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@@ -0,0 +1 @@ +/achilles-0.0.196.tar.gz diff --git a/python-achilles.spec b/python-achilles.spec new file mode 100644 index 0000000..42c3247 --- /dev/null +++ b/python-achilles.spec @@ -0,0 +1,773 @@ +%global _empty_manifest_terminate_build 0 +Name: python-achilles +Version: 0.0.196 +Release: 1 +Summary: Distributed/parallel computing in modern Python based on the multiprocessing.Pool API (map, imap, imap_unordered). +License: MIT License +URL: https://github.com/adpena/achilles +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/0a/e5/853a9df3f78380f34a4e34c1e557e5a08201af99eaae3460e2d3bdef0bbf/achilles-0.0.196.tar.gz +BuildArch: noarch + +Requires: python3-dill +Requires: python3-dotenv +Requires: python3-twisted +Requires: python3-pyyaml +Requires: python3-multiprocess + +%description +# `achilles` +Distributed/parallel computing in modern Python based on the `multiprocessing.Pool` API (`map`, `imap`, `imap_unordered`). + +## What/why is it? +The purpose of `achilles` is to make distributed/parallel computing as easy as possible by limiting the required configuration, hiding the details (server/node/controller architecture) and exposing a simple interface based on the popular `multiprocessing.Pool` API. + +> `achilles` provides developers with entry-level capabilities for concurrency across a network of machines (see PEP 372 on the intent behind adding `multiprocessing` to the standard library -> https://www.python.org/dev/peps/pep-0371/) using a server/node/controller architecture. + +The `achilles_server`, `achilles_node` and `achilles_controller` are designed to run cross-platform/cross-architecture. The server/node/controller may be hosted on a single machine (for development) or deployed across heterogeneous resources. + +`achilles` is comparable to excellent Python packages like `pathos/pyina`, `Parallel Python` and `SCOOP`, but different in certain ways: +- Designed for developers familiar with the `multiprocessing` module in the standard library with simplicity and ease of use in mind. +- In addition to the blocking `map` API which requires that developers wait for all computation to be finished before accessing results (common in such packages), `imap`/`imap_unordered` allow developers to process results as they are returned to the `achilles_controller` by the `achilles_server`. +- `achilles` allows for composable scalability and novel design patterns as: + - Iterables including lists, lists of lists and generator functions (as first-class object - generator expressions will not work as generators cannot be serialized by `pickle`/`dill`) are accepted as arguments. + - TIP: Use generator functions together with `imap` or `imap_unordered` to perform distributed computation on arbitrarily large data. + - The `dill` serializer is used to transfer data between the server/node/controller and `multiprocess` (fork of `multiprocessing` that uses the `dill` serializer instead of `pickle`) is used to perform `Pool.map` on the `achilles_nodes`, so developers are freed from some of the constraints of the `pickle` serializer. + <br/> + +### Install +`pip install achilles` + +### Quick Start +Start an `achilles_server` listening for connections from `achilles_nodes` at a certain endpoint specified as arguments or in an `.env` file in the `achilles` package's directory. + +Then simply import `map`, `imap`, and/or `imap_unordered` from `achilles_main` and use them dynamically in your own code (under the hood they create and close `achilles_controller`s). + +`map`, `imap` and `imap_unordered` will distribute your function to each `achilles_node` connected to the `achilles_server`. Then, the `achilles_server` will distribute arguments to each `achilles_node` (load balanced and made into a list of arguments if the arguments' type is not already a list) which will then perform your function on the arguments using `multiprocess.Pool.map`. + +Each `achilles_node` finishes its work, returns the results to the `achilles_server` and waits to receive another argument. This process is repeated until all of the arguments have been exhausted. + +1) `runAchillesServer(host=None, port=None, username=None, secret_key=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_server import runAchillesServer + + # host = IP address of the achilles_server + # port = port to listen on for connections from achilles_nodes (must be an int) + # username, secret_key used for authentication with achilles_controller + + runAchillesServer(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + ``` + + ```python + + # OR generate an .env file with a default configuration so that + # arguments are no longer required to runAchillesServer() + + # use genConfig() to overwrite + + from achilles.lineReceiver.achilles_server import runAchillesServer, genConfig + + genConfig(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + