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apies-1.7.7
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مشاهده بیشترتوضیحات
A flask blueprint providing an API for accessing and searching an ElasticSearch index created from source datapackages
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | apies-1.7.7 |
| نام | apies |
| نسخه کتابخانه | 1.7.7 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Adam Kariv |
| ایمیل نویسنده | adam.kariv@gmail.com |
| آدرس صفحه اصلی | https://github.com/OpenBudget/apies |
| آدرس اینترنتی | https://pypi.org/project/apies/ |
| مجوز | MIT |
# apies
[](https://travis-ci.org/datahq/apies)
[](https://coveralls.io/r/OpenBudget/apies?branch=master)
apies is a flask blueprint providing an API for accessing and searching an ElasticSearch index created from source datapackages.
## endpoints
### `/get`
### `/search/count`
### `/search/<doctypes>
### `download/<doctypes>`
Downloads search results in either csv, xls or xlsx format.
Query parameters that can be send:
- **types_formatted**: The type of the documents to search
- **search_term**: The Elastic search query
- **size**: Number of hits to return
- **offset**: Whether or not term offsets should be returned
- **filters**: What offset to use for the pagination
- **dont_highlight**:
- **from_date**: If there should be a date range applied to the search, and from what date
- **to_date**: If there should be a date range applied to the search, and until what date
- **order**:
- **file_format**: The format of the file to be returned, either 'csv', 'xls' or 'xlsx'.
If not passed the file format will be xlsx
- **file_name**: The name of the file to be returned, by default the name will be 'search_results'
- **column_mapping**: If the columns should get a different name then in the
original data, a column map can be send, for example:
```
{
"עיר": "address.city",
"תקציב": "details.budget"
}
```
For example, get a csv file with column mapping:
```
http://localhost:5000/api/download/jobs?q=engineering&size=2&file_format=csv&file_name=my_results&column_mapping={%22mispar%22:%22Job%20ID%22}
```
Or get an xslx file without column mapping:
```
http://localhost:5000/api/download/jobs?q=engineering&size=2&file_format=xlsx&file_name=my_results
```
## configuration
Flask configuration for this blueprint:
```python
from apies import apies_blueprint
import elasticsearch
app.register_blueprint(
apies_blueprint(['path/to/datapackage.json', Package(), ...],
elasticsearch.Elasticsearch(...),
{'doc-type-1': 'index-for-doc-type-1', ...},
'index-for-documents',
dont_highlight=['fields', 'not.to', 'highlight'],
text_field_rules=lambda schema_field: [], # list of tuples: ('exact'/'inexact'/'natural', <field-name>)
multi_match_type='most_fields',
multi_match_operator='and'),
url_prefix='/search/'
)
```
## local development
You can start a local development server by following these steps:
1. Install Dependencies:
a. Install Docker locally
b. Install Python dependencies:
```bash
$ pip install dataflows dataflows-elasticsearch
$ pip install -e .
```
2. Go to the `sample/` directory
3. Start ElasticSearch locally:
```bash
$ ./start_elasticsearch.sh
```
This script will wait and poll the server until it's up and running.
You can test it yourself by running:
```bash
$ curl -s http://localhost:9200
{
"name" : "99cd2db44924",
"cluster_name" : "docker-cluster",
"cluster_uuid" : "nF9fuwRyRYSzyQrcH9RCnA",
"version" : {
"number" : "7.4.2",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "2f90bbf7b93631e52bafb59b3b049cb44ec25e96",
"build_date" : "2019-10-28T20:40:44.881551Z",
"build_snapshot" : false,
"lucene_version" : "8.2.0",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
```
4. Load data into the database
```bash
$ DATAFLOWS_ELASTICSEARCH=localhost:9200 python load_fixtures.py
```
You can test that data was loaded:
```bash
$ curl -s http://localhost:9200/jobs-job/_count?pretty
{
"count" : 1757,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
}
}
```
5. Start the sample server
```bash
$ python server.py
* Serving Flask app "server" (lazy loading)
* Environment: production
WARNING: Do not use the development server in a production environment.
Use a production WSGI server instead.
* Debug mode: off
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
```
6. Now you can hit the server's endpoints, for example:
```bash
$ curl -s 'localhost:5000/api/search/jobs?q=engineering&size=2' | jq
127.0.0.1 - - [26/Jun/2019 10:45:31] "GET /api/search/jobs?q=engineering&size=2 HTTP/1.1" 200 -
{
"search_counts": {
"_current": {
"total_overall": 617
}
},
"search_results": [
{
"score": 18.812,
"source": {
"# Of Positions": "5",
"Additional Information": "TO BE APPOINTED TO ANY CIVIL <em>ENGINEERING</em> POSITION IN BRIDGES, CANDIDATES MUST POSSESS ONE YEAR OF CIVIL <em>ENGINEERING</em> EXPERIENCE IN BRIDGE DESIGN, BRIDGE CONSTRUCTION, BRIDGE MAINTENANCE OR BRIDGE INSPECTION.",
"Agency": "DEPARTMENT OF TRANSPORTATION",
"Business Title": "Civil Engineer 2",
"Civil Service Title": "CIVIL ENGINEER",
"Division/Work Unit": "<em>Engineering</em> Review & Support",
...
}
```
نیازمندی
| مقدار | نام |
|---|---|
| <2,>=1 | Flask |
| <4.0.0,>=3.0.7 | Flask-Cors |
| <3.0.0,>=2.20.1 | requests |
| <8.0.0,>=7.0.0 | elasticsearch |
| - | datapackage |
| - | flask-jsonpify |
| - | demjson3 |
| - | xlwt |
| - | xlsxwriter |
| - | pylama |
| - | tox |
| >=0.1.0 | dataflows-elasticsearch |
نحوه نصب
نصب پکیج whl apies-1.7.7:
pip install apies-1.7.7.whl
نصب پکیج tar.gz apies-1.7.7:
pip install apies-1.7.7.tar.gz