greenlet | 🦎 Move an async function into its own thread | Architecture library
kandi X-RAY | greenlet Summary
kandi X-RAY | greenlet Summary
Move an async function into its own thread. A simplified single-function version of workerize, offering the same performance as direct Worker usage. The name is somewhat of a poor choice, but it was available on npm.
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QUESTION
I am beginner on docker and i am trying to run a flask python app and I have the following problem when running docker-compose up, throws error:
ModuleNotFoundError: No module named 'sqlalchemy'
This is a picture of the error: docker-compose up error
This is the files in my current directory my local directory
this is the content of my dockerfile
...ANSWER
Answered 2022-Apr-11 at 18:25Try with the following:
QUESTION
I am trying to start my heroku app with a python flask app, but I am getting the h10 error and the only thing I can see in the log is the Tkinter not found but I am not using Tkinter in this project please help. I've been searching on the web and on other stack overflow questions, but most just say to make sure you don't declare a port or some js server thing. I haven't found anything that helps and when I read the log all I see is the Tkinter but I tried to purge it from my code but it still tries to call it.
...ANSWER
Answered 2022-Mar-16 at 10:50The immediate problem is caused by the following import:
QUESTION
I am trying to build an app from a python file (Mac OS) using the py2app extension. I have a folder with the python file and the "setup.py" file.
- I first tested the app by running
python setup.py py2app -Ain the terminal and the dist and build folder are successfully created and the app works when launched. - Now when I try to build it non-locally by running the command
python setup.py py2appin the terminal, there are various "WARNING: ImportERROR" messages while building and finally aerror: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib'error.
How can I fix this? I've tried to delete anaconda fully as I don't use it but it seems to still want to run through it. Additionally, I have tried to run the build command using a virtual environment but I end up having even more import errors.
*I Left out a lot of the "skipping" and "warning" lines using "..." for space
ANSWER
Answered 2022-Mar-13 at 16:13The error error: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib' was caused by py2app trying to build the program bundle using a non-existent interpreter. This means that even if you try to uninstall a manager like Anaconda, it still has option logs somewhere on your mac.
The fix:
- Open the terminal and type the command
type -a python.
- You will see similar lines
QUESTION
I'm trying to incorporate google-cloud-tasks Python client within my fastapi app. But it's giving me an import error like this:
ANSWER
Answered 2022-Feb-09 at 17:35After doing some more research online I realized that installation of some packages is missed due to some existing packages. This issue helped me realize I need to reorder the position of google-cloud-tasks in my requirements.txt. So what I did was pretty simple, created a new virtualenv installed google-cloud-tasks as my first package and then installed everything else and finally the problem is solved.
Long story short the issue is the order in which packages are installed and that's why some packages are getting missed.
QUESTION
My framework (Locust, https://github.com/locustio/locust) is based on gevent and greenlets. But I would like to leverage Playwright (https://playwright.dev/python/), which is built on asyncio.
Naively using Playwrights sync api doesnt work and gives an exception:
...ANSWER
Answered 2022-Feb-05 at 20:45Insipred by @user4815162342 's comment, I went with something like this:
QUESTION
I am using FastApi and My responseModel is being ignored. I am attempting to NOT return the password field in the response. Why does FastApi ignore my responsemodel definition?
Here is my api post method:
...ANSWER
Answered 2022-Feb-05 at 11:29response_model is an argument to the view decorator (since it's metadata about the view itself), not to the view function (which takes arguments that are necessary for how to process the view):
QUESTION
The title says it all. It seems better and faster to use one of the methods belonging to gevent.Pool to run greenlets in parallel (sort-of) in a pool, as opposed to gevent.joinall(). What are the pros and cons of each approach?
...ANSWER
Answered 2022-Jan-24 at 14:46I think the key difference is not raw performance but instead performance management. When you use gevent.joinall() you have to do your own management of how many greenlets exist at once. The naive implementation would create as many as might be needed by the request for the computation.