runAchillesServer() + ``` + <br/> + + `out:` + ``` + ALERT: achilles_server initiated at 127.0.0.1:9999 + Listening for connections... + ``` + +2) `runAchillesNode(host=None, port=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_node import runAchillesNode + + # genConfig() is also available in achilles_node, but only expects host and port arguments + + runAchillesNode(host='127.0.0.1', port=9999) + ``` + <br/> + + `out:` + ``` + GREETING: Welcome! There are currently 1 open connections. + + Connected to achilles_server running at 127.0.0.1:9999 + CLIENT_ID: 0 + ``` + +3) Examples of how to use the 3 most commonly used `multiprocessing.Pool` methods in `achilles`: + <br/> + >> Note: `map`, `imap` and `imap_unordered` currently accept iterables including - but not limited - to lists, lists of lists, and generator functions as `achilles_args`. + + >> Also note: if there isn't already a `.env` configuration file in the `achilles` package directory, must use `genConfig(host, port, username, secret_key)` before using or include `host`, `port`, `username` and `secret_key` as arguments when using `map`, `imap`, `imap_unordered`. + + 1) `map(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import map + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + results = map(achilles_function, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], achilles_callback, chunksize=1) + print(results) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + [[1, 16, 81, 256, 625, 1296, 2401, 4096], [6561, 10000]] + ``` + + 2) `imap(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + ``` + + 3) `imap_unordered(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap_unordered + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap_unordered(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + ``` + +## How `achilles` works + +### Under the hood +- `Twisted` + - An event-driven networking engine written in Python and MIT licensed. +- `dill` + - `dill` extends Python’s `pickle` module for serializing and de-serializing Python objects to the majority of the built-in Python types. +- `multiprocess` + - multiprocess is a fork of multiprocessing that uses `dill` instead of `pickle` for serialization. `multiprocessing` is a package for the Python language which supports the spawning of processes using the API of the standard library’s threading module. + +### Examples +See the `examples` directory for tutorials on various use cases, including: +- Square numbers/run multiple jobs sequentially +- Word count (TO DO) + +### How to kill cluster +```python +from achilles.lineReceiver.achilles_main import killCluster + +# simply use the killCluster() command and verify your intent at the prompt +# killCluster() will search for an .env configuration file in the achilles package's directory + +# if it does not exist, specify host, port, username and secret_key as arguments +# a command is sent to all connected achilles_nodes to stop the Twisted reactor and exit() the process + +# optionally, you can pass command_verified=True to proceed directly with killing the cluster + +killCluster(command_verified=True) +``` + +### Caveats/Things to know +- `achilles_node`s use all of the CPU cores available on the host machine to perform `multiprocess.Pool.map` (`pool = multiprocess.Pool(multiprocess.cpu_count())`). +- `achilles` leaves it up to the developer to ensure that the correct packages are installed on `achilles_node`s to perform the function distributed by the `achilles_server` on behalf of the `achilles_controller`. Current recommended solution is to SSH into each machine and `pip install` a `requirements.txt` file. +- All import statements required by the developer's function, arguments and callback must be included in the definition of the function. +- The `achilles_server` is currently designed to handle one job at a time. For more complicated projects, I highly recommend checking out `Dask` (especially `dask.distributed`) and learning more about directed acyclic graphs (DAGs). +- Fault tolerance: if some `achilles_node` disconnects before returning expected results, the argument will be distributed to another `achilles_node` for computation instead of being lost. +- `callback_error` argument has yet to be implemented, so detailed information regarding errors can only be gleaned from the interpreter used to launch the `achilles_server`, `achilles_node` or `achilles_controller`. Deploying the server/node/controller on a single machine is recommended for development. +- `achilles` performs load balancing at runtime and assigns `achilles_node`s arguments by `cpu_count` * `chunksize`. + - Default `chunksize` is 1. + - Increasing the `chunksize` is an easy way to speed up computation and reduce the amount of time spent transferring data between the server/node/controller. +- If your arguments are already