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Andrew Svetlov asvetlov Neuromation Kiev http://asvetlov.blogspot.com CPython Core Developer, aiohttp maintainer

aio-libs/yarl 565

Yet another URL library

aio-libs/aiobotocore 559

asyncio support for botocore library using aiohttp

aio-libs/aiozmq 346

Asyncio (pep 3156) integration with ZeroMQ

aio-libs/async_lru 203

Simple lru cache for asyncio

aio-libs/aiohttp_admin 201

admin interface for aiohttp application http://aiohttp-admin.readthedocs.io

aio-libs/multidict 200

The multidict implementation

aio-libs/aioodbc 189

aioodbc - is a library for accessing a ODBC databases from the asyncio

aio-libs/aioelasticsearch 122

aioelasticsearch-py wrapper for asyncio

aio-libs/aioftp 102

ftp client/server for asyncio (http://aioftp.readthedocs.org)

aio-libs/aiocassandra 84

Simple threaded cassandra wrapper for asyncio

Pull request review commentneuro-inc/neuro-flow

Cache

 async def with_action(             raise RuntimeError("Use .with_task() for calling an task-typed task")          assert isinstance(prep_task, PrepBatchCallCtx)-        action = await self.fetch_action(prep_task.action)+        action, digest = await self.fetch_action(prep_task.action)

Wait, the digest is re-calculated in ActionContext.create(), at the moment of caching it is never None or empty. I've added an explicit check to storage:_ctx_default function

asvetlov

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Implemet clear-cache command

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Pull request review commentneuro-inc/neuro-flow

Cache

 async def with_action(             raise RuntimeError("Use .with_task() for calling an task-typed task")          assert isinstance(prep_task, PrepBatchCallCtx)-        action = await self.fetch_action(prep_task.action)+        action, digest = await self.fetch_action(prep_task.action)

You are right

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pull request commentneuro-inc/neuro-flow

Cache

I don't follow why do you call that the action has more aggressive caching. A task depends on the needs context, yaml file with the task definition inside, and contexts for the task call generation: image, tags, env-vars, etc. The action call depends on inputs and the yaml definition file again. Where do you see the difference?

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Pull request review commentneuro-inc/neuro-flow

Cache

 outputs:   needs: ["task_1_${{ inputs.arg1 }}_second", task_2]   res1:     descr: action result 1-    value: ${{ to_json(needs) }}+    value: ${{ fmt('task_1_{}_second', inputs.arg1) }}.needs.task1 task_2.needs.task2

My bad. Please check the third version

asvetlov

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Pull request review commentneuro-inc/neuro-flow

Cache

 def _attempt_from_json(         number=init_data["number"],         result=result,     )+++def _mk_cache_uri(attempt: Attempt, task_id: FullID) -> URL:+    return (+        URL("storage:.flow")+        / attempt.bake.project+        / ".cache"+        / attempt.bake.batch+        / (".".join(task_id) + ".json")+    )+++def _hash(val: Any) -> str:+    hasher = hashlib.new("sha256")+    data = json.dumps(val, sort_keys=True, default=_ctx_default)+    hasher.update(data.encode("utf-8"))+    return hasher.hexdigest()+++def _ctx_default(val: Any) -> Any:+    if isinstance(val, BaseContext):+        ret: Dict[str, Any] = {+            "env": val.env,+            "tags": val.tags,+            "digest": val.digest,+        }+        if isinstance(val, ActionContext):+            ret.update(+                {+                    "inputs": val.inputs,+                }+            )+        elif isinstance(val, TaskContext):+            ret.update(+                {+                    "needs": val.needs,+                    "matrix": val.matrix,+                    "strategy": val.strategy,+                    "task": val.task,+                }+            )+        return ret+    elif dataclasses.is_dataclass(val):+        return dataclasses.asdict(val)+    elif isinstance(val, enum.Enum):+        return val.value+    elif isinstance(val, RemotePath):+        return str(val)+    elif isinstance(val, collections.abc.Set):+        return sorted(val)+    else:+        raise TypeError(f"Cannot dump {val!r}")+++def _result_default(val: Any) -> Any:

You are right. It is an artifact of earlier implementation.