On the other hand gevent.Pool can easily be configured to cap how many are running at once and thus protect against running your application out of resources.
As usual, it's tradeoffs. Your pool may run slower because it potentially won't allow as many greenlets to run as would a naive implementation using gevent.joinall(), however, you are less likely to run your application out of resources (and cascade into other errors).
Ultimately you have to answer questions like this: Are you likely to get too large of requests? Do you have plenty of resources to draw from? Is raw peak performance more important than average reliability?
QUESTION
I am working with a Python server which spawns a greenlet for each connection to the server. Currently, the server doesn't make use of a greenlet pool. While it was my hunch that using a pool would improve performance (mainly response time and requests-per-second throughput), in my trial-and-error implementing a pool of greenlets, there doesn't seem be much performance benefit over just using Gevent.spawn() for each greenlet/connection.
I have seen this question, which is helpful, although I am curious about the application of a greenlet pool, like Gevent Pool, in a server. Is this a useful pattern, a la thread pool? Or, does using a Pool not matter in the case of a server, since Greenlets are so lightweight compared with threads?
...ANSWER
Answered 2022-Jan-14 at 14:47Greenlets are lightweight but they do consume memory. So, even though the number of greenlets a process can support is going to be much larger than the number of threads the OS can support, there is still a cost to them. So a pool is still a useful tool for limiting the number of greenlets that can be spawned - but its size would likely be best set considerably larger than a limit for actual threads would be.
Also, due to their cooperative multitasking nature, the latency on each request (assuming each new request is handled by a new greenlet) would start to rise as the number of greenlets increases beyond a certain threshold. There's a tradeoff between allowing more requests at once and creating poor UX when each request takes an increasing amount of time to complete. It's sometimes better to cap your incoming load and reject new requests - and a pool is a useful way to do that.
QUESTION
import asyncio
from sqlalchemy import Column
from sqlalchemy import DateTime
from sqlalchemy import ForeignKey
from sqlalchemy import func
from sqlalchemy import Integer
from sqlalchemy import String
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.future import select
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import relationship
from sqlalchemy.orm import selectinload
from sqlalchemy.orm import sessionmaker
engine = create_async_engine(
"postgresql+asyncpg://user:pass@localhost/db",
echo=True,
)
# expire_on_commit=False will prevent attributes from being expired
# after commit.
async_session = sessionmaker(
engine, expire_on_commit=False, class_=AsyncSession
)
Base = declarative_base()
class A(Base):
__tablename__ = "a"
id = Column(Integer, primary_key=True)
name = Column(String, unique=True)
data = Column(String)
create_date = Column(DateTime, server_default=func.now())
bs = relationship("B")
# required in order to access columns with server defaults
# or SQL expression defaults, subsequent to a flush, without
# triggering an expired load
__mapper_args__ = {"eager_defaults": True}
class B(Base):
__tablename__ = "b"
id = Column(Integer, primary_key=True)
a_id = Column(ForeignKey("a.id"))
data = Column(String)
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.drop_all)
await conn.run_sync(Base.metadata.create_all)
async with async_session() as session:
async with session.begin():
session.add_all(
[
A(bs=[B(), B()], data="a1"),
A(bs=[B()], data="a2"),
]
)
async with async_session() as session:
result = await session.execute(select(A).order_by(A.id))
a1 = result.scalars().first()
# no issue:
print(a1.name, a1.data)
# throws error:
print(a1.bs)
ANSWER
Answered 2022-Jan-07 at 02:14This is how:
QUESTION
i using VSCode as my IDE for development odoo and for now run using Start > Debugging ( F5)
While running at web browser localhost:8069 ( default ) then appear Internal Server Error and in terminal VSCode there are errors :
...ANSWER
Answered 2021-Dec-27 at 17:01After trying for a few days and just found out that pip and python in the project are not pointing to .venv but to anaconda due to an update. when error
no module stdnum
actually there is a problem with pip so make sure your pip path with which pip or which python
- to solve .venv that doesn't work by deleting the .venv folder, create venv in python, and install all requirements again
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