lists, the `chunksize` argument is not used. + - Instead, one argument/list will be distributed to the connected `achilles_node`s at a time. +- If your arguments are load balanced, the results returned are contained in lists of length `achilles_node's cpu_count` * `chunksize`. + - `map`: + - Final result of `map` is an ordered list of load balanced lists (the final result is not flattened). + - `imap`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are ordered. + - The first result will correspond to the next result after the last result in the preceding results packet's list of results. + - Likely to be slower than `immap_unordered` due to `achilles_controller` yielding ordered results. `imap_unordered` (see below) yields results as they are received, while `imap` yields results as they are received only if the argument's `ARGS_COUNTER` is expected based on the length of the `RESULT` list in the preceding results packet. Otherwise, a `result_buffer` is checked for the results packet with the expected `ARGS_COUNTER` and the current results packet is added to the `result_buffer`. If it is not found, `achilles_controller` will not yield results until a results packet with the expected `ARGS_COUNTER` is received. + - `imap_unordered`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are not ordered. + - Results packets are yielded as they are received (after any `achilles_callback` has been performed on it). + - Fastest way of consuming results received from the `achilles_server`. + + +<hr/> + +`achilles` is in the early stages of active development and your suggestions/contributions are kindly welcomed. + +`achilles` is written and maintained by Alejandro Peña. Email me at adpena at gmail dot com. + + + + +%package -n python3-achilles +Summary: Distributed/parallel computing in modern Python based on the multiprocessing.Pool API (map, imap, imap_unordered). +Provides: python-achilles +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-achilles +# `achilles` +Distributed/parallel computing in modern Python based on the `multiprocessing.Pool` API (`map`, `imap`, `imap_unordered`). + +## What/why is it? +The purpose of `achilles` is to make distributed/parallel computing as easy as possible by limiting the required configuration, hiding the details (server/node/controller architecture) and exposing a simple interface based on the popular `multiprocessing.Pool` API. + +> `achilles` provides developers with entry-level capabilities for concurrency across a network of machines (see PEP 372 on the intent behind adding `multiprocessing` to the standard library -> https://www.python.org/dev/peps/pep-0371/) using a server/node/controller architecture. + +The `achilles_server`, `achilles_node` and `achilles_controller` are designed to run cross-platform/cross-architecture. The server/node/controller may be hosted on a single machine (for development) or deployed across heterogeneous resources. + +`achilles` is comparable to excellent Python packages like `pathos/pyina`, `Parallel Python` and `SCOOP`, but different in certain ways: +- Designed for developers familiar with the `multiprocessing` module in the standard library with simplicity and ease of use in mind. +- In addition to the blocking `map` API which requires that developers wait for all computation to be finished before accessing results (common in such packages), `imap`/`imap_unordered` allow developers to process results as they are returned to the `achilles_controller` by the `achilles_server`. +- `achilles` allows for composable scalability and novel design patterns as: + - Iterables including lists, lists of lists and generator functions (as first-class object - generator expressions will not work as generators cannot be serialized by `pickle`/`dill`) are accepted as arguments. + - TIP: Use generator functions together with `imap` or `imap_unordered` to perform distributed computation on arbitrarily large data. + - The `dill` serializer is used to transfer data between the server/node/controller and `multiprocess` (fork of `multiprocessing` that uses the `dill` serializer instead of `pickle`) is used to perform `Pool.map` on the `achilles_nodes`, so developers are freed from some of the constraints of the `pickle` serializer. + <br/> + +### Install +`pip install achilles` + +### Quick Start +Start an `achilles_server` listening for connections from `achilles_nodes` at a certain endpoint specified as arguments or in an `.env` file in the `achilles` package's directory. + +Then simply import `map`, `imap`, and/or `imap_unordered` from `achilles_main` and use them dynamically in your own code (under the hood they create and close `achilles_controller`s). + +`map`, `imap` and `imap_unordered` will distribute your function to each `achilles_node` connected to the `achilles_server`. Then, the `achilles_server` will distribute arguments to each `achilles_node` (load