add debug arg & generated docs

- debug argument has been added in order to solve issue #18 using logging interface
- docs generated via windows with make.bat file
- requirements updated and so on requirements.txt modified
- user_agent.py minor fix when file was empty
- code-cov improvement

.travis.yml

@@ -8,12 +8,12 @@ python:
 dist: xenial
 
 install:
-  - pip install pandas==0.24.2
+  - pip install pandas==0.25.0
   - pip install requests==2.22.0
-  - pip install lxml==4.3.3
-  - pip install Unidecode==1.0.23
-  - pip install investpy==0.8.7
-  - pip install pytest==4.5.0
+  - pip install lxml==4.4.1
+  - pip install Unidecode==1.1.1
+  - pip install investpy==0.8.8
+  - pip install pytest==5.1.0
   - pip install codecov==2.0.15
   - pip install pytest-cov==2.7.1
 

README.md

@@ -21,7 +21,7 @@ investpy seeks to be one of the most used Python packages when it comes to histo
 
 In order to get this package working you will need to install [**investpy**](https://pypi.org/project/investpy/) using pip on the terminal by typing:
 
-``$ pip install investpy==0.8.7``
+``$ pip install investpy==0.8.8``
 
 Every package used is listed in [requirements.txt](https://github.com/alvarob96/investpy/blob/master/requirements.txt) file, which can also be installed via pip:
 
@@ -40,7 +40,7 @@ As the main functionality is based on historical data retrieval, the usage of ev
 ```python
 import investpy
 
-df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending')
+df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -51,8 +51,11 @@ Date
 2019-07-16  4.971  5.008  4.913  4.947  30730000
 2019-07-17  4.905  4.965  4.900  4.952  22410000
 2019-07-18  4.856  4.894  4.812  4.879  35820000
+```
+```python
+import investpy
 
-df = investpy.get_historical_data(equity='bbva', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending')
+df = investpy.get_historical_data(equity='bbva', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -70,7 +73,7 @@ Date
 ```python
 import investpy
 
-df = investpy.get_fund_recent_data(fund='bbva plan multiactivo moderado pp', as_json=False, order='ascending')
+df = investpy.get_fund_recent_data(fund='bbva plan multiactivo moderado pp', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -81,8 +84,12 @@ Date
 2019-07-16  1.130  1.130  1.130  1.130
 2019-07-17  1.129  1.129  1.129  1.129
 2019-07-18  1.126  1.126  1.126  1.126
+```
 
-df = investpy.get_fund_historical_data(fund='bbva plan multiactivo moderado pp', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending')
+```python
+import investpy
+
+df = investpy.get_fund_historical_data(fund='bbva plan multiactivo moderado pp', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -100,7 +107,7 @@ Date
 ```python
 import investpy
 
-df = investpy.get_etf_recent_data(etf='bbva accion dj eurostoxx 50', as_json=False, order='ascending')
+df = investpy.get_etf_recent_data(etf='bbva accion dj eurostoxx 50', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -111,8 +118,12 @@ Date
 2019-07-16  36.040  36.085  35.835  35.845
 2019-07-17  35.830  36.080  35.810  35.965
 2019-07-18  35.640  35.785  35.515  35.515
+```
+
+```python
+import investpy
 
-df = investpy.get_etf_historical_data(etf='bbva accion dj eurostoxx 50', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending')
+df = investpy.get_etf_historical_data(etf='bbva accion dj eurostoxx 50', from_date='01/01/2018', to_date='12/08/2019', as_json=False, order='ascending', debug=False)
 print(df.head())
 
 >>>
@@ -148,7 +159,8 @@ import investpy
 fund_information = investpy.get_fund_information(fund='bbva plan multiactivo moderado pp', as_json=True)
 print(fund_information)
 
->>> {'Fund Name': 'Bbva Plan Multiactivo Moderado Pp',
+>>> {
+ 'Fund Name': 'Bbva Plan Multiactivo Moderado Pp',
  'Rating': '4',
  '1-Year Change': '-1,19%',
  'Previous Close': '1.103',
@@ -163,7 +175,8 @@ print(fund_information)
  'Expenses': 'N/A',
  'Min Investment': '30',
  'Market Cap': '34820000000',
- 'Category': 'Mixtos Euros Moderados PP'}
+ 'Category': 'Mixtos Euros Moderados PP'
+}
 ```
 
 ## Contribute - [![Open Source Helpers](https://www.codetriage.com/alvarob96/investpy/badges/users.svg)](https://www.codetriage.com/alvarob96/investpy)

docs/_build/html/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 97a01e1d03a1e0b89532148ecd198ed5
+config: aae0ab10b00495dd3c5f1098fa8d43dd
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_build/html/_sources/api.rst.txt

@@ -7,4 +7,5 @@ API Reference
    main_api.rst
    equities_api.rst
    funds_api.rst
-   etfs_api.rst
+   etfs_api.rst
+   user_agent.rst

docs/_build/html/_sources/equities.rst.txt

@@ -10,7 +10,7 @@ protect investors from fraudulent practices. Historically, they have outperforme
 run. These investments can be purchased from most online stock brokers.
 
