details from the profile to build our events
+that simulate customers, or entities.
+
+```python
+from faker import Faker
+from faker_events import Event, EventGenerator
+
+fake = Faker()
+
+event = {
+    'Fixed': 'Doesnt Change',
+    'Once': fake.color(),
+    'Always': '',
+    'Profiled': '',
+}
+
+def profiler(event, profile):
+    return {
+        'Always': fake.boolean(),
+        'Profiled': profile.email,
+    }
+
+EventGenerator.set_first_events(Event(event, profiler))
+```
+
+## Event Sequences
+#### Ordered
+You can sequence the events by setting the next event to occur, and occurence
+on how many times it will happen. To have events occur more than once, increase
+the limit.
+
+Either the 'next' attribute can be set with a statement, or the bitwise operator
+can be use to set the next event.
+
+```python
+from faker_events import Event, EventGenerator
+
+a = Event({'Name': 'A'})
+b = Event({'Name': 'B'}, limit=2)
+c = Event({'Name': 'C'})
+
+a.next = b
+b.next = c
+
+# Short form:
+# a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A"}
+{"Name": "B"}
+{"Name": "B"}
+{"Name": "C"}
+```
+
+#### Grouping
+If you need to two different events to be grouped together, you can set the
+group_by parameter to true on the Event instance creation.  This will cause the
+start and batch methods to send them together.
+
+You can also use the '&' operator (rather than '>>') to set the next event but
+grouped together so the event_time is the same.  Try not to mix the operators
+into long mixed sequences as it can cause problems with the ordering.
+
+### Persistant State
+When creating event flows there is some concepts around how Faker Events works
+that you should get familiar with.
+
+1. The dictionary created is used only as a template for Events
+2. Dictionaries that are identical will be treated as the same flow
+3. Profile Functions should declare a puprose and what needs to be change
+4. Event limit is for each profile created by the generator. (Default is 1)
+
+The following example shows how we create a type of event with the dictionary
+'customer', and then a flow in which a new customer event is made, followed by
+a job change for the customer.
+
+The generator has 2 profiles, and 1 of each event type, resulting in 4 events.
+(Events with a limit of 0 will occur as long as the stream is running, without
+ attempting to switch to the next event, even if one is set.)
+
+```python
+from faker_events import Event, EventGenerator
+from faker import Faker
+
+faker = Faker()
+
+customer = {'Name': 'Unknown', 'Job': None, 'Created': None, 'Updated': None}
+
+def new_customer(event, profile):
+    return {
+        "Name": profile.first_name,
+        "Job": profile.job,
+        "Created": event.time,
+        "Updated": event.time
+    }
+
+def change_job(event, profile):
+    return {
+        "Job": faker.job(),
+        "Updated": event.time
+    }
+
+new_customer_event = Event(customer, new_customer)
+customer_marriged_event = Event(customer, change_job)
+
+new_customer_event >> customer_marriged_event
+
+EventGenerator.set_first_events(new_customer_event)
+```
+
+Output (with two profiles)
+```json
+{"Name": "Ian", "Job": "Medical technical officer", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:55.809062"}
+{"Name": "Eduardo", "Job": "Conservation officer, nature", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:56.316593"}
+{"Name": "Ian", "Job": "Database administrator", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:56.773134"}
+{"Name": "Eduardo", "Job": "Ergonomist", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:57.694891"}
+```
+
+If you need to update the details of the profile, or add persistant data from
+the events you can do so within the Profiled method of the Event instance.
+When using sequenced events, the profile can be used to retrieve the data from
+previous events.
