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Python REPL/API for accessing dimensions.ai.

Project description

Dimcli

asciicast

In a nutshell

Dimcli is a Python library for accessing the Dimensions Analytics API. It makes it easier to authenticate, query the API endpoint and process the results, normally returned as JSON.

Dimcli provides an interactive environment which aims at simplifying the process of learning the grammar of the Dimensions Search Language (DSL). Calling dimcli from the terminal opens a CLI featuring autocomplete (based on the DSL syntax and vocabulary), persistent history across sessions, pretty-printing and preview of JSON results, export to HTML and CSV, and more.

Current version: see pypi homepage. Source code hosted on github.

Installation

$ pip install dimcli -U

Then you can check if the installation worked with

$ dimcli --help

Anaconda errors: a couple of libraries needed by DimCli might need to be updated manually: pip install prompt-toolkit -U and pip install ipython -U (see also this ticket)

Authentication

After installation it's strongly advised to create a configuration file with your Dimensions account credentials. This can be done only once, and it'll save you from having to authenticate each time you use DimCli.

The easiest way to set up the authentication file is to use the command line helper:

$ dimcli --init

The helper will guide you through the process of creating this file, which will be safely stored in your computer home folder. That's it - you're ready to hit the API! See below for more info on how to do that.

The Credentials File

This section provides more details about where DimCli expects credentials data to be found, in case you want to set this up manually.

The credentials file must be called dsl.ini and located in your user directory in the .dimensions folder. If you want to set this up manually, this is what you'd do on unix systems:

$ mkdir ~/.dimensions
$ touch ~/.dimensions/dsl.ini

Then open dsl.ini with a text editor. Its contents should look like this:

[instance.live]
url=https://app.dimensions.ai
login=user@mail.com
password=yourpasswordhere

In most situations you can simply copy/paste the text above and change the login and password as needed.

Note: you must always have an entry in the configuration called [instance.live]

Advanced: Multiple API Endpoints

If you have access to multiple Dimensions API endpoints (or instances), you can just add more entries to the credentials file.

You can add details for more than one instance but make sure you give them unique names. So for example you can add another entry like this:

[instance.private]
url=https://private-instance.dimensions.ai
login=user@mail.com
password=yourpasswordhere

Then when running the CLI you can select which instance to use just by passing its name as argument eg

$ dimcli private

Overriding credentials at runtime e.g. with Jupyter Notebooks

If you are using DimCli within a jupyter notebook and you do not want (or can) set up credentials at the user level, you can simply put a dsl.ini file in the current working directory (= where the notebook is located).

The file should look like this:

[instance.live]
url=https://app.dimensions.ai
login=user@mail.com
password=yourpasswordhere

Note: the same-directory credentials will take precedence over any system-level credentials previously defined.

Using DimCli as a CLI

DimCli includes a handy CLI which lets you query the Dimensions API interactively. The CLI has several features but, most importantly, it allows to use the TAB key to autocomplete your queries (based on the latest API syntax and fields), which makes it an ideal tool for both newbies and expert users.

Run the command line application by typing

$ dimcli

That'll launch the DimCli console, where you can hit help in case you need more support :-)

screenshot1

Using Dimcli as a Python library

Dimcli can be used as a wrapper around the Dimensions API within a Python program. It makes it easier to authenticate, query the Dimensions endpoint and handle the results, normally returned as JSON.

>>> import dimcli

# if you have already set up the credentials file (see above), no need to pass log in details
>>> dsl = dimcli.Dsl()

# otherwise you can authenticate by passing your login details as arguments
>>> dsl = dimcli.Dsl(user="mary.poppins", password="chimneysweeper")

# you can specify endpoint, which by default is set to "https://app.dimensions.ai"
>>> dsl = dimcli.Dsl(user="mary.poppins", password="chimneysweeper", ednpoint="https://nannies-research.dimensions.ai")

Once logged in, you can try some queries:

# queries always return a Result object (subclassing IPython.display.JSON)
>>> dsl.query("search grants for \"malaria\" return publications")
<dimcli.dimensions.Result object>

# use the .data method to get the JSON
>>> dsl.query("search grants for \"malaria\" return publications").data
{'errors': {'query': {'header': 'Semantic Error',
   'details': ["Semantic errors found:\n\tFacet 'publications' is not present in source 'grants'. Available facets are: FOR,FOR_first,HRCS_HC,HRCS_RAC,RCDC,active_year,funder_countries,funders,funding_org_acronym,funding_org_city,funding_org_name,language,research_org_cities,research_org_countries,research_org_name,research_org_state_codes,research_orgs,researchers,start_year,title_language"],
   'query': 'search grants for "malaria" return publications'}}}

# now a good query
>>> res = dsl.query("search grants for \"malaria\" return researchers")
>>> print(res.data)
{'researchers': [{'id': 'ur.01332073522.49',
   'count': 75,
   'last_name': 'White',
   'first_name': 'Nicholas J'},
  {'id': 'ur.01343654360.43',
   'count': 59,
   'last_name': 'Marsh',
   'first_name': 'Kevin'},
  .............
  ],
 '_stats': {'total_count': 8735}}

# JSON keys are available also as dict attributes
>>> res['researchers'][0] 
{'id': 'ur.01332073522.49',
 'count': 75,
 'last_name': 'White',
 'first_name': 'Nicholas John'}
# note: res.['researchers'] is also allowed!

# so now let's pull out all names and surnames
>>> [x['first_name'] + " " + x['last_name'] for x in res['researchers']]
['Nicholas John White',  'Kevin Marsh',
 'Nicholas Philip John Day', 'Takafumi Tsuboi',
 'Malcolm Edward Molyneux', 'Kazuyuki Tanabe',
 'Stephen Lev Hoffman', 'Toshihiro Horii',
 'Louis H Miller', 'Francois Henri Nosten',
 'Motomi Torii', 'Alan Frederick Cowman',
 'Patrick Emmet Duffy', 'Satoru Kawai',
 'Alister Gordon Craig', 'Fumihiko Kawamoto',
 'Makoto Hirai', 'Marcelo Urbano Ferreira',
 'Osamu Kaneko', 'Yusuke Wataya']

Using Dimcli in Jupyter Notebooks

DimCli can simplify working with the Dimensions API within a Jupyter notebook.

For example, it contains a couple of Python magic commands that make it super easy to hit the API from a notebook, or to explore the documentation.

For more information and examples see the notebooks available in the official Dimensions API examples repository

Comments, bug reports

Dimcli lives on Github. You can file issues or pull requests there. Suggestions, pull requests and improvements welcome!

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