update readme with new name pyvespa

2 files changed, 8 insertions, 835 deletions

diff --git a/python/vespa/README.md b/python/vespa/README.md
index c316564f3c1..00d8cc2e769 100644
--- a/python/vespa/README.md
+++ b/python/vespa/README.md
@@ -4,7 +4,7 @@
 
 ## Install
 
-`pip install vespa`
+`pip install pyvespa`
 
 ## Connect to a Vespa app
 
@@ -52,16 +52,9 @@ query_result = app.query(
 ```
 
 ```
-query_result["root"]["fields"]
+query_result.number_documents_retrieved
 ```
 
-
-
-
-    {'totalCount': 1077}
-
-
-
 ## Labelled data
 
 > How to structure labelled data
@@ -97,346 +90,6 @@ training_data_batch = app.collect_training_data(
 training_data_batch
 ```
 
-
-
-
-<div>
-<style scoped>
-    .dataframe tbody tr th:only-of-type {
-        vertical-align: middle;
-    }
-
-    .dataframe tbody tr th {
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-
-    .dataframe thead th {
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-</style>
-<table border="1" class="dataframe">
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>attributeMatch(authors.first)</th>
-      <th>attributeMatch(authors.first).averageWeight</th>
-      <th>attributeMatch(authors.first).completeness</th>
-      <th>attributeMatch(authors.first).fieldCompleteness</th>
-      <th>attributeMatch(authors.first).importance</th>
-      <th>attributeMatch(authors.first).matches</th>
-      <th>attributeMatch(authors.first).maxWeight</th>
-      <th>attributeMatch(authors.first).normalizedWeight</th>
-      <th>attributeMatch(authors.first).normalizedWeightedWeight</th>
-      <th>attributeMatch(authors.first).queryCompleteness</th>
-      <th>...</th>
-      <th>textSimilarity(results).queryCoverage</th>
-      <th>textSimilarity(results).score</th>
-      <th>textSimilarity(title).fieldCoverage</th>
-      <th>textSimilarity(title).order</th>
-      <th>textSimilarity(title).proximity</th>
-      <th>textSimilarity(title).queryCoverage</th>
-      <th>textSimilarity(title).score</th>
-      <th>document_id</th>
-      <th>query_id</th>
-      <th>relevant</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>0</th>
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-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>56212</td>
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-      <td>0.0</td>
-      <td>0.187500</td>
-      <td>0.5</td>
-      <td>0.617188</td>
-      <td>0.428571</td>
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-      <td>34026</td>
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-      <td>0.000000</td>
-      <td>0.000000</td>
-      <td>0.000000</td>
-      <td>3</td>
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-      <td>0.0</td>
-      <td>1.000000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>56212</td>
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-      <td>0.187500</td>
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-      <td>0.617188</td>
-      <td>0.428571</td>
-      <td>0.457087</td>
-      <td>34026</td>
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-      <th>6</th>
-      <td>0.0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
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-      <td>0.071429</td>
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-      <td>0.083333</td>
-      <td>0.039286</td>
-      <td>1</td>
-      <td>1</td>
-      <td>1</td>
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-      <td>0.0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
-      <td>1.000000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>29774</td>
-      <td>1</td>
-      <td>0</td>
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-    <tr>
-      <th>8</th>
-      <td>0.0</td>
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-      <td>...</td>
-      <td>0.0</td>
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-      <td>0.500000</td>
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-      <td>1.000000</td>
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-      <td>22787</td>
-      <td>1</td>
-      <td>0</td>
-    </tr>
-  </tbody>
-</table>
-<p>12 rows × 984 columns</p>
-</div>
-
-
-
 ## Evaluating a query model
 