+
+```python
+from faker_events import Event, EventGenerator
+
+
+event_a = {'Name': 'A', 'LastEvent': 'none'}
+
+def profiler_a(event, profile):
+    profile.LastEvent = 'EventA'
+
+event_b = {'Name': 'B', 'LastEvent': 'none'}
+
+def profiler_b(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+    profile.LastEvent = 'EventB'
+
+event_c = {'Name': 'C', 'LastEvent': 'none'}
+
+def profiler_c(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+
+a = Event(event_a, profiler_a, 1)
+b = Event(event_b, profiler_b, 1)
+c = Event(event_c, profiler_c, 1)
+
+a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A", "LastEvent": "none"}
+{"Name": "B", "LastEvent": "EventA"}
+{"Name": "C", "LastEvent": "EventB"}
+```
+
+### Multiple Event Flows
+By grouping the events in lists, the Event Generator is able to work through
+multiple Event Flows for each profile created, creating complex event streams.
+
+```python
+from faker_events import Event, EventGenerator
+
+flow_a1 = Event({"Name": "A1"})
+flow_aa1 = Event({"Name": "AA1"})
+flow_aa2 = Event({"Name": "AA2"})
+
+flow_b1 = Event({"Name": "B1"})
+flow_bb1 = Event({"Name": "BB1"})
+flow_bb2 = Event({"Name": "BB2"})
+
+flow_a1 >> [flow_aa1, flow_aa2]
+flow_b1 >> [flow_bb1, flow_bb2]
+
+EventGeneratoe.set_first_events([flow_a1, flow_b1])
+```
+
+Output
+```json
+{"Name": "B1"}
+{"Name": "BB2"}
+{"Name": "A1"}
+{"Name": "AA1"}
+{"Name": "AA2"}
+{"Name": "BB1"}
+```
+
+### To Do List
+- [ ] Scheduling events with Cron syntax in Batch Mode.
+- [ ] Edge Case testing to produce bad or corrupted data on purpose.
+
+## License
+Faker-Events is released under the MIT License. See the bundled LICENSE file for details.
+
+## Credits
+* [Daniele Faraglia](https://github.com/joke2k) & [Flavio Curella](https://github.com/fcurella) / [Faker](https://github.com/joke2k/faker)
+
+
+
+
+%package help
+Summary:	Development documents and examples for Faker-Events
+Provides:	python3-Faker-Events-doc
+%description help
+# Faker Events
+[![Python appliction](https://github.com/johnbrandborg/faker-events/workflows/Python%20application/badge.svg)](https://github.com/johnbrandborg/faker-events/actions?query=workflow%3A%22Python+application%22)
+[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=johnbrandborg_faker-events&metric=alert_status)](https://sonarcloud.io/dashboard?id=johnbrandborg_faker-events)
+[![PyPI version](https://badge.fury.io/py/Faker-Events.svg)](https://pypi.org/project/Faker-Events/)
+
+Generates Events with formatted fake data for streams. The intention is for
+ development and testing purposes without relying on real data.
+
+## Usage
+Faker Events allows you to create multiple data structures, and events that
+occur randomly or schedule, after which are sent to a data stream or system,
+through the message handler.
+
+The structures can be defined as Python Dictionaries, and processed using a
+function referred to as the profiler.
+
+The Faker package is utilised to generate the data on the profiles.
+Understanding how Faker works is recommended and you can find the documentation
+for it [here](https://faker.readthedocs.io/en/stable/).
+
+Beyond the profiles though for the custom event types any python data
+generation software can be used.
+
+### Installation
+By default faker-events simply prints to standard out.  To use a stream, give
+the option when installing.
+
+**Kafka**
+```bash
+pip install faker-events[kafka]
+```
+
+**Kinesis**
+```bash
+pip install faker-events[kinesis]
+```
+
+### Starting a Stream
+Create an Event Generator and start using Live Stream. By default only 1
+profile is created.  Giving large numbers of profiles can take sometime to
+build, but you can always save them by supplying the profile file name.
+
+Set the "Events Per Minute" when creating the event to change the maximum
+allowed, but subject to system performance also.  The default is 60 per
+minute with a variance of 25%.  Setting the variance to 0% will cause the
+events to not be random.