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Drop unused function

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Pull request review commentneuro-inc/neuro-flow

Cache

 def parse_flow_main(ctor: BaseConstructor, node: yaml.MappingNode) -> ast.BaseFl FlowLoader.add_constructor("flow:main", parse_flow_main)  # type: ignore  -def parse_live(workspace: LocalPath, config_file: LocalPath) -> ast.LiveFlow:+def parse_live(+    workspace: LocalPath, config_file: LocalPath+) -> Tuple[ast.LiveFlow, Digest]:     # Parse live flow config file+    hasher = hashlib.new("sha256")+    with config_file.open("rb") as bf:

Ideally, both hash calculation and yaml construction should be done in the single iteration over the file. It is not done yet but I'd like to keep this bad-smelling code as is until the future improvement. Perhaps, it will be a custom yaml.Reader instance.

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Pull request review commentneuro-inc/neuro-flow

Cache

 async def _include(             ret.append({k: await v.eval(self) for k, v in dct.items()})         return ret +    async def _build_cache(+        self, ast_cache: Optional[ast.Cache], default: ast.CacheStrategy+    ) -> CacheCtx:+        if ast_cache is None:+            return self.cache+        strategy = ast_cache.strategy+        if strategy is None:+            strategy = default+        if strategy == ast.CacheStrategy.INHERIT:+            strategy = self.cache.strategy+        life_span = await ast_cache.life_span.eval(self)+        if life_span is None:+            life_span = self.cache.life_span+        else:+            life_span = min(self.cache.life_span, life_span)+        return CacheCtx(strategy=strategy, life_span=life_span)+  @dataclass(frozen=True) class BatchContext(TaskContext, BaseFlowContext):     FLOW_TYPE: ClassVar[Type[ast.BatchFlow]] = field(init=False, default=ast.BatchFlow)     LOOKUP_KEYS: ClassVar[Tuple[str, ...]] = field(         init=False,-        default=BaseFlowContext.LOOKUP_KEYS-        + TaskContext.LOOKUP_KEYS-        + ("args", "needs"),+        default=BaseFlowContext.LOOKUP_KEYS + TaskContext.LOOKUP_KEYS + ("args",),     )     _args: Optional[Mapping[str, str]] = None      @classmethod     async def create(         cls: Type[_CtxT],         ast_flow: ast.BaseFlow,+        flow_digest: Digest,         workspace: LocalPath,         config_file: LocalPath,     ) -> _CtxT:         ctx = await super(cls, BatchContext).create(             ast_flow,+            flow_digest,             workspace,             config_file,         )         ast_defaults = ast_flow.defaults+        ctx = replace(ctx, _cache=CacheCtx())

I was thinking about pushing the project default cache strategy in project.yml but did not implement it yet. The example makes value with the mentioned case.

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Fix example

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Pull request review commentneuro-inc/neuro-flow

Cache

 outputs:   needs: ["task_1_${{ inputs.arg1 }}_second", task_2]   res1:     descr: action result 1-    value: ${{ to_json(needs) }}+    value: ${{ fmt('task_1_', 'inputs.arg1', '_second') }}.needs.task1 task_2.needs.task2

Uups. My wrong. The initial problem was that the needs context has no stable order. The update has the fixed expression

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Cache everything

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pull request commentneuro-inc/neuro-flow

Example of non-linear DAG

You can but I had a thought that you wanted to apply a matrix to dataset and avg calculations.