 > Define metrics and evaluate query models. See the [evaluation page](/vespa/evaluation) for more examples.
@@ -463,57 +116,3 @@ evaluation = app.evaluate(
 )
 evaluation
 ```
-
-
-
-
-<div>
-<style scoped>
-    .dataframe tbody tr th:only-of-type {
-        vertical-align: middle;
-    }
-
-    .dataframe tbody tr th {
-        vertical-align: top;
-    }
-
-    .dataframe thead th {
-        text-align: right;
-    }
-</style>
-<table border="1" class="dataframe">
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>query_id</th>
-      <th>match_ratio_retrieved_docs</th>
-      <th>match_ratio_docs_available</th>
-      <th>match_ratio_value</th>
-      <th>recall_10_value</th>
-      <th>reciprocal_rank_10_value</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>0</th>
-      <td>0</td>
-      <td>1267</td>
-      <td>62529</td>
-      <td>0.020263</td>
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-    <tr>
-      <th>1</th>
-      <td>1</td>
-      <td>887</td>
-      <td>62529</td>
-      <td>0.014185</td>
-      <td>0</td>
-      <td>0</td>
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-  </tbody>
-</table>
-</div>
-
-
diff --git a/python/vespa/docs/index.html b/python/vespa/docs/index.html
index 054c74f3bec..7c55143b923 100644
--- a/python/vespa/docs/index.html
+++ b/python/vespa/docs/index.html
@@ -35,7 +35,7 @@ description: "Provide data analysis support for Vespa applications"
 </div>
 <div class="cell border-box-sizing text_cell rendered"><div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<p><code>pip install vespa</code></p>
+<p><code>pip install pyvespa</code></p>
 
 </div>
 </div>
@@ -55,7 +55,7 @@ description: "Provide data analysis support for Vespa applications"
 
 <div class="inner_cell">
     <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.application</span> <span class="k">import</span> <span class="n">Vespa</span>
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.application</span> <span class="kn">import</span> <span class="n">Vespa</span>
 
 <span class="n">app</span> <span class="o">=</span> <span class="n">Vespa</span><span class="p">(</span><span class="n">url</span> <span class="o">=</span> <span class="s2">&quot;https://api.cord19.vespa.ai&quot;</span><span class="p">)</span>
 </pre></div>
@@ -82,8 +82,8 @@ description: "Provide data analysis support for Vespa applications"
 
 <div class="inner_cell">
     <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.query</span> <span class="k">import</span> <span class="n">Query</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">WeakAnd</span><span class="p">,</span> <span class="n">ANN</span><span class="p">,</span> <span class="n">RankProfile</span>
-<span class="kn">from</span> <span class="nn">random</span> <span class="k">import</span> <span class="n">random</span>
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.query</span> <span class="kn">import</span> <span class="n">Query</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">WeakAnd</span><span class="p">,</span> <span class="n">ANN</span><span class="p">,</span> <span class="n">RankProfile</span>
+<span class="kn">from</span> <span class="nn">random</span> <span class="kn">import</span> <span class="n">random</span>
 
 <span class="n">match_phase</span> <span class="o">=</span> <span class="n">Union</span><span class="p">(</span>
     <span class="n">WeakAnd</span><span class="p">(</span><span class="n">hits</span> <span class="o">=</span> <span class="mi">10</span><span class="p">),</span> 
@@ -143,29 +143,13 @@ description: "Provide data analysis support for Vespa applications"
 
 <div class="inner_cell">
     <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">query_result</span><span class="p">[</span><span class="s2">&quot;root&quot;</span><span class="p">][</span><span class="s2">&quot;fields&quot;</span><span class="p">]</span>
+<div class=" highlight hl-ipython3"><pre><span></span><span class="n">query_result</span><span class="o">.</span><span class="n">number_documents_retrieved</span>
 </pre></div>
 
     </div>
 </div>
 </div>
 
-<div class="output_wrapper">
-<div class="output">
-
-<div class="output_area">
-
-
-
-<div class="output_text output_subarea output_execute_result">
-<pre>{&#39;totalCount&#39;: 1077}</pre>
-</div>
-
-</div>
-
-</div>
-</div>
-
 </div>
     {% endraw %}
 
@@ -240,354 +224,6 @@ description: "Provide data analysis support for Vespa applications"
 </div>
 </div>
 
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-
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-        text-align: right;
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-      <th>attributeMatch(authors.first).averageWeight</th>
-      <th>attributeMatch(authors.first).completeness</th>
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-      <th>attributeMatch(authors.first).matches</th>
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-      <th>attributeMatch(authors.first).normalizedWeightedWeight</th>
-      <th>attributeMatch(authors.first).queryCompleteness</th>
-      <th>...</th>
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-      <th>textSimilarity(results).score</th>
-      <th>textSimilarity(title).fieldCoverage</th>
