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| author | CoprDistGit <infra@openeuler.org> | 2023-05-05 10:55:23 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-05 10:55:23 +0000 |
| commit | 92cd7c549faf1d8e1458bffde0c1739fb6c26f48 (patch) | |
| tree | 570f2180467eaf149b0d986e42d0fd974d53f53c | |
| parent | fc67cadff20cbd111a6ace8369c7ebaef5b5184a (diff) | |
automatic import of python-apiesopeneuler20.03
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-apies.spec | 831 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 833 insertions, 0 deletions
@@ -0,0 +1 @@ +/apies-1.9.1.tar.gz diff --git a/python-apies.spec b/python-apies.spec new file mode 100644 index 0000000..a8c208b --- /dev/null +++ b/python-apies.spec @@ -0,0 +1,831 @@ +%global _empty_manifest_terminate_build 0 +Name: python-apies +Version: 1.9.1 +Release: 1 +Summary: A flask blueprint providing an API for accessing and searching an ElasticSearch index created from source datapackages +License: MIT +URL: https://github.com/OpenBudget/apies +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ad/4e/7be8932f65b9e1fe46560d059c394406f4538eae685e5934017532863b52/apies-1.9.1.tar.gz +BuildArch: noarch + +Requires: python3-Flask +Requires: python3-Flask-Cors +Requires: python3-requests +Requires: python3-elasticsearch +Requires: python3-datapackage +Requires: python3-flask-jsonpify +Requires: python3-demjson3 +Requires: python3-xlwt +Requires: python3-xlsxwriter +Requires: python3-pylama +Requires: python3-tox +Requires: python3-dataflows-elasticsearch + +%description +# 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/<doc-id>` + +Fetches a document from the index. + +Query parameters that can be used: +- **type**: The type of the document to fetch (if not `docs`) + +### `/search/count` + +### `/search/<doc-types>` + +Performs a search on the index. + +`doc-types` is a comma separated list of document types to search. + +Query parameters that can be used: +- **q**: The full text search textual query + +- **filter**: A JSON object with filters to apply to the search. These are applied to the query but don't affect the scoring of the results. + Filters should be an array of objects, each object depicting a single filter. All filters are combined with an `OR` operator. For example: + ``` + [ + { + "first-name": "John", + "last-name": "Watson" + }, + { + "first-name": "Sherlock", + "last-name": "Holmes" + } + ] + ``` + Each object contains a set of rules that all must match. Each rule is a key-value pair, where the key is the field name and the value is the value to match. The value can be a string or an array of strings. If the value is an array, the rule will match if any of the values in the array match. For example: + ``` + { + "first-name": ["Emily", "Charlotte"], + "last-name": "Bronte" + } + ``` + Field names can be appended with two underscores and an operator to convey other relations other than equality. For example: + ``` + { + "first-name": "Emily", + "last-name": "Bronte", + "age__gt": 30, + } + ``` + Allowed operators are: + ('gt', 'gte', 'lt', 'lte', 'eq', 'not', 'like', 'bounded', 'all'): + - `gt`: greater than + - `gte`: greater than or equal to + - `lt`: less than + - `lte`: less than or equal to + - `eq`: equal to + - `not`: not equal to + - `like`: like (textual match) + - `bounded`: bounded (geospatial match to a bounding box) + - `all`: all (for arrays - all values in the array must exist in the target) + + If multiple operators are needed for the same field, the field can also be suffixed by a hashtag and a number. For example: + ``` + { + "city": "San Francisco", + "price__lt": 300000, + "bedrooms__gt": 4, + "amenities": "garage", + "amenities#1": ["pool", "back yard"], + } + ``` + The above filter will match all documents where the `city` is "San Francisco", `price` is less than 300000, more than 4 `bedrooms`, the `amenities` field contains 'garage' and at least one of "pool" and "back yard". + +- **lookup**: A JSON object with lookup filters to apply to the search. These filter the results, but also affect the scoring of the results. +- **context**: A textual context to search in (i.e. run the search in a subset of results matching the full-text-search query provided in this field) + +- **extra**: Extra information that's passed to library extensions + +- **size**: Number of results to fetch (default: 10) +- **offset**: Offset of first result to fetch (default: 0) +- **order**: Order results by (default: _score) + +- **highlight**: Commas separated list of fields to highlight +- **snippets**: Commas separated list of fields to fetch snippets from + +- **match_type**: ElasticSearch match type (default: most_fields) +- **match_operator**: ElasticSearch match operator (default: and) +- **minscore**: Minimum score for a result to be returned (default: 0.0) + +### `download/<doctypes>` + +Downloads search results in either csv, xls or xlsx format. + +Query parameters that can be used: +- **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", + ... + } + ``` + + + +%package -n python3-apies +Summary: A flask blueprint providing an API for accessing and searching an ElasticSearch index created from source datapackages +Provides: python-apies +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-apies +# 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/<doc-id>` + +Fetches a document from the index. + +Query parameters that can be used: +- **type**: The type of the document to fetch (if not `docs`) + +### `/search/count` + +### `/search/<doc-types>` + +Performs a search on the index. + +`doc-types` is a comma separated list of document types to search. + +Query parameters that can be used: +- **q**: The full text search textual query + +- **filter**: A JSON object with filters to apply to the search. These are applied to the query but don't affect the scoring of the results. + Filters should be an array of objects, each object depicting a single filter. All filters are combined with an `OR` operator. For example: + ``` + [ + { + "first-name": "John", + "last-name": "Watson" + }, + { + "first-name": "Sherlock", + "last-name": "Holmes" + } + ] + ``` + Each object contains a set of rules that all must match. Each rule is a key-value pair, where the key is the field name and the value is the value to