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contentaiextractor-1.1.0
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
makes it easier to implement a ContentAI extractor
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | contentaiextractor-1.1.0 |
| نام | contentaiextractor |
| نسخه کتابخانه | 1.1.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | John Ritsema |
| ایمیل نویسنده | john.ritsema@turner.com |
| آدرس صفحه اصلی | http://github.com/turnercode/contentai-extractor-runtime-python |
| آدرس اینترنتی | https://pypi.org/project/contentaiextractor/ |
| مجوز | apache-2 |
# contentai-extractor-runtime-python
This is a python package used for implementing a custom extractor that runs on the ContentAI platform.
https://pypi.org/project/contentaiextractor/
1. [Usage](#Usage)
1. [API Documentation](#API-Documentation)
1. [Dependencies](#Dependencies)
1. [Develop](#Develop)
1. [Changes](#Changes)
# Usage
```sh
pip install contentaiextractor
```
```python
import contentaiextractor as contentai
# download content locally
content_path = contentai.download_content()
# access metadata that was supplied when running a job
# contentai run s3://bucket/video.mp4 -d '{ "input": "value" }'
inputData = contentai.metadata()["input"]
# get output from another extractor
csv = contentai.get("extractor", "data.csv")
json = contentai.get_json("extractor", "data.json")
# extract some data
outputData = []
outputData.append({"frameNumber": 1})
# output data from this extractor
contentai.set("output", outputData)
```
# API Documentation
<a name="contentaiextractor.ContentAIError"></a>
## ContentAIError Objects
```python
class ContentAIError(Exception)
```
represents a contentai error
## Fields
- `extractor_name` - name of the extractor being run
- `job_id` - current job id
- `content_url` - URL of the content the extractor is run against
- `content_path` - local path where the extractor can access the content
- `result_path` - local path where the extractor should write the results
- `running_in_contentai` - boolean set to `True`; useful for testing code locally
- `metadata_json` - raw string (or `None` if not set) for active extractor run (also, see parsed [metadata()](#metadata))
## Functions
<a name="contentaiextractor.download_content"></a>
#### download\_content
```python
download_content()
```
download content to work with locally
returns local path where content is written
<a name="contentaiextractor.metadata"></a>
#### metadata
```python
metadata()
```
returns a dict containing input metadata
example:
access metadata that was supplied when running a job
```sh
contentai run s3://bucket/video.mp4 -d '{ "input: "value" }'
```
```python
input = contentai.metadata()["input"]
```
<a name="contentaiextractor.extractors"></a>
#### extractors
```python
extractors()
```
get list of all extractors executed against this content url
returns a list of strings
```json
[
"extractor1",
"extractor2"
],
```
example:
```python
# get all data from all extractors
for extractor in contentai.extractors():
for key in contentai.keys(extractor):
data = contentai.get(extractor, key)
```
<a name="contentaiextractor.keys"></a>
#### keys
```python
keys(extractor_name)
```
get a list of keys for specified extractor
returns a dict containing a list of keys
```json
[
"data.json",
"data.csv",
"data.txt,"
]
```
example:
```python
keys = contentai.keys("azure_videoindexer")
for key in keys:
data = contentai.get("azure_videoindexer", key)
```
<a name="contentaiextractor.get"></a>
#### get
```python
get(extractor_name, key)
```
get the contents of a particular key
example:
```python
# get another extractor's output
data = contentai.get("some_extractor", "output.csv")
```
<a name="contentaiextractor.get_json"></a>
#### get\_json
```python
get_json(extractor_name, key)
```
get the json contents of a particular key
example:
```python
# get another extractor's output
data = contentai.get_json("some_extractor", "data.json")
```
<a name="contentaiextractor.get_bytes"></a>
#### get\_bytes
```python
get_bytes(extractor_name, key)
```
get the contents of a particular key in raw bytes
example:
```python
# get another extractor's output
data = contentai.get_bytes("some_extractor", "output.bin")
```
<a name="contentaiextractor.set"></a>
#### set
```python
set(key, value)
```
set results data for this extractor
can be called multiple times with different keys
value is a string
example:
```python
contentai.set("output", "hello world")
```
<a name="contentaiextractor.set_json"></a>
#### set\_json
```python
set_json(key, value)
```
set results data for this extractor
can be called multiple times with different keys
value can be anything
example:
```python
data = {}
data["foo"] = bar
contentai.set_json("output", data)
```
<a name="contentaiextractor.set_bytes"></a>
#### set\_bytes
```python
set_bytes(key, value)
```
set results data for this extractor
can be called multiple times with different keys
value is bytes
example:
```python
some_file = open("some-file", "rb")
contentai.set_bytes("output", some_file.read())
```
<a name="contentaiextractor.save_results"></a>
#### save\_results
```python
save_results()
```
save results immediately, instead of waiting until process exits
<a name="contentaiextractor.parse_content_url"></a>
#### parse\_content\_url
```python
parse_content_url()
```
extract details from content url
returns
- `source_bucket_name` - the s3 bucket name derived from content_url
- `source_bucket_key` - the s3 bucket key derived from content_url
- `source_bucket_region` - the s3 bucket region derived from content_url
the following `content url` formats are supported:
- Simple (CLI) Format - `s3://{bucket}/{key}`
- Virtual Hosted Format - `https://{bucket}.s3.amazonaws.com/{key}`
- Virtual Hosted Format with Region - `https://{bucket}.s3.{region}.amazonaws.com/{key}`
# Dependencies
```
pip install -r requirements.txt
```
# Develop
```
Choose a make command to run
build build package
deploy upload package to pypi
docs generates api docs in markdown
```
# Release
To publish a new release to pypi, increment the version number in `setup.py`, tag the commit and push it.
### Changes
- 1.1.0
- add `extractors()`
- 1.0.4
- updated changelog
- 1.0.3
- fixes issue where `EXTRACTOR_METADATA` envvar was indavertently required
- 1.0.2
- add safety to setting retrieval on local runs
- documentation updates
- 1.0.1
- api docs for publish to pypi
- 1.0.0
- initial release
نحوه نصب
نصب پکیج whl contentaiextractor-1.1.0:
pip install contentaiextractor-1.1.0.whl
نصب پکیج tar.gz contentaiextractor-1.1.0:
pip install contentaiextractor-1.1.0.tar.gz