+
+If you want to see an example of this without writing code, run faker_events
+from the command line.  For help in using the CLI use the -h parameter.
+
+```shell
+faker-events -n 10 -p profiles.json
+```
+
+Output
+```json
+{"event_time": "2022-05-19T22:43:39.683304", "type": "example", "event_id": "1", "user_id": "1009", "first_name": "Brandon", "last_name": "Braun", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:40.291519", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.001050", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:41.358616", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.356265", "type": "example", "event_id": "4", "user_id": "1004", "first_name": "Joseph", "last_name": "Frank", "spent": 71, "status": "normal"}
+{"event_time": "2022-05-19T22:43:42.788833", "type": "example", "event_id": "6", "user_id": "1003", "first_name": "Nathaniel", "last_name": "Garrett", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.106967", "type": "example", "event_id": "7", "user_id": "1000", "first_name": "Jeffrey", "last_name": "Owens", "spent": 0, "status": "normal"}
+{"event_time": "2022-05-19T22:43:43.754115", "type": "example", "event_id": "2", "user_id": "1002", "first_name": "Jonathan", "last_name": "Keith", "spent": 77, "status": "normal"}
+{"event_time": "2022-05-19T22:43:44.121750", "type": "example", "event_id": "3", "user_id": "1001", "first_name": "Lauren", "last_name": "Rodriguez", "spent": 93, "status": "normal"}
+```
+
+If you would like to know more about how this Event Flow was created, read the
+[Example documentation](https://github.com/johnbrandborg/faker-events/blob/main/docs/Example.MD).
+
+
+#### Running a Faker Event Script
+
+You can work with Faker Events interactively in Python, or you can just use
+the class structures in a Python script, and call it using the command line
+interface.
+
+```shell
+faker-events -s fake_users_flow.py -n 1
+```
+
+If you prefer to use Python diretly, use the `start` method on an
+EventGenerator instance, to begin the steam.
+
+
+#### Saving the Profile Data
+
+The profile information created by Faker Events can be saved, so multiple runs
+of the python script will contain the same profile details.
+
+```shell
+faker-events -s fake_users_flow.py -n 100 -p profiles.json
+```
+
+### Using Stream Handlers
+Once you have installed Faker Events with the Stream type you want you
+can now use a stream handler to send the JSON messages to Kakfa, or
+Kinesis.
+
+**Kafka**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kafka', host='kafka:9092', name='example')
+EventGenerator.set_stream(example)
+```
+
+**Kinesis**
+```python
+from faker_events import EventGenerator, Stream
+
+example = Stream(stype='kinesis', name='example', key='key')
+EventGenerator.set_stream(example)
+```
+
+Creating a custom Stream handler is easy.  Just create a Class that has a
+`send` method, which takes the Dictionary of data, and then deliveries it.
+
+**Custom Handler**
+```python
+class CustomStream():
+    def __init__(self, *args, **kwargs):
+        # Store Parameters and Connect to destination
+
+    def send(self, message: Dict) -> None:
+        # Do something with the message
+```
+
+### Starting a Batch
+Create an Event Generator and use the batch method, with a start and finish
+datetime object, and the frequncy like on the live stream.
+
+```python
+from datetime import datetime, timedelta
+
+from faker_events import EventGenerator
+
+start = datetime(2019, 1, 1)  # No one wants to relive 2020...
+finish = start + timedelta(seconds=10)
+
+EventGenerator.batch(start, finish)
+```
+
+## Data Points
+### Event Data Points
+The Event Type has some basic data points about the event that can be used
+within the profiled method. (Access the Attribute using the 'event' within the
+profiler)
+
+* id - The id of the particular event, based on the event dictionary.
+* time - The time the event occured (ISO Format).
+* data - Event Data for updates or augmented assignments.
+
+By default the Event time is local time.  Set the timezone on the generator
+when required.