balanced and made into a list of arguments if the arguments' type is not already a list) which will then perform your function on the arguments using `multiprocess.Pool.map`. + +Each `achilles_node` finishes its work, returns the results to the `achilles_server` and waits to receive another argument. This process is repeated until all of the arguments have been exhausted. + +1) `runAchillesServer(host=None, port=None, username=None, secret_key=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_server import runAchillesServer + + # host = IP address of the achilles_server + # port = port to listen on for connections from achilles_nodes (must be an int) + # username, secret_key used for authentication with achilles_controller + + runAchillesServer(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + ``` + + ```python + + # OR generate an .env file with a default configuration so that + # arguments are no longer required to runAchillesServer() + + # use genConfig() to overwrite + + from achilles.lineReceiver.achilles_server import runAchillesServer, genConfig + + genConfig(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + runAchillesServer() + ``` + <br/> + + `out:` + ``` + ALERT: achilles_server initiated at 127.0.0.1:9999 + Listening for connections... + ``` + +2) `runAchillesNode(host=None, port=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_node import runAchillesNode + + # genConfig() is also available in achilles_node, but only expects host and port arguments + + runAchillesNode(host='127.0.0.1', port=9999) + ``` + <br/> + + `out:` + ``` + GREETING: Welcome! There are currently 1 open connections. + + Connected to achilles_server running at 127.0.0.1:9999 + CLIENT_ID: 0 + ``` + +3) Examples of how to use the 3 most commonly used `multiprocessing.Pool` methods in `achilles`: + <br/> + >> Note: `map`, `imap` and `imap_unordered` currently accept iterables including - but not limited - to lists, lists of lists, and generator functions as `achilles_args`. + + >> Also note: if there isn't already a `.env` configuration file in the `achilles` package directory, must use `genConfig(host, port, username, secret_key)` before using or include `host`, `port`, `username` and `secret_key` as arguments when using `map`, `imap`, `imap_unordered`. + + 1) `map(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import map + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + results = map(achilles_function, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], achilles_callback, chunksize=1) + print(results) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + [[1, 16, 81, 256, 625, 1296, 2401, 4096], [6561, 10000]] + ``` + + 2) `imap(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + ``` + + 3) `imap_unordered(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap_unordered + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap_unordered(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + ``` + +## How `achilles` works + +### Under the hood +- `Twisted` + - An event-driven networking engine written in Python and MIT licensed. +- `dill` + - `dill` extends Python’s `pickle` module for serializing and de-serializing Python objects to the majority of the built-in Python types. +- `multiprocess` + - multiprocess is a fork of multiprocessing that uses `dill` instead of `pickle` for serialization. `multiprocessing` is a package for the Python language which supports the spawning of processes using the API of the standard library’s threading module. + +### Examples +See the `examples` directory for tutorials on various use cases, including: +- Square numbers/run multiple jobs sequentially +- Word count (TO DO) + +### How to kill cluster +```python +from achilles.lineReceiver.achilles_main import killCluster + +# simply use the killCluster() command and verify your intent at the prompt +# killCluster() will search for an .env configuration file in the achilles package's directory + +# if it does not exist, specify host, port, username and secret_key as arguments +# a command is sent to all connected achilles_nodes to stop the Twisted reactor and exit() the process + +# optionally, you can pass command_verified=True to proceed directly with killing the cluster + +killCluster(command_verified=True) +``` + +### Caveats/Things to know +- `achilles_node`s use all of the CPU cores available on the host machine to perform `multiprocess.Pool.map` (`pool = multiprocess.Pool(multiprocess.cpu_count())`). +- `achilles` leaves it up to the developer to ensure that the correct packages are installed on `achilles_node`s to perform the function distributed by the `achilles_server` on behalf of the `achilles_controller`. Current recommended solution is to SSH into each machine and `pip install` a `requirements.txt` file. +- All import statements required by the developer's function, arguments and callback