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Bump isort from 5.5.3 to 5.5.4 (#90) Bumps [isort](https://github.com/pycqa/isort) from 5.5.3 to 5.5.4. - [Release notes](https://github.com/pycqa/isort/releases) - [Changelog](https://github.com/PyCQA/isort/blob/develop/CHANGELOG.md) - [Commits](https://github.com/pycqa/isort/compare/5.5.3...5.5.4) Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

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Move out cli and add autocomplete support (#89) * Move out cli and add autocomplete support * Make completion patch idempotent Co-authored-by: Andrew Svetlov <andrew.svetlov@gmail.com> Co-authored-by: Andrew Svetlov <andrew.svetlov@gmail.com>

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Merge branch 'master' into cache

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Pull request review commentneuro-inc/neuro-flow

Move out cli and add autocomplete support

+import click+import os+import sys++from neuro_flow.cli.utils import wrap_async+from neuro_flow.types import LocalPath+++CFG_FILE = {"bash": LocalPath("~/.bashrc"), "zsh": LocalPath("~/.zshrc")}+SOURCE_CMD = {"bash": "source", "zsh": "source_zsh"}++ACTIVATION_TEMPLATE = 'eval "$(_NEURO_FLOW_COMPLETE={cmd} {exe})"'+++@click.group()+def completion() -> None:+    """+    Output shell completion code.+    """+++@completion.command()+@click.argument("shell", type=click.Choice(["bash", "zsh"]))+@wrap_async(pass_obj=False)+async def generate(shell: str) -> None:+    """+    Provide an instruction for shell completion generation.+    """+    click.echo(f"Push the following line into your {CFG_FILE[shell]}")+    click.echo(ACTIVATION_TEMPLATE.format(cmd=SOURCE_CMD[shell], exe=sys.argv[0]))+++@completion.command()+@click.argument("shell", type=click.Choice(["bash", "zsh"]))+@wrap_async(pass_obj=False)+async def patch(shell: str) -> None:+    """+    Automatically patch shell configuration profile to enable completion+    """+    GENERATED_START = (+        b"# Start of generated by neuro-flow. Please do not edit this comment.\n"+    )+    GENERATED_END = (+        b"\n# End of generated by neuro-flow. Please do not edit this comment.\n"+    )++    profile_file = CFG_FILE[shell].expanduser()++    code = (+        GENERATED_START+        + os.fsencode(+            ACTIVATION_TEMPLATE.format(cmd=SOURCE_CMD[shell], exe=sys.argv[0])+        )+        + GENERATED_END+    )++    try:+        with profile_file.open("rb+") as profile:+            content = profile.read()+    except FileNotFoundError:+        content = b""++    start = content.find(GENERATED_START)+    if start != -1:+        end = content.find(GENERATED_END)+        if end == -1:+            raise click.ClickException(+                f"Malformed guarding comments. Please modify {profile_file} manually"
                f"Malformed guarding comments. Please edit {profile_file} manually"
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Use digests everywhere

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Bump cryptography from 3.1 to 3.1.1 (#1756) Bumps [cryptography](https://github.com/pyca/cryptography) from 3.1 to 3.1.1. - [Release notes](https://github.com/pyca/cryptography/releases) - [Changelog](https://github.com/pyca/cryptography/blob/master/CHANGELOG.rst) - [Commits](https://github.com/pyca/cryptography/compare/3.1...3.1.1) Signed-off-by: dependabot-preview[bot] <support@dependabot.com> Co-authored-by: dependabot-preview[bot] <27856297+dependabot-preview[bot]@users.noreply.github.com>

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Bump cryptography from 3.1 to 3.1.1 dependencies

Bumps cryptography from 3.1 to 3.1.1. <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/pyca/cryptography/blob/master/CHANGELOG.rst">cryptography's changelog</a>.</em></p> <blockquote> <h1>3.1.1 - 2020-09-22</h1> <ul> <li>Updated Windows, macOS, and <code>manylinux</code> wheels to be compiled with OpenSSL 1.1.1h.</li> </ul> </blockquote> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/pyca/cryptography/commit/d4e17ea937a50d69f615f7fe53d0482bd8660bb9"><code>d4e17ea</code></a> 3.1.1 release (<a href="https://github-redirect.dependabot.com/pyca/cryptography/issues/5475">#5475</a>)</li> <li>See full diff in <a href="https://github.com/pyca/cryptography/compare/3.1...3.1.1">compare view</a></li> </ul> </details> <br />

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