-      <th>textSimilarity(title).order</th>
-      <th>textSimilarity(title).proximity</th>
-      <th>textSimilarity(title).queryCoverage</th>
-      <th>textSimilarity(title).score</th>
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-      <td>1.000000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>56212</td>
-      <td>0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>...</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.187500</td>
-      <td>0.5</td>
-      <td>0.617188</td>
-      <td>0.428571</td>
-      <td>0.457087</td>
-      <td>34026</td>
-      <td>0</td>
-      <td>0</td>
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-      <th>6</th>
-      <td>0.0</td>
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-      <td>0.0</td>
-      <td>0.0</td>
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-      <td>0.0</td>
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-      <td>0.071429</td>
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-      <td>0.083333</td>
-      <td>0.039286</td>
-      <td>1</td>
-      <td>1</td>
-      <td>1</td>
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-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
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-      <td>1.000000</td>
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-      <td>1</td>
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-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>...</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.500000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>0.333333</td>
-      <td>0.700000</td>
-      <td>22787</td>
-      <td>1</td>
-      <td>0</td>
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-      <th>9</th>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>...</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.058824</td>
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-      <td>0.000000</td>
-      <td>0.083333</td>
-      <td>0.036765</td>
-      <td>5</td>
-      <td>1</td>
-      <td>1</td>
-    </tr>
-    <tr>
-      <th>10</th>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>...</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>1.000000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>1.000000</td>
-      <td>29774</td>
-      <td>1</td>
-      <td>0</td>
-    </tr>
-    <tr>
-      <th>11</th>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>...</td>
-      <td>0.0</td>
-      <td>0.0</td>
-      <td>0.500000</td>
-      <td>1.0</td>
-      <td>1.000000</td>
-      <td>0.333333</td>
-      <td>0.700000</td>
-      <td>22787</td>
-      <td>1</td>
-      <td>0</td>
-    </tr>
-  </tbody>
-</table>
-<p>12 rows × 984 columns</p>
-</div>
-</div>
-
-</div>
-
-</div>
-</div>
-
 </div>
     {% endraw %}
 
@@ -618,7 +254,7 @@ description: "Provide data analysis support for Vespa applications"
 
 <div class="inner_cell">
     <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.evaluation</span> <span class="k">import</span> <span class="n">MatchRatio</span><span class="p">,</span> <span class="n">Recall</span><span class="p">,</span> <span class="n">ReciprocalRank</span>
+<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">vespa.evaluation</span> <span class="kn">import</span> <span class="n">MatchRatio</span><span class="p">,</span> <span class="n">Recall</span><span class="p">,</span> <span class="n">ReciprocalRank</span>
 
 <span class="n">eval_metrics</span> <span class="o">=</span> <span class="p">[</span><span class="n">MatchRatio</span><span class="p">(),</span> <span class="n">Recall</span><span class="p">(</span><span class="n">at</span><span class="o">=</span><span class="mi">10</span><span class="p">),</span> <span class="n">ReciprocalRank</span><span class="p">(</span><span class="n">at</span><span class="o">=</span><span class="mi">10</span><span class="p">)]</span>
 </pre></div>
@@ -657,68 +293,6 @@ description: "Provide data analysis support for Vespa applications"
 </div>
 </div>
 
-<div class="output_wrapper">
-<div class="output">
-
-<div class="output_area">
-
-
-<div class="output_html rendered_html output_subarea output_execute_result">
-<div>
-<style scoped>
-    .dataframe tbody tr th:only-of-type {
-        vertical-align: middle;
-    }
-
-    .dataframe tbody tr th {
-        vertical-align: top;
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-
-    .dataframe thead th {
-        text-align: right;
-    }
-</style>
-<table border="1" class="dataframe">
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>query_id</th>
-      <th>match_ratio_retrieved_docs</th>
-      <th>match_ratio_docs_available</th>
-      <th>match_ratio_value</th>
-      <th>recall_10_value</th>
-      <th>reciprocal_rank_10_value</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>0</th>
-      <td>0</td>
-      <td>1267</td>
-      <td>62529</td>
-      <td>0.020263</td>
-      <td>0</td>
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-      <th>1</th>
-      <td>1</td>
-      <td>887</td>
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-      <td>0.014185</td>
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-
 </div>
     {% endraw %}