crawler-py | 分享一些爬虫脚本 | Crawler library

by abbeyokgo Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(7)Vulnerabilities Install Support

kandi X-RAY | crawler-py Summary

crawler-py is a Python library typically used in Automation, Crawler applications. crawler-py has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However crawler-py build file is not available. You can download it from GitHub.

分享一些爬虫脚本

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Quality

Security

License

Reuse

Support

crawler-py has a low active ecosystem.

It has 113 star(s) with 78 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. On average issues are closed in 48 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of crawler-py is current.

Quality

crawler-py has 0 bugs and 0 code smells.

Security

crawler-py has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

crawler-py code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

crawler-py 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

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

crawler-py has no build file. You will be need to create the build yourself to build the component from source.

crawler-py saves you 207 person hours of effort in developing the same functionality from scratch.

It has 509 lines of code, 36 functions and 5 files.

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

Top functions reviewed by kandi - BETA

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

downloads a file from a filename
Main entry point .
load data from file
get list of videos
write images to file
download image from text
downloads a video
Return content of given URL .
get posts from uid
Checks if the given id exists in the history . txt file .

Get all kandi verified functions for this library.

crawler-py Key Features

No Key Features are available at this moment for crawler-py.

crawler-py Examples and Code Snippets

No Code Snippets are available at this moment for crawler-py.

Community Discussions

Trending Discussions on crawler-py

Can I write custom query in Google BigQuery Connector for AWS Glue?

AWS Glue Exclude Patterns

Is there any method to concatenate/unite DynamicFrame objects in AWS GLue?

dy.drop_fields() vs DropFields.apply()

What is catalog_connection param in aws glue?

What options can be passed to AWS Glue DynamicFrame.toDF()?

Calling getResolvedOptions() in Local Environment Generates KeyError

QUESTION

Can I write custom query in Google BigQuery Connector for AWS Glue?

Asked 2022-Mar-24 at 06:45

I'm creating a Glue ETL job that transfers data from BigQuery to S3. Similar to this example, but with my own dataset.
n.b.: I use BigQuery Connector for AWS Glue v0.22.0-2 (link).

The data in BigQuery is already partitioned by date, and I would like to have every Glue job run fetches a specific date only (WHERE date = ...) and group them into 1 CSV file output. But I don't find any clue where to insert the custom WHERE query.

In BigQuery source node configuration options, the options are only these:

Also in the generated script, it uses create_dynamic_frame.from_options which does not accommodate custom query (per documentation).

...

ANSWER

Answered 2022-Mar-24 at 06:45

Quoting this AWS sample project, we can use filter in Connection Options:

filter – Passes the condition to select the rows to convert. If the table is partitioned, the selection is pushed down and only the rows in the specified partition are transferred to AWS Glue. In all other cases, all data is scanned and the filter is applied in AWS Glue Spark processing, but it still helps limit the amount of memory used in total.

Example if used in script:

Source https://stackoverflow.com/questions/71576096

QUESTION

AWS Glue Exclude Patterns

Asked 2022-Mar-02 at 16:45

I am working on a project which is using Glue 3.0 & PySpark to process large amounts of data between S3 buckets. This is being achieved using GlueContext.create_dynamic_frame_from_options to read the data from an S3 bucket to a DynamicFrame using the recurse connection option set to True as the data is nested heavily. I only wish to read files which end in meta.json therefore I have set the exclusions filter to exclude any files which end in data.csv "exclusions": ['**.{txt, csv}', '**/*.data.csv', '**.data.csv', '*.data.csv'] however I am consistently getting the following error:

...

ANSWER

Answered 2022-Mar-02 at 16:45

Exclusions has to be a string

Source https://stackoverflow.com/questions/71254804

QUESTION

Is there any method to concatenate/unite DynamicFrame objects in AWS GLue?

Asked 2021-Nov-11 at 20:29

I've tried to concatenate a set of DynamicFrame objects in order to create a composite bigger one within Glue Job. According to Glue docs there are only a few methods available for DynamicFrameCollection class and none of them allows this kind of operation. Have anyone tried to perform something similar?

A collection is an indexed by keys structure and looks like the following within gluecontext, where each datasource object is a parsed table in parquet format.

...

ANSWER

Answered 2021-Nov-10 at 12:57

You can convert them to a data frame by calling the .toDF() method. Then you can use this method to union data frames regardless of their schema:

Source https://stackoverflow.com/questions/69913328

QUESTION

dy.drop_fields() vs DropFields.apply()

Asked 2021-Jun-30 at 16:08

When using Glue I came across two ways to remove columns from a dynamic frame.

A method of the DynamicFrame: drop_fields()
and the class DropFields.apply()

they are used like this:

...

ANSWER

Answered 2021-Jun-30 at 16:08

I can only answer parts of that question:

Is there any difference between them?

No, the Class-Style transforms actually call the underlying DynamicFrame methods:

From the library:

Source https://stackoverflow.com/questions/68192753

QUESTION

What is catalog_connection param in aws glue?

Asked 2021-Feb-25 at 09:17

I wish to regularly run a etl job at every 4 hours which will union (combine) data from s3 bucket (parquet format) and data from redshift. Find out the unique and then write it again to redshift, replacing old redshift data. For writing dataframes to redshift, this

...

ANSWER

Answered 2021-Feb-25 at 09:17

The catalog_connection refers to the glue connection defined inside glue catalog.

Let's say if there is a connection named redshift_connection in glue connection, it will be used like:

Source https://stackoverflow.com/questions/66353553

QUESTION

What options can be passed to AWS Glue DynamicFrame.toDF()?

Asked 2020-Oct-08 at 09:50

The documentation on toDF() method specifies that we can pass an options parameter to this method. But it does not specify what those options can be (https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api-crawler-pyspark-extensions-dynamic-frame.html). Does anyone know if there is further documentation on this? I am specifically interested in passing in a schema when creating a DataFrame from DynamicFrame.

...

ANSWER

Answered 2020-Oct-08 at 09:50

Unfortunately there's not much documentation available, yet R&D and analysis of source code for dynamicframe suggests the following:

options available in toDF have more to do with ResolveOption class then toDF itself, as ResolveOption class adds meaning to the parameters (please read the code).
ResolveOption class takes in ChoiceType as a parameter.
The options examples available in documentation are similar to the specs available in ResolveChoice that also mention ChoiceType.
Options are further converted to sequence and referenced to toDF function from _jdf here.

My understanding after seeing the specs, toDF implementation of dynamicFrame and toDF from spark is that we can't pass schema when creating a DataFrame from DynamicFrame, but only minor column manipulations are possible.

Saying this, a possible approach is to obtain a dataframe from dynamic frame and then manipulate it to change its schema.

Source https://stackoverflow.com/questions/64215323

QUESTION

Calling getResolvedOptions() in Local Environment Generates KeyError

Asked 2020-Jul-15 at 22:05

I have a local AWS Glue environment with the AWS Glue libraries, Spark, PySpark, and everything installed.

I'm running the following code (literally copy-past in the REPL):

...

ANSWER

Answered 2020-Jul-09 at 22:52

From AWS documentation, --JOB_NAME is internal to AWS Glue and you should not set it.

If you're running a local Glue setup and wish to run the job locally, you can pass the --JOB_NAME parameter when the job is submitted to gluesparksubmit. E.g.

Source https://stackoverflow.com/questions/62641809

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

Vulnerabilities

No vulnerabilities reported

Install crawler-py

You can download it from GitHub.
You can use crawler-py like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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