must be included in the definition of the function. +- The `achilles_server` is currently designed to handle one job at a time. For more complicated projects, I highly recommend checking out `Dask` (especially `dask.distributed`) and learning more about directed acyclic graphs (DAGs). +- Fault tolerance: if some `achilles_node` disconnects before returning expected results, the argument will be distributed to another `achilles_node` for computation instead of being lost. +- `callback_error` argument has yet to be implemented, so detailed information regarding errors can only be gleaned from the interpreter used to launch the `achilles_server`, `achilles_node` or `achilles_controller`. Deploying the server/node/controller on a single machine is recommended for development. +- `achilles` performs load balancing at runtime and assigns `achilles_node`s arguments by `cpu_count` * `chunksize`. + - Default `chunksize` is 1. + - Increasing the `chunksize` is an easy way to speed up computation and reduce the amount of time spent transferring data between the server/node/controller. +- If your arguments are already lists, the `chunksize` argument is not used. + - Instead, one argument/list will be distributed to the connected `achilles_node`s at a time. +- If your arguments are load balanced, the results returned are contained in lists of length `achilles_node's cpu_count` * `chunksize`. + - `map`: + - Final result of `map` is an ordered list of load balanced lists (the final result is not flattened). + - `imap`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are ordered. + - The first result will correspond to the next result after the last result in the preceding results packet's list of results. + - Likely to be slower than `immap_unordered` due to `achilles_controller` yielding ordered results. `imap_unordered` (see below) yields results as they are received, while `imap` yields results as they are received only if the argument's `ARGS_COUNTER` is expected based on the length of the `RESULT` list in the preceding results packet. Otherwise, a `result_buffer` is checked for the results packet with the expected `ARGS_COUNTER` and the current results packet is added to the `result_buffer`. If it is not found, `achilles_controller` will not yield results until a results packet with the expected `ARGS_COUNTER` is received. + - `imap_unordered`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are not ordered. + - Results packets are yielded as they are received (after any `achilles_callback` has been performed on it). + - Fastest way of consuming results received from the `achilles_server`. + + +<hr/> + +`achilles` is in the early stages of active development and your suggestions/contributions are kindly welcomed. + +`achilles` is written and maintained by Alejandro Peña. Email me at adpena at gmail dot com. + + + + +%package help +Summary: Development documents and examples for achilles +Provides: python3-achilles-doc +%description help +# `achilles` +Distributed/parallel computing in modern Python based on the `multiprocessing.Pool` API (`map`, `imap`, `imap_unordered`). + +## What/why is it? +The purpose of `achilles` is to make distributed/parallel computing as easy as possible by limiting the required configuration, hiding the details (server/node/controller architecture) and exposing a simple interface based on the popular `multiprocessing.Pool` API. + +> `achilles` provides developers with entry-level capabilities for concurrency across a network of machines (see PEP 372 on the intent behind adding `multiprocessing` to the standard library -> https://www.python.org/dev/peps/pep-0371/) using a server/node/controller architecture. + +The `achilles_server`, `achilles_node` and `achilles_controller` are designed to run cross-platform/cross-architecture. The server/node/controller may be hosted on a single machine (for development) or deployed across heterogeneous resources. + +`achilles` is comparable to excellent Python packages like `pathos/pyina`, `Parallel Python` and `SCOOP`, but different in certain ways: +- Designed for developers familiar with the `multiprocessing` module in the standard library with simplicity and ease of use in mind. +- In addition to the blocking `map` API which requires that developers wait for all computation to be finished before accessing results (common in such packages), `imap`/`imap_unordered` allow developers to process results as they are returned to the `achilles_controller` by the `achilles_server`. +- `achilles` allows for composable scalability and novel design patterns as: + - Iterables including lists, lists of lists and generator functions (as first-class object - generator expressions will not work as generators cannot be serialized by `pickle`/`dill`) are accepted as arguments. + - TIP: Use generator functions together with `imap` or `imap_unordered` to perform