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Pseudo API for Google Trends

Project description


### 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


```pip install pytrends```

* 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)**

* 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)**

* 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: ``````
- ```"%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: ```""```
- ```"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 61-m"`` 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)**

* path
- Output path
* trend_name
- Human readable name for fil

### Get Google Term Suggestions

* 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

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