fp-server | Free proxy server | Crawler library

by Karmenzind Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | fp-server Summary

fp-server is a Python library typically used in Automation, Crawler, Docker applications. fp-server has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

:exclamation: This code really sucks. I'll rewrite it when I have free time. 这项目写的很烂，仅供参考，后续有时间会重构……. A free proxy server based on Tornado and Scrapy.

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Quality

Security

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Support

fp-server has a low active ecosystem.

It has 154 star(s) with 37 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 13 have been closed. On average issues are closed in 165 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of fp-server is current.

Quality

fp-server has 0 bugs and 0 code smells.

Security

fp-server has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fp-server code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fp-server is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

fp-server releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

fp-server saves you 1397 person hours of effort in developing the same functionality from scratch.

It has 3125 lines of code, 230 functions and 63 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed fp-server and discovered the below as its top functions. This is intended to give you an instant insight into fp-server implemented functionality, and help decide if they suit your requirements.

Process the request
Logs the message header
Create a log message
Set proxy information
Check the status of the response
Get local IP address
Merge two configuration dictionaries
Update a single document
Update a record
Convert an object to an ObjectId
Called when an IP fail
Validate a boolean field
Start requests
Returns a list of random keys
Set the status for a key
Query a set of keys
Add a failure to the minion
Start fetch requests
Get all keys status
Get log configuration
Validate field data
Validate dictionary data
Parse the response from the server
Get redis configuration
Return a list of all keys
Start the worker thread

Get all kandi verified functions for this library.

fp-server Key Features

No Key Features are available at this moment for fp-server.

fp-server Examples and Code Snippets

No Code Snippets are available at this moment for fp-server.

Community Discussions

Trending Discussions on fp-server

Vertex AI Model Batch prediction, issue with referencing existing model and input file on Cloud Storage

QUESTION

Vertex AI Model Batch prediction, issue with referencing existing model and input file on Cloud Storage

Asked 2021-Dec-21 at 14:35

I'm struggling to correctly set Vertex AI pipeline which does the following:

read data from API and store to GCS and as as input for batch prediction.
get an existing model (Video classification on Vertex AI)
create Batch prediction job with input from point 1.
As it will be seen, I don't have much experience with Vertex Pipelines/Kubeflow thus I'm asking for help/advice, hope it's just some beginner mistake. this is the gist of the code I'm using as pipeline

...

ANSWER

Answered 2021-Dec-21 at 14:35

I'm glad you solved most of your main issues and found a workaround for model declaration.

For your input.output observation on gcs_source_uris, the reason behind it is because the way the function/class returns the value. If you dig inside the class/methods of google_cloud_pipeline_components you will find that it implements a structure that will allow you to use .outputs from the returned value of the function called.

If you go to the implementation of one of the components of the pipeline you will find that it returns an output array from convert_method_to_component function. So, in order to have that implemented in your custom class/function your function should return a value which can be called as an attribute. Below is a basic implementation of it.

Source https://stackoverflow.com/questions/70356856

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fp-server

Choose either one option as follows. After successful deployment, use the APIs to get proxies.
Install Redis and python>=3.5(I use Python-3.6.5).
Clone this repo.
Install python packages by:
Read the config and modify it according to your need.
Start the server: