Metadata-Version: 1.1
Name: pytrends
Version: 1.1.2
Summary: Pseudo API for Google Trends
Home-page: https://github.com/dreyco676/pytrends
Author: ['John Hogue', 'Burton DeWilde']
Author-email: dreyco676@gmail.com
License: MIT
Description: pytrends
        =========
        
        ### About
        
        **Pseudo API for Google Trends**
        
        * Allows simple interface for automating downloads of csv reports from Google Trends.
        * Main feature is to help trick google into thinking the script is actually a browser.
        
        
        * Only good until Google changes their backend again :-P
        
        **Installation**
        
        ```pip install pytrends```
        
        **Requirements**
        * Written for both Python 2.7+ and Python 3.3+
        * Requires a google account to use.
        * Requires fake-useragent python library (installed automatically with pip)
        
        ## Connect to Google
        **pyGTrends(google_username, google_password)**
        
        **Parameters**
        * google_username
          - a valid gmail address
        * google_password
          - password for the gmail account
        
        ### Request a Report
        **request_report(keywords, hl='en-US', cat=None, geo=None, date=None)**
        
        **Parameters**
        * Keywords
          - the words to get data for
          - Example ```"Pizza"```
          - Up to five terms with a comma and space: ```"Pizza, Italian, Spaghetti, Breadsticks, Sausage"```
        * Advanced Keywords
          - When using Google Trends dashboard Google may provide suggested narrowed search terms. 
          - For example ```"iron"``` will have a drop down of ```"Iron Chemical Element, Iron Cross, Iron Man, etc"```. 
          - Find the encoded topic by using the get_suggestions() function and choose the most relevant one for you. 
          - For example: ```https://www.google.com/trends/explore#q=%2Fm%2F025rw19&cmpt=q```
          - ```"%2Fm%2F025rw19"``` is the topic "Iron Chemical Element" to use this with pytrends
        * hl
          - Language to return result headers in
          - Two letter language abbreviation
          - For example English is ```"en"```
          - Defaults to english
        * cat
          - Category to narrow results
          - Find available cateogies by inspecting the url when manually using Google Trends. The category starts after ```cat=``` and ends before the next ```&```
          - For example: ```"https://www.google.com/trends/explore#q=pizza&cat=0-71"```
          - ```"0-71"``` is the category
          - Defaults to no category
        * geo
          - Two letter country abbreviation
          - For example United States is ```"US"```
          - Defaults to World
        * tz
          - Timezone using Etc/GMT
          - For example US CST is ```"Etc/GMT+5"```
        * date
          - Date to start from
          - Defaults to all available data, 2004 - present.
          - Custom Timeframe Pattern:
            - By Month: ```"MM/YYYY #m"``` where # is the number of months from that date to pull data for
              - For example: ``"10/2009 61m"`` would get data from October 2009 to October 2014
              - Less than 4 months will return Daily level data
              - More than 36 months will return monthly level data
              - 4-36 months will return weekly level data
          - Current Time Minus Time Pattern:
            - By Month: ```"today-#m"``` where # is the number of months from that date to pull data for
              - For example: ``"today-61m"`` would get data from today to 61months ago
              - 1-3 months will return daily intervals of data
              - 4-36 months will return weekly intervals of data
              - 36+ months will return monthly intervals of data
            - Daily: ```"today #-d"``` where # is the number of days from that date to pull data for
              - For example: ``"today 7-d"`` would get data from the last week
              - 1 day will return 8min intervals of data
              - 2-8 days will return Hourly intervals of data
              - 8-90 days will return Daily level data
            - Hourly: ```"now #-H"``` where # is the number of hours from that date to pull data for
              - For example: ``"now 1-H"`` would get data from the last hour
              - 1-3 hours will return 1min intervals of data
              - 4-26 hours will return 8min intervals of data
              - 27-34 hours will return 16min intervals of data
        
        ### Save a Report to file
        **save_csv(path, trend_name)**
        
        **Parameters**
        * path
          - Output path
        * trend_name
          - Human readable name for fil
        
        ### Get Google Term Suggestions
        **get_suggestions(keyword)**
        
        **Parameters**
        * keyword
          - keyword to get suggestions for
          
        **Returns JSON**
        ```{"default": {"topics": [{"mid": "/m/0663v","title": "Pizza","type": "Dish"}]}}```
        * Use the ```mid``` value for the keyword in future searches for a more refined trend set
        ### Credits
        
        * Connecting to google code heavily based off Sal Uryasev's pyGTrends
        
        * With some ideas pulled from Matt Reid's Google Trends API
          - https://bitbucket.org/mattreid9956/google-trend-api/overview
        
Keywords: google trends api search
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: License :: OSI Approved :: MIT License