distributed computation on arbitrarily large data. + - The `dill` serializer is used to transfer data between the server/node/controller and `multiprocess` (fork of `multiprocessing` that uses the `dill` serializer instead of `pickle`) is used to perform `Pool.map` on the `achilles_nodes`, so developers are freed from some of the constraints of the `pickle` serializer. + <br/> + +### Install +`pip install achilles` + +### Quick Start +Start an `achilles_server` listening for connections from `achilles_nodes` at a certain endpoint specified as arguments or in an `.env` file in the `achilles` package's directory. + +Then simply import `map`, `imap`, and/or `imap_unordered` from `achilles_main` and use them dynamically in your own code (under the hood they create and close `achilles_controller`s). + +`map`, `imap` and `imap_unordered` will distribute your function to each `achilles_node` connected to the `achilles_server`. Then, the `achilles_server` will distribute arguments to each `achilles_node` (load balanced and made into a list of arguments if the arguments' type is not already a list) which will then perform your function on the arguments using `multiprocess.Pool.map`. + +Each `achilles_node` finishes its work, returns the results to the `achilles_server` and waits to receive another argument. This process is repeated until all of the arguments have been exhausted. + +1) `runAchillesServer(host=None, port=None, username=None, secret_key=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_server import runAchillesServer + + # host = IP address of the achilles_server + # port = port to listen on for connections from achilles_nodes (must be an int) + # username, secret_key used for authentication with achilles_controller + + runAchillesServer(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + ``` + + ```python + + # OR generate an .env file with a default configuration so that + # arguments are no longer required to runAchillesServer() + + # use genConfig() to overwrite + + from achilles.lineReceiver.achilles_server import runAchillesServer, genConfig + + genConfig(host='127.0.0.1', port=9999, username='foo', secret_key='bar') + runAchillesServer() + ``` + <br/> + + `out:` + ``` + ALERT: achilles_server initiated at 127.0.0.1:9999 + Listening for connections... + ``` + +2) `runAchillesNode(host=None, port=None)` -> run on your local machine or on another machine connected to your network + + `in:` + ```python + from achilles.lineReceiver.achilles_node import runAchillesNode + + # genConfig() is also available in achilles_node, but only expects host and port arguments + + runAchillesNode(host='127.0.0.1', port=9999) + ``` + <br/> + + `out:` + ``` + GREETING: Welcome! There are currently 1 open connections. + + Connected to achilles_server running at 127.0.0.1:9999 + CLIENT_ID: 0 + ``` + +3) Examples of how to use the 3 most commonly used `multiprocessing.Pool` methods in `achilles`: + <br/> + >> Note: `map`, `imap` and `imap_unordered` currently accept iterables including - but not limited - to lists, lists of lists, and generator functions as `achilles_args`. + + >> Also note: if there isn't already a `.env` configuration file in the `achilles` package directory, must use `genConfig(host, port, username, secret_key)` before using or include `host`, `port`, `username` and `secret_key` as arguments when using `map`, `imap`, `imap_unordered`. + + 1) `map(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import map + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + results = map(achilles_function, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], achilles_callback, chunksize=1) + print(results) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + [[1, 16, 81, 256, 625, 1296, 2401, 4096], [6561, 10000]] + ``` + + 2) `imap(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + ``` + + 3) `imap_unordered(func, args, callback=None, chunksize=1, host=None, port=None, username=None, secret_key=None)`<br/><br/> + `in:` + ```python + from achilles.lineReceiver.achilles_main import imap_unordered + + def achilles_function(arg): + return arg ** 2 + + def achilles_callback(result): + return result ** 2 + + if __name__ == "__main__": + for result in imap_unordered(achilles_function, [1,2,3,4,5,6,7,8,9,10], achilles_callback, chunksize=1): + print(result) + ``` + <br/> + + `out:` + ``` + ALERT: Connection to achilles_server at 127.0.0.1:9999 and authentication successful. + + {'ARGS_COUNTER': 8, 'RESULT': [6561, 10000]} + {'ARGS_COUNTER': 0, 'RESULT': [1, 16, 81, 256, 625, 1296, 2401, 4096]} + ``` + +## How `achilles` works + +### Under the hood +- `Twisted` + - An event-driven networking engine written in Python and MIT licensed. +- `dill` + - `dill` extends Python’s `pickle` module for serializing and de-serializing Python objects to the majority of the built-in Python types. +- `multiprocess` + - multiprocess