Merge pull request #74 from LuuMing/dev

analy 功能的标准模块实现

grank/__init__.py

@@ -0,0 +1 @@
+from grank import analy

grank/analy/__init__.py

@@ -0,0 +1 @@
+from .core import *

grank/analy/core.py

@@ -0,0 +1,16 @@
+__all__ = ['get_analy']
+
+def get_analy(token=None,start=None,stop=None,owner=None,repo=None):
+    from ..script.crawler import fetch_repo_data
+    from ..libs.helpers import get_config_instance
+    from ..script.activity import analyse_repo
+    from ..script.social import analyse_repo as analyse_social
+    if owner is None:
+        raise ValueError('owner invalid!')
+    if repo is None:
+        raise ValueError('repo invalid!')
+    config = get_config_instance(token=token,start=start,stop=stop)
+    data = fetch_repo_data(owner,repo,config)
+    activity = analyse_repo(owner, repo, data, config, ret_score = True)
+    social = analyse_social(owner, repo, data, config, ret_score = True)
+    return {'activity': activity, 'social':social}

grank/script/activity.py

@@ -4,8 +4,7 @@
 import click
 import math
 
-
-def analyse_repo(owner, repository, data, config):
+def analyse_repo(owner, repository, data, config, ret_score = False):
     click.echo("开始活跃度分析：%s/%s" % (owner, repository))
     """查询 Repo 数据"""
     pullRequestArray = data["pullRequestArray"]
@@ -75,6 +74,9 @@ def analyse_repo(owner, repository, data, config):
 
     # 求活跃分数平均值
     target_score = new_df["score"].sum() / len(new_df)
+
+    if ret_score is True:
+        return target_score
 
     # 获取平均分实例，用于后续排序
     instance = helpers.get_activity_average_instance()

grank/script/social.py

@@ -32,7 +32,7 @@ def analyse_email(data,config):
 
     pass
 
-def analyse_repo(owner, repository, data, config):
+def analyse_repo(owner, repository, data, config, ret_score = False):
     click.echo("开始社区化分析：%s/%s" % (owner, repository))
     pullRequestArray = data["pullRequestArray"]
     commitArray = data["commitArray"]
@@ -84,6 +84,9 @@ def analyse_repo(owner, repository, data, config):
 
     target_social_score = social_df["score"].mean()
 
+    if ret_score is True:
+        return target_social_score
+
     instance = helpers.get_social_average_instance()
 
     helpers.export_pickle(social_df, 'social', owner, repository)