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suqingdong · Jan 11, 2023 · 2cff6f6 · 2cff6f6
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diff --git a/docs/source/api/impact_factor.bin.rst b/docs/source/api/impact_factor.bin.rst
diff --git a/docs/source/api/impact_factor.db.rst b/docs/source/api/impact_factor.db.rst
diff --git a/docs/source/api/impact_factor.rst b/docs/source/api/impact_factor.rst
diff --git a/docs/source/api/impact_factor.util.rst b/docs/source/api/impact_factor.util.rst
diff --git a/docs/source/api/modules.rst b/docs/source/api/modules.rst
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -28,7 +28,7 @@
 # -- Project information -----------------------------------------------------
 
 project = 'impact_factor'
-copyright = '2022, suqingdong'
+copyright = '2023, suqingdong'
 author = 'suqingdong'
 
 # The full version, including alpha/beta/rc tags

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -3,7 +3,7 @@
 ====================================
 ImpactFactor |version| Documentation
 ====================================
-ImpactFactor is a Impact Factor Toolkits, which contains ``build``, ``version``, ``search``, ``pubmed_filter`` 
+ImpactFactor is a Impact Factor Toolkits, which contains ``build``, ``search``, ``filter`` 
 sub-commands. You can search the IF of a journal, and you can generate a pubmed filter for NCBI Pubmed.
 
 Installation Guide

diff --git a/docs/source/installation.rst b/docs/source/installation.rst
@@ -4,7 +4,7 @@ Installation guide
 
 Install with ``pip``::
 
-    pip install impact_factor
+    python3 -m pip install -U impact_factor
 
 Install from `source code`_ ::
 

diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
@@ -5,57 +5,26 @@ Tutorials
 ``build``
 =========
 
-Download NCBI Journals
-----------------------
-
-`NCBI Journal List`_
-
-.. _NCBI Journal List: https://www.ncbi.nlm.nih.gov/books/NBK3827/table/pubmedhelp.T.journal_lists/
-
-download with ``wget``::
-
-    wget -c ftp://ftp.ncbi.nih.gov/pubmed/J_Entrez.gz
-    wget -c ftp://ftp.ncbi.nih.gov/pubmed/J_Medline.gz
-
-.. note::
-    You can also download the journals from browser, or you can speed up with ``ascp``
-
-
-Build the Database
+build the database
 ------------------
 
 .. code:: console
 
-    impact_factor build -ef J_Entrez.gz -mf J_Medline.gz -t 32
-
-.. note::
-    * ``--threads N`` parameter can be used to speed up building
-    * ``--echo`` parameter will show the detail processing of building
-
+    impact_factor build # default
 
+    impact_factor -d test.db build -i IF.xlsx
 
-``version``
-===========
-
-Show the informations of database
-
-.. code:: console
-
-    impact_factor version
-
-might shown as follows::
+.. note::
+    * ``-d dbfile`` specify a dbfile
+    * ``-i excel``  specify a excel file
 
-    ==========================================================
-    program version:    1.0.0
-    database version:   2020 [2020-08-20 15:32:34.141140]
-    total journals:     9167
-    indexed journals:   8714
-    database filepath:  /data/work/suqingdong/code/impact_factor/impact_factor/data/impact_factor.db
-    ==========================================================
 
 ``search``
 ==========
 
+search the database
+-------------------
+
 * search with ISSN::
 
     impact_factor search 0028-0836
@@ -73,40 +42,41 @@ might shown as follows::
     impact_factor search "nature com%"
 
 
-``pubmed_filter``
+``filter``
 =================
 
+filter with factor
+------------------
+
 IF >= 30::
 
-    impact_factor pubmed_filter -min 30
+    impact_factor filter -min 30
     
 IF <= 1::
 
-    impact_factor pubmed_filter -min 1
+    impact_factor filter -min 1
 
 5 <= IF <= 10::
 
-    impact_factor pubmed_filter -min 5 -max 10
+    impact_factor filter -min 5 -max 10
 
-save result to a file::
+output pubmed filter format::
 
-    impact_factor pubmed_filter -min 5 -max 10 -o 5_10.txt
+    impact_factor filter -min 5 -max 10 --pubmed-filter
 
 
 use as a module
 ===============
 .. code:: python
 
-    from impact_factor import ImpactFactor
-
-    IF = ImpactFactor()
-
-    IF.check_version()
+    from impact_factor.core import Factor
 
-    IF.search('nature')
+    fa = Factor()
 
-    IF.search('nature com%')
+    print(fa.dbfile)
 
-    IF.pubmed_filter(min_value=30)
+    fa.search('nature')
+    fa.search('nature c%')
 
-    IF.pubmed_filter(min_value=5, max_value=10)
+    fa.filter(min_value=100, max_value=200)
+    fa.filter(min_value=100, max_value=200, pubmed_filter=True)