is a fork of multiprocessing that uses `dill` instead of `pickle` for serialization. `multiprocessing` is a package for the Python language which supports the spawning of processes using the API of the standard library’s threading module. + +### Examples +See the `examples` directory for tutorials on various use cases, including: +- Square numbers/run multiple jobs sequentially +- Word count (TO DO) + +### How to kill cluster +```python +from achilles.lineReceiver.achilles_main import killCluster + +# simply use the killCluster() command and verify your intent at the prompt +# killCluster() will search for an .env configuration file in the achilles package's directory + +# if it does not exist, specify host, port, username and secret_key as arguments +# a command is sent to all connected achilles_nodes to stop the Twisted reactor and exit() the process + +# optionally, you can pass command_verified=True to proceed directly with killing the cluster + +killCluster(command_verified=True) +``` + +### Caveats/Things to know +- `achilles_node`s use all of the CPU cores available on the host machine to perform `multiprocess.Pool.map` (`pool = multiprocess.Pool(multiprocess.cpu_count())`). +- `achilles` leaves it up to the developer to ensure that the correct packages are installed on `achilles_node`s to perform the function distributed by the `achilles_server` on behalf of the `achilles_controller`. Current recommended solution is to SSH into each machine and `pip install` a `requirements.txt` file. +- All import statements required by the developer's function, arguments and callback must be included in the definition of the function. +- The `achilles_server` is currently designed to handle one job at a time. For more complicated projects, I highly recommend checking out `Dask` (especially `dask.distributed`) and learning more about directed acyclic graphs (DAGs). +- Fault tolerance: if some `achilles_node` disconnects before returning expected results, the argument will be distributed to another `achilles_node` for computation instead of being lost. +- `callback_error` argument has yet to be implemented, so detailed information regarding errors can only be gleaned from the interpreter used to launch the `achilles_server`, `achilles_node` or `achilles_controller`. Deploying the server/node/controller on a single machine is recommended for development. +- `achilles` performs load balancing at runtime and assigns `achilles_node`s arguments by `cpu_count` * `chunksize`. + - Default `chunksize` is 1. + - Increasing the `chunksize` is an easy way to speed up computation and reduce the amount of time spent transferring data between the server/node/controller. +- If your arguments are already lists, the `chunksize` argument is not used. + - Instead, one argument/list will be distributed to the connected `achilles_node`s at a time. +- If your arguments are load balanced, the results returned are contained in lists of length `achilles_node's cpu_count` * `chunksize`. + - `map`: + - Final result of `map` is an ordered list of load balanced lists (the final result is not flattened). + - `imap`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are ordered. + - The first result will correspond to the next result after the last result in the preceding results packet's list of results. + - Likely to be slower than `immap_unordered` due to `achilles_controller` yielding ordered results. `imap_unordered` (see below) yields results as they are received, while `imap` yields results as they are received only if the argument's `ARGS_COUNTER` is expected based on the length of the `RESULT` list in the preceding results packet. Otherwise, a `result_buffer` is checked for the results packet with the expected `ARGS_COUNTER` and the current results packet is added to the `result_buffer`. If it is not found, `achilles_controller` will not yield results until a results packet with the expected `ARGS_COUNTER` is received. + - `imap_unordered`: + - Results are returned as computation is finished in dictionaries that include the following keys: + - `RESULT`: load balanced list of results. + - `ARGS_COUNTER`: index of first argument (0-indexed). + - Results are not ordered. + - Results packets are yielded as they are received (after any `achilles_callback` has been performed on it). + - Fastest way of consuming results received from the `achilles_server`. + + +<hr/> + +`achilles` is in the early stages of active development and your suggestions/contributions are kindly welcomed. + +`achilles` is written and maintained by Alejandro Peña. Email me at adpena at gmail dot com. + + + + +%prep +%autosetup -n achilles-0.0.196 + +%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-achilles -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.196-1 +- Package Spec generated @@ -0,0 +1 @@ +786265e746e4155da4e17ecc56f04672 achilles-0.0.196.tar.gz |