+
+### Profile Data Points
+When you use the Event Generator, the profiles you will use are created by the
+Profile Generator.  Each profile holds a number of data points. Below is a
+list of attributes that can be used on the 'profile' within the Event Profiler
+function.
+
+* id
+* uuid
+* username
+* gender
+* first_name
+* last_name
+* prefix_name
+* suffix_name
+* birthdate
+* blood_group
+* email
+* employer
+* job
+* full_address1
+* building_number1
+* street_name1
+* street_suffix1
+* state1
+* postcode1
+* city1
+* phone1
+* full_address2
+* building_number2
+* street_name2
+* street_suffix2
+* state2
+* postcode2
+* city2
+* phone2
+* driver_license
+* license_plate
+
+## Profiling Events
+Creating an Event is as easy as just creating a dictionary that is passed into
+the Event Class.  The Event Instance is then just set on the Event Generator,
+and you can then use the 'create_events' method which will return a generator,
+or us the 'start' or 'batch' methods that will handle the generator.
+
+If you want event values to be dynamic, create a profiler functions. The
+function should take two arguments; event and profile.  These carry the attributes
+listed above into the function for updating event values, or even creating new
+key value pairs.
+
+Update the event yourself by using 'event.data', which contains the dictionary
+passed into the Event Class.  The other option is to return a dictionary with
+the key value pairs you want to update.  The Event instance will handle updating
+the values.
+
+The profile is a randomly selected profile from the profiles created by the
+Event Generator.  You can use details from the profile to build our events
+that simulate customers, or entities.
+
+```python
+from faker import Faker
+from faker_events import Event, EventGenerator
+
+fake = Faker()
+
+event = {
+    'Fixed': 'Doesnt Change',
+    'Once': fake.color(),
+    'Always': '',
+    'Profiled': '',
+}
+
+def profiler(event, profile):
+    return {
+        'Always': fake.boolean(),
+        'Profiled': profile.email,
+    }
+
+EventGenerator.set_first_events(Event(event, profiler))
+```
+
+## Event Sequences
+#### Ordered
+You can sequence the events by setting the next event to occur, and occurence
+on how many times it will happen. To have events occur more than once, increase
+the limit.
+
+Either the 'next' attribute can be set with a statement, or the bitwise operator
+can be use to set the next event.
+
+```python
+from faker_events import Event, EventGenerator
+
+a = Event({'Name': 'A'})
+b = Event({'Name': 'B'}, limit=2)
+c = Event({'Name': 'C'})
+
+a.next = b
+b.next = c
+
+# Short form:
+# a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A"}
+{"Name": "B"}
+{"Name": "B"}
+{"Name": "C"}
+```
+
+#### Grouping
+If you need to two different events to be grouped together, you can set the
+group_by parameter to true on the Event instance creation.  This will cause the
+start and batch methods to send them together.
+
+You can also use the '&' operator (rather than '>>') to set the next event but
+grouped together so the event_time is the same.  Try not to mix the operators
+into long mixed sequences as it can cause problems with the ordering.
+
+### Persistant State
+When creating event flows there is some concepts around how Faker Events works
+that you should get familiar with.
+
+1. The dictionary created is used only as a template for Events
+2. Dictionaries that are identical will be treated as the same flow
+3. Profile Functions should declare a puprose and what needs to be change
+4. Event limit is for each profile created by the generator. (Default is 1)
+
+The following example shows how we create a type of event with the dictionary
+'customer', and then a flow in which a new customer event is made, followed by
+a job change for the customer.
+
+The generator has 2 profiles, and 1 of each event type, resulting in 4 events.
+(Events with a limit of 0 will occur as long as the stream is running, without
+ attempting to switch to the next event, even if one is set.)