match. The value can be a string or an array of strings. If the value is an array, the rule will match if any of the values in the array match. For example: + ``` + { + "first-name": ["Emily", "Charlotte"], + "last-name": "Bronte" + } + ``` + Field names can be appended with two underscores and an operator to convey other relations other than equality. For example: + ``` + { + "first-name": "Emily", + "last-name": "Bronte", + "age__gt": 30, + } + ``` + Allowed operators are: + ('gt', 'gte', 'lt', 'lte', 'eq', 'not', 'like', 'bounded', 'all'): + - `gt`: greater than + - `gte`: greater than or equal to + - `lt`: less than + - `lte`: less than or equal to + - `eq`: equal to + - `not`: not equal to + - `like`: like (textual match) + - `bounded`: bounded (geospatial match to a bounding box) + - `all`: all (for arrays - all values in the array must exist in the target) + + If multiple operators are needed for the same field, the field can also be suffixed by a hashtag and a number. For example: + ``` + { + "city": "San Francisco", + "price__lt": 300000, + "bedrooms__gt": 4, + "amenities": "garage", + "amenities#1": ["pool", "back yard"], + } + ``` + The above filter will match all documents where the `city` is "San Francisco", `price` is less than 300000, more than 4 `bedrooms`, the `amenities` field contains 'garage' and at least one of "pool" and "back yard". + +- **lookup**: A JSON object with lookup filters to apply to the search. These filter the results, but also affect the scoring of the results. +- **context**: A textual context to search in (i.e. run the search in a subset of results matching the full-text-search query provided in this field) + +- **extra**: Extra information that's passed to library extensions + +- **size**: Number of results to fetch (default: 10) +- **offset**: Offset of first result to fetch (default: 0) +- **order**: Order results by (default: _score) + +- **highlight**: Commas separated list of fields to highlight +- **snippets**: Commas separated list of fields to fetch snippets from + +- **match_type**: ElasticSearch match type (default: most_fields) +- **match_operator**: ElasticSearch match operator (default: and) +- **minscore**: Minimum score for a result to be returned (default: 0.0) + +### `download/<doctypes>` + +Downloads search results in either csv, xls or xlsx format. + +Query parameters that can be used: +- **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", + ... + } + ``` + + + +%package help +Summary: Development documents and examples for apies +Provides: python3-apies-doc +%description help +# 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/<doc-id>` + +Fetches a document from the index. + +Query parameters that can be used: +- **type**: The type of the document to fetch (if not `docs`) + +### `/search/count` + +### `/search/<doc-types>` + +Performs a search on the index. + +`doc-types` is a comma separated list of document types to search. + +Query parameters that can be used: +- **q**: The full text search textual query + +- **filter**: A JSON object with filters to apply to the search. These are applied to the query but don't affect the scoring of the results. + Filters should be an array of objects, each object depicting a single filter. All filters are combined with an `OR` operator. For example: + ``` + [ + { + "first-name": "John", + "last-name": "Watson" + }, + { + "first-name": "Sherlock", + "last-name": "Holmes" + } + ] + ``` + Each object contains a set of rules that all must match. Each rule is a key-value pair, where the key is the field name and the value is the value to match. The value can be a string or an array of strings. If the value is an array, the rule will match if any of the values in the array match. For example: + ``` + { + "first-name": ["Emily", "Charlotte"], + "last-name": "Bronte" + } + ``` + Field names can be appended with two underscores and an operator to convey other relations other than equality. For example: + ``` + { + "first-name": "Emily", + "last-name": "Bronte", + "age__gt": 30, + } + ``` + Allowed operators are: + ('gt', 'gte', 'lt', 'lte', 'eq', 'not', 'like', 'bounded', 'all'): + - `gt`: greater than + - `gte`: greater than or equal to + - `lt`: less than + - `lte`: less than or equal to + - `eq`: equal to + - `not`: not equal to + - `like`: like (textual match) + - `bounded`: bounded (geospatial match to a bounding box) + - `all`: all (for arrays - all values in the array must exist in the target) + + If multiple operators are needed for the same field, the field can also be suffixed by a hashtag and a number. For example: + ``` + { + "city": "San Francisco", + "price__lt": 300000, + "bedrooms__gt": 4, + "amenities": "garage", + "amenities#1": ["pool", "back yard"], + } + ``` + The above filter will match all documents where the `city` is "San Francisco", `price` is less than 300000, more than 4 `bedrooms`, the `amenities` field contains 'garage' and at least one of "pool" and "back yard". + +- **lookup**: A JSON object with lookup filters to apply to the search. These filter the results, but also affect the scoring of the results. +- **context**: A textual context to search in (i.e. run the search in a subset of results matching the full-text-search query provided in this field) + +- **extra**: Extra information that's passed to library extensions + +- **size**: Number of results to fetch (default: 10) +- **offset**: Offset of first result to fetch (default: 0) +- **order**: Order results by (default: _score) + +- **highlight**: Commas separated list of fields to highlight +- **snippets**: Commas separated list of fields to fetch snippets from + +- **match_type**: ElasticSearch match type (default: most_fields) +- **match_operator**: ElasticSearch match operator (default: and) +- **minscore**: Minimum score for a result to be returned (default: 0.0) + +### `download/<doctypes>` + +Downloads search results in either csv, xls or xlsx format. + +Query parameters that can be used: +- **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", + ... + } + ``` + + + +%prep +%autosetup -n apies-1.9.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-apies -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.9.1-1 +- Package Spec generated @@ -0,0 +1 @@ +62c9f337cd44a3481089328f6f292773 apies-1.9.1.tar.gz |