 In this case, historical data from stocks or equities is retrieved from `Investing Equities <https://es.investing.com/equities/spain>`_
-just for the Spanish Stock Market, on the current release 0.8.7.
+just for the Spanish Stock Market, on the current release 0.8.8.
 
 Getting Started
 ---------------
@@ -54,10 +54,10 @@ have been developed in order to retrieve both recent and historical data between
 So on an example is proposed in order to clarify the use of investpy for historical data retrieval::
 
     # Retrieves the recent data of BBVA (last month) as a pandas.DataFrame on ascending order
-    df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending')
+    df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending', debug=False)
 
     # Retrieves the historical data of BBVA on the specified date range as a pandas.DataFrame on ascending order
-    df = investpy.get_historical_data(equity='bbva', start='01/01/2010', end='01/01/2019', as_json=False, order='ascending')
+    df = investpy.get_historical_data(equity='bbva', from_date='01/01/2010', to_date='01/01/2019', as_json=False, order='ascending', debug=False)
 
 As we already saw, both functions take a lot of parameters, but some of them are *optional* which means that the function
 does not need the user to specify them.

docs/_build/html/_sources/installation.md.txt

@@ -29,5 +29,5 @@ it will install the following dependencies:
 
 .. note::
 
-    After installing the package you are now available to use it! As investpy's latest release is 0.8.7 the installation is
+    After installing the package you are now available to use it! As investpy's latest release is 0.8.8 the installation is
     optimized for it. If you try installing another investpy release, some features may not work.

docs/_build/html/_sources/installation.rst.txt

@@ -5,7 +5,7 @@ Installation
 
 .. note::
 
-    After installing the package you are now available to use it! As investpy's latest release is 0.8.7 the installation is
+    After installing the package you are now available to use it! As investpy's latest release is 0.8.8 the installation is
     optimized for it. If you try installing another investpy release, some features may not work.
 
 First Installation

docs/_build/html/_sources/introduction.rst.txt

@@ -43,7 +43,7 @@ Reference. So a block of code in order to get to test investpy usage is presente
     equities = investpy.get_equities_list()
 
     # Retrieve the recent historical data (past month) of an equity as a pandas.DataFrame on ascending date order
-    df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending')
+    df = investpy.get_recent_data(equity='bbva', as_json=False, order='ascending', debug=False)
 
     # Retrieve the company profile of the introduced equity on english
     profile = investpy.get_company_profile(equity='bbva', language='english')

docs/_build/html/_static/documentation_options.js

@@ -1,6 +1,6 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: '0.8.7',
+    VERSION: '0.8.8',
     LANGUAGE: 'None',
     COLLAPSE_INDEX: false,
     FILE_SUFFIX: '.html',

docs/_build/html/api.html

@@ -8,7 +8,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-  <title>API Reference &mdash; investpy 0.8.7 documentation</title>
+  <title>API Reference &mdash; investpy 0.8.8 documentation</title>
 
 
 
@@ -60,7 +60,7 @@
 
 
               <div class="version">
-                0.8.7
+                0.8.8
               </div>
 
 
@@ -95,6 +95,7 @@
 <li class="toctree-l2"><a class="reference internal" href="equities_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.equities</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="funds_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.funds</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="etfs_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.etfs</span></code></a></li>
+<li class="toctree-l2"><a class="reference internal" href="user_agent.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.user_agent</span></code></a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="information.html">Additional Information</a></li>
@@ -171,6 +172,7 @@ <h1>API Reference<a class="headerlink" href="#api-reference" title="Permalink to
 <li class="toctree-l1"><a class="reference internal" href="equities_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.equities</span></code></a></li>
 <li class="toctree-l1"><a class="reference internal" href="funds_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.funds</span></code></a></li>
 <li class="toctree-l1"><a class="reference internal" href="etfs_api.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.etfs</span></code></a></li>
+<li class="toctree-l1"><a class="reference internal" href="user_agent.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">investpy.user_agent</span></code></a></li>
 </ul>
 </div>
 </div>

docs/_build/html/contribution.html

@@ -8,7 +8,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-  <title>Contribute to investpy - &mdash; investpy 0.8.7 documentation</title>
+  <title>Contribute to investpy - &mdash; investpy 0.8.8 documentation</title>
 