+
+```python
+from faker_events import Event, EventGenerator
+from faker import Faker
+
+faker = Faker()
+
+customer = {'Name': 'Unknown', 'Job': None, 'Created': None, 'Updated': None}
+
+def new_customer(event, profile):
+    return {
+        "Name": profile.first_name,
+        "Job": profile.job,
+        "Created": event.time,
+        "Updated": event.time
+    }
+
+def change_job(event, profile):
+    return {
+        "Job": faker.job(),
+        "Updated": event.time
+    }
+
+new_customer_event = Event(customer, new_customer)
+customer_marriged_event = Event(customer, change_job)
+
+new_customer_event >> customer_marriged_event
+
+EventGenerator.set_first_events(new_customer_event)
+```
+
+Output (with two profiles)
+```json
+{"Name": "Ian", "Job": "Medical technical officer", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:55.809062"}
+{"Name": "Eduardo", "Job": "Conservation officer, nature", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:56.316593"}
+{"Name": "Ian", "Job": "Database administrator", "Created": "2021-09-28T15:13:55.809062", "Updated": "2021-09-28T15:13:56.773134"}
+{"Name": "Eduardo", "Job": "Ergonomist", "Created": "2021-09-28T15:13:56.316593", "Updated": "2021-09-28T15:13:57.694891"}
+```
+
+If you need to update the details of the profile, or add persistant data from
+the events you can do so within the Profiled method of the Event instance.
+When using sequenced events, the profile can be used to retrieve the data from
+previous events.
+
+```python
+from faker_events import Event, EventGenerator
+
+
+event_a = {'Name': 'A', 'LastEvent': 'none'}
+
+def profiler_a(event, profile):
+    profile.LastEvent = 'EventA'
+
+event_b = {'Name': 'B', 'LastEvent': 'none'}
+
+def profiler_b(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+    profile.LastEvent = 'EventB'
+
+event_c = {'Name': 'C', 'LastEvent': 'none'}
+
+def profiler_c(event, profile):
+    event.data['LastEvent'] = profile.LastEvent
+
+a = Event(event_a, profiler_a, 1)
+b = Event(event_b, profiler_b, 1)
+c = Event(event_c, profiler_c, 1)
+
+a >> b >> c
+
+EventGenerator.set_first_events(a)
+```
+
+Output
+```json
+{"Name": "A", "LastEvent": "none"}
+{"Name": "B", "LastEvent": "EventA"}
+{"Name": "C", "LastEvent": "EventB"}
+```
+
+### Multiple Event Flows
+By grouping the events in lists, the Event Generator is able to work through
+multiple Event Flows for each profile created, creating complex event streams.
+
+```python
+from faker_events import Event, EventGenerator
+
+flow_a1 = Event({"Name": "A1"})
+flow_aa1 = Event({"Name": "AA1"})
+flow_aa2 = Event({"Name": "AA2"})
+
+flow_b1 = Event({"Name": "B1"})
+flow_bb1 = Event({"Name": "BB1"})
+flow_bb2 = Event({"Name": "BB2"})
+
+flow_a1 >> [flow_aa1, flow_aa2]
+flow_b1 >> [flow_bb1, flow_bb2]
+
+EventGeneratoe.set_first_events([flow_a1, flow_b1])
+```
+
+Output
+```json
+{"Name": "B1"}
+{"Name": "BB2"}
+{"Name": "A1"}
+{"Name": "AA1"}
+{"Name": "AA2"}
+{"Name": "BB1"}
+```
+
+### To Do List
+- [ ] Scheduling events with Cron syntax in Batch Mode.
+- [ ] Edge Case testing to produce bad or corrupted data on purpose.
+
+## License
+Faker-Events is released under the MIT License. See the bundled LICENSE file for details.
+
+## Credits
+* [Daniele Faraglia](https://github.com/joke2k) & [Flavio Curella](https://github.com/fcurella) / [Faker](https://github.com/joke2k/faker)
+
+
+
+
+%prep
+%autosetup -n Faker-Events-1.6.0
+
+%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-Faker-Events -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.6.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..cb9ec2e
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+116a1350df1169eecdd000b1ca36ad56  Faker-Events-1.6.0.tar.gz