 
 
@@ -58,7 +58,7 @@
 
 
               <div class="version">
-                0.8.7
+                0.8.8
               </div>
 
 

docs/_build/html/disclaimer.html

@@ -8,7 +8,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-  <title>Disclaimer &mdash; investpy 0.8.7 documentation</title>
+  <title>Disclaimer &mdash; investpy 0.8.8 documentation</title>
 
 
 
@@ -59,7 +59,7 @@
 
 
               <div class="version">
-                0.8.7
+                0.8.8
               </div>
 
 

docs/_build/html/equities.html

@@ -8,7 +8,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
 
-  <title>Stocks/Equities &mdash; investpy 0.8.7 documentation</title>
+  <title>Stocks/Equities &mdash; investpy 0.8.8 documentation</title>
 
 
 
@@ -60,7 +60,7 @@
 
 
               <div class="version">
-                0.8.7
+                0.8.8
               </div>
 
 
@@ -175,7 +175,7 @@ <h1>Stocks/Equities<a class="headerlink" href="#stocks-equities" title="Permalin
 protect investors from fraudulent practices. Historically, they have outperformed most other investments over the long
 run. These investments can be purchased from most online stock brokers.</p>
 <p>In this case, historical data from stocks or equities is retrieved from <a class="reference external" href="https://es.investing.com/equities/spain">Investing Equities</a>
-just for the Spanish Stock Market, on the current release 0.8.7.</p>
+just for the Spanish Stock Market, on the current release 0.8.8.</p>
 <div class="section" id="getting-started">
 <h2>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this headline">¶</a></h2>
 <p>To get started using <a class="reference external" href="https://pypi.org/project/investpy/">investpy</a> you first need to install it as described on
@@ -211,10 +211,10 @@ <h3>Recent &amp; Historical Data<a class="headerlink" href="#recent-historical-d
 have been developed in order to retrieve both recent and historical data between a date range.</p>
 <p>So on an example is proposed in order to clarify the use of investpy for historical data retrieval:</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># Retrieves the recent data of BBVA (last month) as a pandas.DataFrame on ascending order</span>
-<span class="n">df</span> <span class="o">=</span> <span class="n">investpy</span><span class="o">.</span><span class="n">get_recent_data</span><span class="p">(</span><span class="n">equity</span><span class="o">=</span><span class="s1">&#39;bbva&#39;</span><span class="p">,</span> <span class="n">as_json</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="s1">&#39;ascending&#39;</span><span class="p">)</span>
+<span class="n">df</span> <span class="o">=</span> <span class="n">investpy</span><span class="o">.</span><span class="n">get_recent_data</span><span class="p">(</span><span class="n">equity</span><span class="o">=</span><span class="s1">&#39;bbva&#39;</span><span class="p">,</span> <span class="n">as_json</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="s1">&#39;ascending&#39;</span><span class="p">,</span> <span class="n">debug</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
 
 <span class="c1"># Retrieves the historical data of BBVA on the specified date range as a pandas.DataFrame on ascending order</span>
-<span class="n">df</span> <span class="o">=</span> <span class="n">investpy</span><span class="o">.</span><span class="n">get_historical_data</span><span class="p">(</span><span class="n">equity</span><span class="o">=</span><span class="s1">&#39;bbva&#39;</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="s1">&#39;01/01/2010&#39;</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="s1">&#39;01/01/2019&#39;</span><span class="p">,</span> <span class="n">as_json</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="s1">&#39;ascending&#39;</span><span class="p">)</span>
+<span class="n">df</span> <span class="o">=</span> <span class="n">investpy</span><span class="o">.</span><span class="n">get_historical_data</span><span class="p">(</span><span class="n">equity</span><span class="o">=</span><span class="s1">&#39;bbva&#39;</span><span class="p">,</span> <span class="n">from_date</span><span class="o">=</span><span class="s1">&#39;01/01/2010&#39;</span><span class="p">,</span> <span class="n">to_date</span><span class="o">=</span><span class="s1">&#39;01/01/2019&#39;</span><span class="p">,</span> <span class="n">as_json</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="s1">&#39;ascending&#39;</span><span class="p">,</span> <span class="n">debug</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>As we already saw, both functions take a lot of parameters, but some of them are <em>optional</em> which means that the function